Big Data LDN 2019

Paths

Big Data LDN 2019

Author: Big Data LDN

Big Data LDN (London) is a free to attend conference and exhibition, hosting leading data and analytics experts who are ready to equip you with the tools you need to deliver your... Read more

What You Will Learn

  • Data Analytics
  • Big Data
  • Data Science
  • DataOps
  • Artificial Intelligence (AI)
  • Data Governance

Pre-requisites

None.

Keynote Theatre

The Big Data LDN Keynote theater is the centerpiece of the content program where subject matter experts, jetting in from all around the globe, present the latest intelligence and opinion on the industry’s hottest topics. In addition to the foremost speakers in the industry, the keynote track contains remarkable enterprise case studies, transformation journeys, and lively panel debates.

The Database Is Only Half Done

by Big Data LDN

Dec 13, 2019 / 30m

30m

Start Course
Description

Databases represent some of the most successful software that has ever been written and their importance over the last fifty years is hard to overemphasize. Over this time, they have evolved to form a vast landscape of products that cater to different data types, volumes, velocities and query characteristics. But the broad definition of what a database is has changed relatively little. Databases are passive receptacles that store our data and wait to be queried: an approach designed to help humans carry out the activities that businesses need to perform. But today's world is far less dependent on human interaction. Booking a taxi, buying groceries, or applying for a loan to buy a house are all increasingly automated processes driven by machines. This change in purpose forces a fundamental question: Is the database in its current form the right abstraction for this machine-driven world? In this session, Ben Stopford will introduce a new type of database that caters not only for the tables and columns we are familiar with but also the continuous, never-ending streams of events that represent data as it moves.

Table of contents
  1. The Database Is Only Half Done

Your AI Is Wrong! Lessons from Decision-making with Imperfect AI

by Big Data LDN

Dec 13, 2019 / 23m

23m

Start Course
Description

Accounting, auditing, and consultancy firms have typically been slow to adopt AI, relying instead on the continued expertise and experience of highly trained professionals. Now, the rapid acceleration of technology, growth in volumes of data, and rising complexity of regulation seem to be compelling firms to swap human expertise for AI and machine learning. The challenge is that even modern approaches to AI are still far from perfect solutions, especially in areas such as safety, compliance and risk, when outputs have to be 100% accurate. Join Harvey Lewis, EY's Chief Scientist, to hear how firms are being transformed by new thinking around explainable AI and algorithmic supervision. Through real-life case studies, learn how people, still one of a company's greatest assets, are now working side by side with algorithms to achieve accurate, safer, and more collaborative decision-making.

Table of contents
  1. Your AI Is Wrong! Lessons from Decision-making with Imperfect AI

Multiparadigm Data Science: The Next Frontier in Decision Making

by Big Data LDN

Dec 13, 2019 / 25m

25m

Start Course
Description

Has 'Big Data' led to better decisions at your organisation? If your answer isn't an overwhelming 'yes,' then watch Conrad Wolfram's talk. From the core idea of symbolic computation to computable data, notebook interfaces, and the latest in highly automated AI and computational knowledge, Conrad will showcase how a multiparadigm approach can accelerate innovation and unlock actionable insight, including live demos in the Wolfram Technology stack. You will acquire insights on how to define and apply this next frontier, an Enterprise Computation strategy, of your own.

Table of contents
  1. Multiparadigm Data Science: The Next Frontier in Decision Making

Achieving 100% Adoption of Analytics in the Enterprise

by Big Data LDN

Dec 13, 2019 / 29m

29m

Start Course
Description

Traditionally, most business intelligence software has been focused on the individual analyst. While the analyst is a key player obtaining insight for the organisation, a truly intelligent enterprise relies on all employees being able to leverage data and analytics in their day to day decisions. In order to achieve this 100% adoption, enterprises must employ novel new ways of inserting data and analytics into the day to day workflows of their employees in a way that makes their use intuitive and easy. In this session, you will learn the three elements of how an intelligent enterprise designs their analytics and business intelligence platform, how a governed single version of the truth can be paired with agile analytics, and novel new frictionless access for end users to achieve 100% adoption of analytics in the enterprise.

Table of contents
  1. Achieving 100% Adoption of Analytics in the Enterprise

Data Skills: How Mondi Does Digital

by Big Data LDN

Dec 15, 2019 / 20m

20m

Start Course
Description

Organisations are becoming more aware of the importance of data in their daily business, but hiring people with the right skills is only part of the process. Building a Digital Transformation team in a traditional, multinational industry comes with its own challenges. How do you integrate specialists into teams across the globe while ensuring they stay connected and work as one unit? In this talk, Jillian Augustine will introduce the Digital Transformation team, the extended data community, and how Mondi does digital.

Table of contents
  1. Data Skills: How Mondi Does Digital

Building a Modern Data Architecture for the Data Driven Enterprise

by Big Data LDN

Dec 13, 2019 / 30m

30m

Start Course
Description

Big Data LDN 2019 | Building a Modern Data Architecture for the Data Driven Enterprise | Mike Ferguson

Table of contents
  1. Building a Modern Data Architecture for the Data Driven Enterprise

Harnessing the Power of Data to Improve Public Health

by Big Data LDN

Dec 13, 2019 / 23m

23m

Start Course
Description

Tech and data provide the health sector with innovative, more efficient, and cost-effective ways to tackle some of the biggest health challenges our nation faces. This session looks at the role that data plays in a new way of intelligent public health where everyone has access to their health information and many more health interventions are targeted or personalized. Specifically, how Public Health England is exploring how combining consumer generated data with traditional healthcare data could create more meaningful two-way engagement with the public, helping people to take greater control of their well-being, as well as how digital design can improve the uptake of data outputs in decision making. Attendees will leave this session with an understanding of: How the government is harnessing the power of data to use data, artificial intelligence and innovation to transform the prevention, early diagnosis, and treatment of chronic diseases by 2030; as well as helping to achieve an extra five years of Disability Free Life Expectancy, and the unique challenges that those operating in the public health space face when it comes to data.

Table of contents
  1. Harnessing the Power of Data to Improve Public Health

Real-time Data Analytics at Scale Using Cloud Services

by Big Data LDN

Dec 13, 2019 / 28m

28m

Start Course
Description

Working with streaming data at scale is hard. Before you realize, you can end up with a very sophisticated architecture with different moving parts you need to secure, monitor, and scale independently. In this session, you will learn how to work with real-time data, at any scale, by leveraging open source tools, managed services provided by Amazon Web Services, or a combination of both. Key takeaways from Javier Ramirez's talk include identifying the challenges of streaming data, learning different patterns in stream data processing, and moving from on-prem to serverless auto-scaling streaming analytics.

Table of contents
  1. Real-time Data Analytics at Scale Using Cloud Services

Quick and Easy Access to Data through a Logical Data Warehouse Environment

by Big Data LDN

Dec 13, 2019 / 24m

24m

Start Course
Description

Landsbankinn is the leading bank in Iceland because of its unified team, solid infrastructure, satisfied customers, and the benefits it provides to society and the Bank's owners. In order to maintain and improve its position, it needs fast access to unified data and the ability to quickly deliver the resulting insights to its business consumers. What role does the logical data warehouse architecture and data virtualization play in this and how does it work in practise?

Table of contents
  1. Quick and Easy Access to Data through a Logical Data Warehouse Environment

The Promise of Data Mastering at Scale

by Big Data LDN

Dec 13, 2019 / 28m

28m

Start Course
Description

Master data management (MDM) software turned 15 years old this year. Originally launched in 2004 by SAP, master data management systems aimed to help resolve the data unification problem by creating a central source of standardized references to customers, products, employees, suppliers, physical assets and other data across their many IT systems. MDM is valuable, but it's also slow, labor intensive, and costly. As the scale of MDM projects increases to millions of entities and hundreds or thousands of data sources, the traditional methods often fail. Mike Stonebraker will share his view on how MDM technology and MDM organizations must change to fulfill the promise of MDM at scale. He'll discuss how MDM at scale requires machine learning (ML) models, how MDM ML requires humans-in-the-loop, how MDM at scale often requires real-time model update, and how future data mastering innovations will come to market as ML models. You'll learn how MDM technology and MDM organizations must change to fulfill the promise of MDM at enterprise scale.

Table of contents
  1. The Promise of Data Mastering at Scale

Artificial Intelligence (AI)

The sessions in this track separate the hype from the reality and brings artificial intelligence (AI) to life through real-world examples from a range of businesses. You will also find expert advice from those at the forefront of harnessing the power of predictive analytics, machine learning and deep learning algorithms.

Research vs. Reality in AI: Would You Trust Your Model with Your Life?

by Big Data LDN

Dec 13, 2019 / 26m

26m

Start Course
Description

There are many considerations before deploying deep learning models into the real world, especially in safety-critical environments like automated driving, smart medical devices, aerospace, and biomedical applications. A deep learning researcher can achieve 99% accuracy on a deep learning model, but what about the edge cases? What if those edge cases represent someone's life? Is AI ready to move from research to reality? Model accuracy is only one part of a production-ready system, which also includes: model justification and documentation, rigorous testing, use of specialized hardware (GPUs, FPGAs, cloud resources, etc.), and collaboration between multiple people with various expertise related to the project and system. In this session, Heather Gorr will discuss the importance of explainable models, system design, and testing before an AI system is production-ready.

Table of contents
  1. Research vs. Reality in AI: Would You Trust Your Model with Your Life?

Modernise Your IT Infrastructure for AI

by Big Data LDN

Dec 13, 2019 / 19m

19m

Start Course
Description

In this session, learn about the latest best practices for designing end-to-end AI platforms for your data science teams. You can seamlessly fit AI projects into a unified analytics plan with the right infrastructure built for scaling. Brian Carpenter will map out how Pure Storage can support your overall AI strategy by walking through an example AI data hub microservices deployment.

Table of contents
  1. Modernise Your It Infrastructure for AI

Scaling Machine Learning at Holiday Extras

by Big Data LDN

Dec 13, 2019 / 25m

25m

Start Course
Description

This talk will describe how the data science team at Holiday Extras are using Google Cloud Machine Learning Engine to deploy models in production. Rebecca Vickery will be discussing how using Google Cloud machine learning tools can help to democratize data science at scale by allowing data scientists to put models into production independently. Some of the challenges they faced as a small team of data scientists were: Managing bespoke deployment processes for models, a lack of collaboration across the team, and difficulty in finding the right combination of skills to deploy and manage models in operation. Google Cloud Machine Learning Engine has been the impetus for a fully extensible and collaborative machine learning platform and has allowed Holiday Extras to deploy models at speed and scale.

Table of contents
  1. Scaling Machine Learning at Holiday Extras

Why Do Some Machine Learning Models Fail?

by Big Data LDN

Dec 13, 2019 / 27m

27m

Start Course
Description

Most Machine Learning (ML) talks present beautiful cases of success, but, in reality, ML models often fail to deliver the desired performance. It is not uncommon to see developers blaming certain ML models and even providing blacklists of ML models. In this talk, Rafael Garcia-Dias will provide some tips on choosing ML models and guide them through the path of finding a good solution. Rafael will also present two of his recent works that use machine learning in astrophysics and in neuroscience.

Table of contents
  1. Why Do Some Machine Learning Models Fail?

AI: Lessons Learned from the Front Line

by Big Data LDN

Dec 13, 2019 / 29m

29m

Start Course
Description

You want to apply AI to your data to get new insights, but can you? Automation is making it possible for anyone to make use of AI, but hidden barriers and dangers lurk below the surface. Mark Braithwaite will share experiences from Wolfram Research Technical Services projects across a range of industries to distill some key lessons learned. He will also use Wolfram Language live coding demonstrations to show how the right combination of approach and technology can achieve a successful outcome. Examples will be drawn from the health, energy, manufacturing, finance, and media-related industries.

Table of contents
  1. AI: Lessons Learned from the Front Line

Machine Learning in Real-time: Predicting Taxi Fare in NYC

by Big Data LDN

Dec 13, 2019 / 24m

24m

Start Course
Description

Today, the benefit of Machine Learning is conditioned to its deployment in real-time. In this talk, Adam Jelley, Data Scientist, will explain how to deploy a real-time taxi fare prediction engine to power an Uber-like application. Along the cycle of developing such a project, he will highlight key lessons learned, like understand the problem before building models, do not add features for the sake of features, try as many algorithms as possible, and simplify your pipeline before deployment.

Table of contents
  1. Machine Learning in Real-time: Predicting Taxi Fare in NYC

How AI and Automated Machine Learning Will Disrupt the Organisational Alignment of Businesses

by Big Data LDN

Dec 13, 2019 / 31m

31m

Start Course
Description

Businesses have continually evolved how they structured their analytics functions to leverage their best talent. With tools now making it increasingly easy for anyone to do AI, new ways of working are emerging. Learn how businesses are aligning organizationally to democratize AI.

Table of contents
  1. How AI and Automated Machine Learning Will Disrupt the Organisational Alignment of Businesses

Multi-model Powered Machine Learning

by Big Data LDN

Dec 13, 2019 / 25m

25m

Start Course
Description

With the rapid and recent rise of data science, machine learning frameworks, such as TensorFlow, have become popular. However, those frameworks do not form a complete Machine Learning Platform by themselves. In this talk, Jorg Schad will look at what role databases play in the Machine Learning World, in particular Multi-Model databases supporting multiple data models such as graphs, documents, and key-values. Many powerful Machine Learning algorithms are based on graphs, e.g., Page Rank (Pregel), Recommendation Engines (collaborative filtering), text summarization, and other NLP tasks. There are even more applications once you consider data pre-processing and feature engineering which are both vital tasks in Machine Learning Pipelines. But how can you combine Multi-Model Databases with Machine Learning Systems, such as TensorFlow or Pytorch? Using real-world examples, Jorg shows how Multi-Model databases and machine learning frameworks form a very powerful combination. In particular, there will be a focus on graph-based Machine Learning models as well as graph-based data pre-processing and feature engineering (which can, in turn, serve as input for a deep neural network).

Table of contents
  1. Multi-model Powered Machine Learning

ML in Production: Serverless and Painless

by Big Data LDN

Dec 13, 2019 / 33m

33m

Start Course
Description

Productionising machine learning pipelines can be a daunting and difficult task for Data Scientists. Fortunately, many novel tools and technologies have become available in the past years to address this issue and make it easier than ever to deploy ML models into production, without the need to configure servers. In this session, Oliver Gindele will walk through some of the best serverless options on how to operationalise ML pipelines within the Tensorflow ecosystem and on Google Cloud Platform based on actual case studies. One of these real-life case studies will dive into the journey of a global cosmetics brand to become packaging-free with the help of ML. The first step towards this goal allows customers to view product information simply by taking a picture. This completely eliminates the need for packaging and labels in stores. However, in order to do this effectively, an accurate image classification model, accessible on mobile phones, is needed. This session will cover the details of the end-to-end machine learning pipeline that was created to deliver and update performant ML models to mobile users.

Table of contents
  1. ML in Production: Serverless and Painless

Leveraging Data Virtualization to Maximize Advanced Analytics and Machine Learning Potential in Your Data Architecture

by Big Data LDN

Dec 13, 2019 / 24m

24m

Start Course
Description

Machine learning elicits mixed reactions, some consider it a company's new superpower, while others see it as an over-hyped fad that fails to deliver. Either way, companies need to factor in machine learning to obtain better insights from their data and stay competitive. Complemented with data virtualization, machine learning can live up to its true potential. This session with Vincent Fages will explain how data virtualization can be used to get the information needed in a more efficient and agile manner via a demo and a real customer success story.

Table of contents
  1. Leveraging Data Virtualization to Maximize Advanced Analytics and Machine Learning Potential in Your Data Architecture

Blueprint

For many companies who are capturing new and varied data sources using both modern cloud-based systems and legacy on premise ones, the navigation of their data landscape is becoming extremely challenging. This track will guide you through the data architecture maze, giving you a blueprint from which you can more effectively find, store, and govern your data while avoiding vendor lock in.

Bring the Power of Watson to AWS and Azure: Watson Anywhere Powered by Cloud Pak for Data

by Big Data LDN

Dec 13, 2019 / 29m

29m

Start Course
Description

Today's successful enterprises must juggle many different cloud vendors. How do you run consistent Data and AI initiatives in a multicloud world? It's possible with Cloud Pak for Data. Our cloud-native Data and AI platform not only leverages innovative Watson AI services but brings the power of Watson to AWS, Azure, and other major cloud providers. Learn how Watson Anywhere can help you implement, unify, and scale your AI efforts to take your business to the next level in this talk with Chris Williams.

Table of contents
  1. Bring the Power of Watson to AWS and Azure: Watson Anywhere Powered by Cloud Pak for Data

Modern Data Warehousing at Scale Using Azure Data Factory

by Big Data LDN

Dec 13, 2019 / 29m

29m

Start Course
Description

Data is essential in empowering every enterprise's journey in digital transformation. The ability to bring together datasets across the silos to derive deep insights is key to business success. Whether you are an enterprise or an ISV, you need robust and scalable data integration capability to create a variety of data pipelines to modernize your data warehouse. In this session, Shirley Wang will showcase how to use Azure Data Factory to build secure and highly performant ETL/ELT pipelines. We will cover key challenges, common patterns, and best practices based on real-world customer case studies. There will also be demos so you can see how to build, operationalize, and monitor pipelines in a code-free manner. The key objectives are: To understand the target scenarios for using ADF, to understand key design patterns and best practices when building analytics solutions using ADF, to develop an understanding of the application model, and how to get started with ADF.

Table of contents
  1. Modern Data Warehousing at Scale Using Azure Data Factory

Balancing Performance, Scalability, and High Availability in Your Database Environment

by Big Data LDN

Dec 13, 2019 / 24m

24m

Start Course
Description

As the big data landscape evolves, open source software solutions become increasingly important. Percona open source database software is downloaded every 15 seconds and Percona has helped over 3,000 customers worldwide tune and optimize their database environment. Dimitri Vanoverbeke's presentation will walk you through a typical enterprise database scenario. We will consider a multi-cloud environment with the goal of achieving several 9's availability, and share some key tactics that you can use to balance performance, scalability, and high availability.

Table of contents
  1. Balancing Performance, Scalability, and High Availability in Your Database Environment

Enabling Microservices for Big Data On-demand in the Cloud

by Big Data LDN

Dec 13, 2019 / 23m

23m

Start Course
Description

Enterprises, startups, and developers are all moving Big Data workloads to the Cloud. This session will show how DataStax Constellation will enable scalable and robust on-demand data storage based around DataStax Apollo, a new fully-managed version of Apache Cassandra, which is now in extended beta, using your choice of the major cloud vendors. Luke Robinson will also be discussing a new AI-based performance monitoring system called DataStax Insights, as well as a demo of a Microservices API generation tool called AppStax.

Table of contents
  1. Enabling Microservices for Big Data On-demand in the Cloud

From ETL to ELT: Building a Scalable Data Stack with SQL

by Big Data LDN

Dec 13, 2019 / 31m

31m

Start Course
Description

Big Data LDN 2019 | From ETL to ELT: Building a Scalable Data Stack with SQL | Lewis Hemens

Table of contents
  1. From ETL to ELT: Building a Scalable Data Stack with SQL

Data, Governance, and Freedom

by Big Data LDN

Dec 13, 2019 / 26m

26m

Start Course
Description

Any enterprise seeking to create value from data has two conflicting and divergent objectives. On the one hand, cohorts of users and developers need to access data from multiple sources, to create analytics, dashboards, reports and apps. On the other hand, a responsible enterprise must secure, govern and define data in order that users only see what they are permitted to see. In a perfect world, such a system would also deliver nirvana in data terms - the single version of the truth. In this presentation, Nick Barth points out the pitfalls of lack of governance, and how governance can be an enabler to deliver a more intelligent enterprise.

Table of contents
  1. Data, Governance, and Freedom

How to Get the Technology Stack Right for Your Business

by Big Data LDN

Dec 13, 2019 / 26m

26m

Start Course
Description

We spend a lot of time at conferences hearing about all the incredible use cases that people have been delivering, the wild futures ahead in our industries, or how some new technology is going to fix any problem you might have. We don't generally hear about the (often challenging!) journey to take an organisation from the very beginnings of a data strategy, through a successful delivery, to the new business norm. Once you have your data strategy in place, one of the next steps will involve choosing the right platform to support that strategy. Many strategies can fail to deliver because the wrong choices are made early on in this process. There's a lot of choice in the market at the moment and every vendor will be telling you that their technology is the thing you need. So how do you pick a technology stack that aligns properly to your strategy? Join James Lupton to find out 10 questions you should be asking to get things right.

Table of contents
  1. How to Get the Technology Stack Right for Your Business

Data Modelling with Apache Cassandra

by Big Data LDN

Dec 13, 2019 / 30m

30m

Start Course
Description

Any data science initiative depends on data to work. That data has to be modeled and managed well in order to get value out of it. However, the approach we take around data modelling can be influenced by the ways that we store data over time. Understanding this in advance can make it easier to get to answers from our data and also avoid problems caused by bad decisions or overlooking data modelling at the start. In this session, you will learn about applying data modelling based on taking concepts through to logical workflows and understand how to implement a data model on Apache Cassandra

Table of contents
  1. Data Modelling with Apache Cassandra

How to Orchestrate Your ML Pipelines in Hybrid Cloud

by Big Data LDN

Dec 13, 2019 / 31m

31m

Start Course
Description

This talk shows how to integrate Airflow, Tensorflow Extended, and Kubeflow Pipelines to create a production ready Machine Learning pipeline in hybrid cloud. David Sabater Dinter will introduce these open source frameworks and run a demo in Google Cloud Platform to show how powerful these frameworks are together for hybrid cloud solutions.

Table of contents
  1. How to Orchestrate Your ML Pipelines in Hybrid Cloud

Full Stack Metadata Driven Thinking to Drive Business Agility

by Big Data LDN

Dec 13, 2019 / 24m

24m

Start Course
Description

We've all heard about metadata driven approaches in analytics, and indeed particularly in ingestion. What about if you applied this technology to the full stack, metadata driven UI, metadata driven business rules, and, naturally, the analytics, too? Could this approach drive real business agility? Watch this talk with Dan Keeley to find out how a 25 year old datacentric UK charity turned around their data platforms.

Table of contents
  1. Full Stack Metadata Driven Thinking to Drive Business Agility

Enhance Developer Experience Using OpenShift on Azure

by Big Data LDN

Dec 13, 2019 / 27m

27m

Start Course
Description

This talk will demonstrate OpenShift on Azure offering, the first fully managed and easiest to use version of OpenShift in the cloud. Currently, to develop, debug, deploy an application, a developer needs various tool sets to achieve them together and developers have power of choice now and they drive the decision making for it. As Red Hat, we have to embrace this continuity and focus on delivering integrated value to our developer community. We present OpenShift Connector, a VSCode Extension that aims to simplify the OpenShift experience for developers. We will be running this extension that works on top on Kubernetes and OpenShift and helps the developers to create an end-to-end experience from design, code, debug and deploy. This extension currently has more than 15K+ downloads. The talk will conclude with a demo of deploying a Game using following scenarios. Node front end component that uses the open source Phaser Javascript game engine. SpringBoot backend component that uses the Red Hat OpenShift Java API to communicate with Kubernetes and OpenShift. Deploy these components on top of our cloud-native developer tooling for Red Hat OpenShift on Azure. The scenario will cover how to provide your own custom, developer-oriented experience for use with OpenShift on Azure cluster and configure multiple components(agnostic to any language), services, routes for a project with OpenShift on Azure and manage everything from VSCode itself. Thus, there are a ton of easy wins here if you're working with OpenShift and want to spin something up on the cloud quickly.

Table of contents
  1. Enhance Developer Experience Using OpenShift on Azure

Fast Data

The Fast Data track investigates the increasing velocity of Big Data and explores how traditional “batch” processing is being replaced by streaming systems, promising instant data analysis, and rapid insight-to-action.

Fast Data for Faster Business

by Big Data LDN

Dec 13, 2019 / 19m

19m

Start Course
Description

In this case study session, learn how ASOS, a leading global fashion retailer that, scaled their IT architecture to meet global demand as well as modern consumer needs. Learn how Azure, Oracle Retail Suite, and real-time replication technology, HVR, enabled an efficient and scalable solution.

Table of contents
  1. Fast Data for Faster Business

Driving Faster, Smarter Actions on IoT Data with New Real-time Analytics Capabilities

by Big Data LDN

Dec 13, 2019 / 29m

29m

Start Course
Description

The ability to act on customer and IoT data faster and smarter is driving competitive advantages, lowering costs, and reducing risks. Join this session to learn from Phil Tetlow about how you can take advantage of data from IoT and online apps with data science, machine learning, and open source tools in an integrated end-to-end platform for fast data and event-driven application development.

Table of contents
  1. Driving Faster, Smarter Actions on IoT Data with New Real-time Analytics Capabilities

Introduction to Adept and How Big Data and Analytics Is Transforming the Connected Car Ecosystem

by Big Data LDN

Dec 13, 2019 / 28m

28m

Start Course
Description

Big Data LDN 2019 | Introduction to Adept and How Big Data and Analytics Is Transforming the Connected Car Ecosystem | Alan Gawthorpe

Table of contents
  1. Introduction to Adept and How Big Data and Analytics Is Transforming the Connected Car Ecosystem

Bridge to Cloud

by Big Data LDN

Dec 13, 2019 / 26m

26m

Start Course
Description

This session covers architecture best practices and recommendations for organizations aiming for a more cloud-centric approach in the use of Kafka. Getting data from on-prem systems into the cloud is the first step. Is Replicator or MirrorMaker really the best solution? How can you address Cloud-to-Cloud requirements? How does the new Kafka native geo-replication factor in? Connectivity, security, and access controls are important in the cloud, what are the options there? This is at least the direction Peter Gustafsson is going, so based on the earlier talks but more cloud focused with a "best practices/recommendations and how-to" angle.

Table of contents
  1. Bridge to Cloud

How to Train Your AI Models at Scale

by Big Data LDN

Dec 13, 2019 / 14m

14m

Start Course
Description

Redis delivers instant experiences through your applications and for users, combining the advantages of the highest performance, seamless scalability and high availability. Redis is not just the fastest database on the market today but also includes a comprehensive set of management and automated capabilities. In this talk, Kamran Yausaf will share how to co-locate and execute your trained AI models for personalisation, recommendation, and fraud detection with your data to provide real time insights at scale.

Table of contents
  1. How to Train Your AI Models at Scale

99% of Your IoT Data Is Worthless, but Which 99%?

by Big Data LDN

Dec 13, 2019 / 28m

28m

Start Course
Description

Organisations are paralyzed by the volume of time series (IoT) data currently being generated. There's too much data to transfer from devices over expensive bandwidth and databases are growing too large to quickly and effectively interrogate. But, what if 99% of that data could simply be thrown away? Datalytyx CTO, Guy Adams, will explain how our software, Gallium, delivers 99% accuracy using only 1% of the source data. You'll learn: The reasons why organisations are not able to leverage the vast amount of data they are collecting, how currently accepted methods of data reduction sacrifice accuracy for speed, and how Gallium makes it possible to work with huge volumes of data to get accurate information in a fraction of the time.

Table of contents
  1. 99% of Your Iot Data Is Worthless, but Which 99%?

Data Engineering in MagicLab: The Birth and Life of an Event

by Big Data LDN

Dec 13, 2019 / 16m

16m

Start Course
Description

Every day, the Business Intelligence unit in MagicLab (an umbrella to Badoo, Bumble, Chappy and Lumen brands) is receiving 28 bln events. Learn how the Data Engineering team defines, receives, processes, and presents all of that data, all in one talk.

Table of contents
  1. Data Engineering in MagicLab: The Birth and Life of an Event

RNA - Event Stream Processing Made Simple

by Big Data LDN

Dec 13, 2019 / 30m

30m

Start Course
Description

With an Master of Science in Computer Science and over 15 years of experience in international enterprises as Head of IT Innovation and CTO, Roberto Bentivoglio is now the COO of Radicalbit, a product company specialized in streaming technologies and real-time data. In the balanced combination of hard skills and a strong business sense, he found his personal formula to contribute successfully to the company growth.

Table of contents
  1. RNA - Event Stream Processing Made Simple

When Data Leads, Transformation Follows - A Look at Qlik's Data Integration Portfolio

by Big Data LDN

Dec 13, 2019 / 30m

30m

Start Course
Description

In this session you'll learn how Qlik is accelerating DataOps for analytics with our new modern data integration platform that combines the recently acquired Attunity products together with Qlik Data Catalyst. We'll share use cases and demonstrations that highlight the tremendous impact that real-time data delivery, automation and catalogs have with cloud data lake and warehouse initiatives, with examples from enterprise organizations.

Table of contents
  1. When Data Leads, Transformation Follows - A Look at Qlik’s Data Integration Portfolio

Saving Energy in Homes with a Unified Approach to Data and AI

by Big Data LDN

Dec 13, 2019 / 19m

19m

Start Course
Description

Energy wastage by residential buildings is a significant contributor to total worldwide energy consumption. Quby, an Amsterdam based technology company, offers solutions to empower homeowners to stay in control of their electricity, gas, and water usage. Using Europe's largest energy data-set, consisting of petabytes of IoT data, the company has developed AI powered products that are used by hundreds of thousands of users on a daily basis. In this talk, Erni Durdevic will take you on a tour of how Quby leverages the full Databricks stack to quickly prototype, validate, scale and launch data science products. We will explore the technical workflow of a Data Science project from end to end. Starting from developing a notebook prototype and tracking model performance with MLFlow, we move towards production-grade Databricks jobs with a CI/CD pipeline and monitoring system in place. We will see how Quby manages more than 1 million models in production, how Delta Lake allows batch and streaming on the same IoT data, and the impact these tools have had on the team itself.

Table of contents
  1. Saving Energy in Homes with a Unified Approach to Data and AI

Building Stream Processing Applications with Apache Kafka Using KSQL

by Big Data LDN

Dec 13, 2019 / 31m

31m

Start Course
Description

Apache Kafka is a de facto standard streaming data processing platform, being widely deployed as a messaging system, and having a robust data integration framework (Kafka Connect) and stream processing API (Kafka Streams) to meet the needs that common attend real-time message processing. But there's more! KSQL is a declarative, SQL-like stream processing language that lets you easily define powerful stream-processing applications. What once took some moderately sophisticated Java code can now be done at the command line with a familiar and eminently approachable syntax. Filtering one stream of data into another, creating derived columns, even joining two topics together‚ it's all possible with KSQL. Watch Robin Moffatt's talk for a thorough overview of KSQL. There'll be plenty of live coding on streaming data to clearly illustrate KSQL's awesome power!

Table of contents
  1. Building Stream Processing Applications with Apache Kafka Using KSQL

Real-world, Real-time Digital Transformation

by Big Data LDN

Dec 13, 2019 / 28m

28m

Start Course
Description

In this presentation, Steve Wilkes will discuss real-world case studies from multiple industries highlighting the role streaming data has played in their digital transformation strategies. You will see how, by harnessing real-time data and utilizing the appropriate new technologies, organizations from the Finance, Retail, Transportation, and Telecommunications sectors have modernized their businesses and streamlined operations.

Table of contents
  1. Real-world, Real-time Digital Transformation

Machine Data in Industry 4.0: How to Handle It Better

by Big Data LDN

Dec 13, 2019 / 26m

26m

Start Course
Description

The rise of IoT and smart infrastructure has led to the generation of massive amounts of complex data. Traditional solutions struggle to cope with this shift, leading to a decrease in performance and an increase in cost. In this talk, we will take a look at this kind of data coming from real-world smart factory sensors. Participants will learn how to create a data pipeline for ingestion and visualization. By the end of this session, you will be able to set up a highly scalable data pipeline for complex time series data with real time query performance.

Table of contents
  1. Machine Data in Industry 4.0: How to Handle It Better

DataOps

The DataOps track examines the tools and techniques required to collect, distribute, and control access to data.

Why CockroachDB in the Kindred Platform?

by Big Data LDN

Dec 13, 2019 / 22m

22m

Start Course
Description

Kindred is an online gambling group with over 25 million registered customers and a portfolio of 11 brands within sportsbook, casino, and games. The customers are at the heart of everything Kindred does. Kindred wants to give them the best customer experience in a safe environment and meet all required regulatory requirements. The team also wants to achieve a state of the art disruption and disaster resilience. This talk will focus on why CockroachDB was chosen to meet all of these requirements.

Table of contents
  1. Why CockroachDB in the Kindred Platform?

The Hardest Part of AI & Analytics Is Not AI, It Is Data Management

by Big Data LDN

Dec 13, 2019 / 23m

23m

Start Course
Description

AI and predictive analytics hold a great promise for organisations. Fraud detection, next-best action, operational efficiency and forecast analysis are among the many business challenges that AI and analytics can help solve. However, bad data is currently hindering AI since machine learning (ML) models are only as good as the data you feed them. In this session, Greg Hanson of Informatica will discuss an end-to-end data engineering approach to achieving good clean data you can trust for successful AI initiatives. This approach includes data discovery, ingestion, integration, quality, prep, and governance.

Table of contents
  1. The Hardest Part of AI & Analytics Is Not AI, It Is Data Management

Effective Cloud Migration Strategies for Your Modern Data Applications

by Big Data LDN

Dec 13, 2019 / 17m

17m

Start Course
Description

Whether you are looking to establish a "cloud first" strategy for big data or you are migrating from on-premises Cloudera, Hortonworks, and MapR, this session provides practical insights on how to make that journey simple and cost effective regardless the public cloud vendor. Join Chris Santiago as he shares how a data driven approach can guide you in deciding which cloud technologies will best fit the needs unique to your organisation and budget.

Table of contents
  1. Effective Cloud Migration Strategies for Your Modern Data Applications

Snowflake? Why Should I Care?

by Big Data LDN

Dec 13, 2019 / 27m

27m

Start Course
Description

Snowflake is the most talked-about database solution of recent years. In this talk, Graham Mossman will describe what Snowflake is and give ten reasons (in no particular order) why you should care.

Table of contents
  1. Snowflake? Why Should I Care?

The Future of Business Intelligence Isn't a Tool

by Big Data LDN

Dec 13, 2019 / 30m

30m

Start Course
Description

Business data has changed radically. Enterprises today use thousands of SaaS applications and business systems that create more data than ever imagined, resulting in a struggle for users to gain holistic and actionable insights. Organizations need a solution to simplify the end to end workflow - from data prep and governance to visualization, delivery, and action. This talk with Jonathan Walls will reveal a proven solution with real world examples and how it creates future opportunities for your organization.

Table of contents
  1. The Future of Business Intelligence Isn't a Tool

AI-driven Retail for the 21st Century

by Big Data LDN

Dec 17, 2019 / 23m

23m

Start Course
Description

Despite many early initiatives, most retailers know that they could derive greater value from the data at their disposal. How can they achieve this? In this session, Andy Hopcraft will overview how SDG Group is transforming marketing, operations and supply chain for some of the best-known brand retailers through the application of AI and ML, leveraging a modern cloud data architecture. SDG will discuss their approach, methodology and platform using real-world scenarios.

Table of contents
  1. AI-driven Retail for the 21st Century

The Next Generation of Data Architecture

by Big Data LDN

Dec 20, 2019 / 23m

23m

Start Course
Description

Modern use cases, such as Customer Journey and Hyper Personalization, have blurred the boundaries between operational and analytics systems. The legacy operational databases and enterprise data warehouses find it challenging to keep up with the demands in terms of agility, variety, and playing in an ecosystem of open source, ML and cloud data platforms where everything is consumed as a service. Understand how a next gen hybrid data architecture with a cloud data warehouse as its foundation, unifies the operational and analytics capabilities to help deliver on modern use cases. Learn what the key capabilities of how to implement a next generation hybrid cloud data warehouse that is agile enough to address the changing needs, flexible to give you the best cost for performance and help you leverage with existing IT investments. Gain insight in how to successfully migrate from legacy data warehouses from Netezza, Teradata and Oracle Exadata. In addition, Pradeep Bhanot will also address the needs and demands of personas like data scientists, business analysts, IT users, and business users who bring unique hyper personalization requirements to tomorrow’s data architecture.

Table of contents
  1. The Next Generation of Data Architecture

Modern Enterprise Data Engineering

by Big Data LDN

Dec 17, 2019 / 18m

18m

Start Course
Description

We envision a world where enterprise data customers readily have access to high-quality, cross-silo, unified enterprise data for all of their core logical entities. Data Operations (DataOps) is a methodology consisting of people, processes, tools, and services for enterprises to rapidly, repeatedly, and reliably deliver production-ready data from the vast array of enterprise data sources. Learn how to and why implementing these key ingredients can help a business achieve the analytic velocity necessary to create a competitive advantage.

Table of contents
  1. Modern Enterprise Data Engineering

Taking Control of User Analytics with Snowplow

by Big Data LDN

Dec 17, 2019 / 22m

22m

Start Course
Description

This talk describes how Auto Trader migrated to Snowplow on Google Cloud for their user-analytics platform. Snowplow is an event streaming pipeline that provides many features such as a unified log of your users, event enrichment, and a schema registry to enforce data integrity. Paul Doran will walk through why Auto Trader chose to migrate, the overall Snowplow platform, the architectural benefits and how using Google BigQuery and DataFlow has been a huge success for Auto Trader.

Table of contents
  1. Taking Control of User Analytics with Snowplow

Flex Your Data(Ops) Muscles

by Big Data LDN

Dec 17, 2019 / 31m

31m

Start Course
Description

The advent of data platforms from AWS, Microsoft Azure, Cloudera, and Google Cloud gives every business the ability to swipe a credit card and have access to virtually any computing service to handle just about any data initiative. Yet, why are so many organizations still struggling to drive meaningful ROI from their data investments? The answer starts with DataOps. In this session, David Barkaway discuss the role of data wrangling in DataOps and key considerations in modernizing data management in the cloud and beyond.

Table of contents
  1. Flex Your Data(Ops) Muscles

You Love Big Data, so Does R

by Big Data LDN

Dec 17, 2019 / 29m

29m

Start Course
Description

Using R with Big Data is easier than you think! In this session, Alex Gold demonstrates how R can integrate with tools you know and love, allowing you and your data scientists to leverage the power of big data more easily than ever. This session will focus on using R to orchestrate workflows and communicate insights from data that doesn't fit into memory.

Table of contents
  1. You Love Big Data, so Does R

Building Predictive Maintenance Solutions

by Big Data LDN

Dec 17, 2019 / 16m

16m

Start Course
Description

There are numerous and varying definitions of DataOps, a new methodology which helps businesses effectively use their data to drive innovation and secure competitive advantage. However, no definition fails to mention the importance of metadata for the DataOps strategy - it is essential for data management, governance, and provenance. In the face of newfound necessities of edge computing, the Internet of Things (IoT), and statistical expressions of Artificial Intelligence (AI), there are shifts occurring in metadata management that require further attention. For this reason, in this session Dr. Agne Gvozdevaite will discuss the importance and best practice of DataOps metadata management for now and the future.

Table of contents
  1. Building Predictive Maintenance Solutions

Quickly, Codelessly Connect Any Application to Any REST API

by Big Data LDN

Dec 17, 2019 / 18m

18m

Start Course
Description

In today’s digital business landscape, data is fragmented and scattered across various systems. Pulling all this data together is a significant challenge, and with businesses constantly implementing new data sources, integration complexities just keep multiplying. In this presentation, James Goodfellow explores a new approach to data access that seamlessly connects and integrates with REST APIs without coding. The results include more productive developers and easy and fast access to the data that you need to find insights and drive value.

Table of contents
  1. Quickly, Codelessly Connect Any Application to Any REST API

Rethinking Data Warehouse Modernization in the Age of Hybrid Cloud/On-premise Data Warehouses

by Big Data LDN

Dec 17, 2019 / 28m

28m

Start Course
Description

Data Warehouse Modernization - On the surface, sounds like a no-brainer to move to a shiny new system that runs in the cloud, costs a fraction of what you were paying before, and can be turned on and off like a light switch. New advances have transformed how to think about enterprise data warehouse modernization. Traditional thinking was migrating legacy data warehouses, such as Netezza, Teradata or Exadata, could be challenging and risky. Today, a new generation of cloud/on-premise data warehouses with innovative hybrid architecture and high-performance advanced analytics make the leap to data warehouse modernization easier and more compelling than ever.

Table of contents
  1. Rethinking Data Warehouse Modernization in the Age of Hybrid Cloud/On-premise Data Warehouses

From Waterfall to Agile – A Data Warehouse Modernisation Story

by Big Data LDN

Dec 17, 2019 / 23m

23m

Start Course
Description

Admiral’s disparate and complex data ecosystem had outgrown waterfall methodologies and hand coding, and wasn't fit for the company’s digital ambitions. In this session, James Gardiner describes the business message of how Data Automation software enabled his team to adopt an agile mindset and create a repeatable, automated framework in just a few months. James’ colleagues Cara Monk and Aaran Morris will then explain what happened at a technical level – how the addition of Continuous Integration, Continuous Deployment, Continuous Testing, and monitoring methodologies added agility to their overall process.

Table of contents
  1. From Waterfall to Agile – A Data Warehouse Modernisation Story

Freeing up Engineering and Infrastructure Resources to Scale with DataOps

by Big Data LDN

Dec 17, 2019 / 24m

24m

Start Course
Description

When you're one of the world’s largest tech unicorns and you're dealing with the health and lives of hundreds of millions of people, you don't want to be the bottleneck. That was the data platform engineering team at Babylon Health and so began the Babylon with Lenses.io journey to introduce DataOps tools and practices to scale their business. In this session, understand the complexity of Babylon’s data challenges as their business exploded into new markets by the month, the tools, processes, and GitOps practices Babylon had to put in place to scale.

Table of contents
  1. Freeing up Engineering and Infrastructure Resources to Scale with DataOps

Data-driven LDN

These sessions focus on modern data management, integration, and analytics use cases.

Unit Testing with pytest

by Big Data LDN

Dec 17, 2019 / 20m

20m

Start Course
Description

As more models are being developed to help businesses understand and serve customers better, it is crucial to ensure the code written behind these model pipelines have been sufficiently tested to ensure various components perform as expected. In this talk, Tola Alade will focus on unit testing using pytest, a Python based test framework, and showing some examples on how to increase trust in your model pipelines by writing good unit tests.

Table of contents
  1. Unit Testing with pytest

Credit Card Fraud – Why the Database Matters

by Big Data LDN

Dec 17, 2019 / 26m

26m

Start Course
Description

Barclays processes circa 30 million-plus payment transactions a day for its 20 million-plus customers and had many fraud detection solutions in place across its various business units. Barclays knew transaction fraud detection required ultra low latency, but not having the ability to seamlessly re-use its large-scale user profile datasets across use cases across its business units resulted in multiple complex, bespoke engineering solutions. These solutions became increasingly difficult to both maintain and evolve, and thus posed a significant limitation to achieving the company’s strategy. As more time is taken during an End-to-End fraud detection process, more risk is introduced. These risks include stand-in processing (STIP), the rise of data consistency issues, which in turn can lead to increased false positives and false negatives for future transactions. Comprehensive expert analysis of the problem revealed that most of these issues could be tracked back to a limiting database deployment and technology. Implementing a new database technology, the payment fraud team at Barclays ended up with a fraud-detection system which solved its problems. The resulting solution could scale the Barclays dataset from 3TB to 30TB-plus over the course of just three years, share fraud rules across platforms, and facilitate machine learning consistently with an aim to achieve a maximum of two digit (<100) millisecond response time for the 99.99 percentile of transactions. Perhaps the database for credit card fraud matters after all?

Table of contents
  1. Credit Card Fraud – Why the Database Matters

Data Science at SEGA

by Big Data LDN

Dec 17, 2019 / 29m

29m

Start Course
Description

SEGA is one of the leading interactive entertainment companies in the world. Their studios include Sports Interactive, Amplitude, The Creative Assembly, HardLight, and Relic Entertainment. SEGA Europe is responsible for games such as Football Manager and the Total War series. This talk will cover how data science techniques are introduced to the business and their studios, and outline some of their potential applications for a video game publisher. Stanley Wang will share experiences of transitioning from a university graduate to the first data scientist hired at SEGA Europe as well as the challenges of building a foundation for a data driven approach for all areas of the business. Examples of current ongoing projects are provided throughout the talk to help better understand in-game player behavior, consumer habits, and purchase patterns, all in order to improve the overall player experience.

Table of contents
  1. Data Science at SEGA

British Telecom: Data-driven Digital Transformation

by Big Data LDN

Dec 17, 2019 / 22m

22m

Start Course
Description

Under the guidance of a "data-driven" approach, organizations must build and develop ecosystem capabilities that enable comprehensive customer understanding, intelligent decision-making, and enhance service quality and decision-making efficiency. Unlike digital native companies, traditional organisations only have access to limited, traditional customer behavior data such as financial transactions and asset information. Horia Selegean, Data Governance Director, will share the journey that British Telecom (BT) have embarked on for data-driven digital transformation. Horia will also share best practices and lessons learned to date on how to cope with the challenge of an organisation that needs to build an ecosystem and obtain data through service innovation or cross-industry operations. All of this to support faster business growth and make more open and agile service provisioning and deployment possible.

Table of contents
  1. British Telecom: Data-driven Digital Transformation

Using Cloud Solution Platforms to Drive Business Value and Cost Optimization

by Big Data LDN

Dec 17, 2019 / 24m

24m

Start Course
Description

Discover how customers across multiple industries have driven business value and cost optimization with Atos cloud strategies. The Atos cloud solution platform includes end-to-end big data, analytics, and container managed platform-as-a-service, helping customers to reduce capital and operational costs. In addition, end-users are able to leverage proven, re-usable, open standards architecture for new data-based services. All of this is secure, scalable and fully supported: this common data analytics set-up can be leveraged for multiple use cases, leveraging best practice tools and techniques.

Table of contents
  1. Using Cloud Solution Platforms to Drive Business Value and Cost Optimization

Data Analytics & IoT Innovations at Bosch

by Big Data LDN

Dec 17, 2019 / 27m

27m

Start Course
Description

Deutsche Bank is one of the world’s largest financial institutions with operations in 58 countries. It’s a universal bank with a rich heritage and operations across private and commercial banking, corporate and investment banking (CIB), and asset management (DWS). As an early adopter of data science, machine learning, and AI, the group-wide analytics function is trailblazing new ways to drive revenues, lower costs, and reduce risk across all areas of the group. John Allen shares how his team combines commercial offerings from vendors, such as Cloudera and Red Hat, with open source technologies, like Python and Kafka to revolutionize legacy processes and transform the way the bank uses technology to drive innovation. Discover how they have industrialized data science and advanced analytics across the group, embracing both experts and “citizen data scientists,” and helped Deutsche Bank become a leading data technology pioneer.

Table of contents
  1. Data Analytics & IoT Innovations at Bosch

Converting the CDO to a Profit Centre

by Big Data LDN

Dec 17, 2019 / 20m

20m

Start Course
Description

Why can't the CDO be a profit center in their own right? Monetization of data has historically been about using data to improve internal analytics. This is hugely valuable, but it has limited scope for many companies. The next era of growth for CDOs will be the creation of new revenue streams for their organisations. In this session, Gary Goldberg will explore the strategies and changes for you to convert your data function into a profit center.

Table of contents
  1. Converting the CDO to a Profit Centre

Self-service Analytics

This track demonstrates how business users can access and work with corporate data without a background in statistical analysis, business intelligence (BI), or data science. It will also cover how to minimize the risk of decision makers using data the wrong way and which environments prove to be most suitable.

Why Self-service Data Analytics Usually Fails & Ideas for Succeeding

by Big Data LDN

Dec 17, 2019 / 29m

29m

Start Course
Description

Organizations adopt old approaches to analytics; our tools are typically okay, but the way we use them is wrong. Approaches and processes ensure we fail. Takeaways from this session will include what self-service analytics really means and how it should be enabled.

Table of contents
  1. Why Self-service Data Analytics Usually Fails & Ideas for Succeeding

Governed Data Discovery

by Big Data LDN

Dec 17, 2019 / 16m

16m

Start Course
Description

Self-service is a fantastically powerful capability, meaning that everyone can obtain the information they require. Everyone wants faster answers, and sometimes that means digging into the data to work them out. What happens when two departments calculate the same thing slightly differently, or when you want to share only parts of the information to particular teams? Join Matt Pepper's session to find out how MicroStrategy’s Semantic Graph enables Governed Data Discovery at scale.

Table of contents
  1. Governed Data Discovery

Journey to Create a Great Analytic Culture

by Big Data LDN

Dec 17, 2019 / 23m

23m

Start Course
Description

What are the key elements needed to create a great analytic culture? This is a key question that many organizations are currently struggling with as they look to be more analytically driven. Join this session as Shaan Mistry uncovers what it takes to build a great analytics culture. Learn about the challenges you may face and the effect a successful culture of analytics has on your data, people and organisation. Shaan will share some best practices on how to develop a great analytic culture including: data driven transformation, analytic maturity, democratization of technology, and uncovering hidden analytic talent.

Table of contents
  1. Journey to Create a Great Analytic Culture

Something Amazing for Everyone: Embracing Inclusive Design to Deliver Accessible Experiences

by Big Data LDN

Dec 17, 2019 / 24m

24m

Start Course
Description

Krissie Barrick will introduce the Big Hack, Scope’s flagship Digital Influencing Programme which seeks to make the digital world more inclusive. She'll highlight what it’s like to be cut out of the use of tech that has become the foundation of our day-to-day activities, and what can be done to change this. She'll also talk about the business case for inclusive design and where to start if your organization wants to be more inclusive.

Table of contents
  1. Something Amazing for Everyone: Embracing Inclusive Design to Deliver Accessible Experiences

Democratising Data – How We Built a Self-serve Data Platform

by Big Data LDN

Dec 17, 2019 / 27m

27m

Start Course
Description

Auto Trader is the UK's leading digital automotive marketplace. They receive 60 million cross-platform visits each month. Interpreting the vast quantity of data we collect is essential for their success and the success of their customers. Three years ago, Auto Trader started building a new cloud-based data platform. Their mission was to empower the company and their customers to make informed data-driven decisions, by democratizing access to data and promoting a self-serve platform. They wanted to increase their capability for complex analyses and data-science-led data products, while making it easier than ever before for new users to access the data they need. Edward Kent will walk you through the architecture of Auto Trader's multi-cloud data platform and the various tools they are using to fulfill this mission, including AWS S3, Apache Spark, Databricks, Google BigQuery, and Looker.

Table of contents
  1. Democratising Data – How We Built a Self-serve Data Platform

Discover the “Why” You Didn't Know Existed

by Big Data LDN

Dec 17, 2019 / 29m

29m

Start Course
Description

In this session, Becky O'Connor will share the hidden truths about crime using the latest and greatest version of Tableau to explore a publicly available data set. Learn how anyone, regardless of role or technical know-how, can achieve powerful insights using Natural Language. She'll tell her story and help everyone understand the ‘why’ hidden in the data, with Explain Data, a new feature to help people identify relationships in their data, brand new in Tableau in 2019. With Explain Data, you can identify causes and see relationships you didn't know existed, and Becky will show you how.

Table of contents
  1. Discover the “Why” You Didn't Know Existed

Selecting Your Fantasy Premier League Team with Advanced Analytics

by Big Data LDN

Dec 17, 2019 / 24m

24m

Start Course
Description

Learn how to utilize the advanced analytics capabilities in Alteryx to select your top Premier League players for your fantasy team. By connecting to the FPL website via API and a database, Alteryx can prep and blend data together and perform predictive analytics to generate your winning fantasy team. William Davis will also show how you can push this data into visualization tools, such as Tableau.

Table of contents
  1. Selecting Your Fantasy Premier League Team with Advanced Analytics

Decouple Storage from Compute

by Big Data LDN

Dec 17, 2019 / 30m

30m

Start Course
Description

Kaggle’s state of data science and machine learning survey showed in some industries that up to 92% of people say that bad, unavailable, or difficult to access data is one of the top barriers to success in data and analytic projects. This is a problem because without data there is no AI. The volume and types of data that organisations need to store and process is increasing. Large data appliances that run 24/7 are often unsuitable when designing and implementing cost effective data architectures. Fortunately cloud platforms have a number of services that can help us develop and deliver a modern, cost effective and flexible data architecture. This talk will outline and demonstrate a number of services in AWS to achieve this. The talk will start with taking a look at S3 as a storage layer that is decoupled from our compute services. We will look at discovery and classification of data in S3 using Glue and Macie and how we can apply appropriate lifecycle management and security. Moving on to the various types of processing a data project may require, Matt Houghton will look at Lambda and Glue for ETL and Athena and Redshift for query and analysis. We will look at the ready baked machine learning services available that can jump start your AI/ML capabilities. Finally we will look at how we can put data directly into the hands of decision makers using QuickSight and Alexa and deliver a self service BI capability.

Table of contents
  1. Decouple Storage from Compute

Data Skills: Building a Data Team Fit for a Data-driven Enterprise

by Big Data LDN

Dec 17, 2019 / 50m

50m

Start Course
Description

Big Data LDN 2019 | Data Skills: Building a Data Team Fit for a Data-driven Enterprise | Jez Clark

Table of contents
  1. Data Skills: Building a Data Team Fit for a Data-driven Enterprise

Customer Experience

These talks show how insights obtained from big data can power customer and citizen engagement and improve experience and interactions with government and commercial brands.

Consent, Compliance, and the Impact on Customer Experience

by Big Data LDN

Dec 17, 2019 / 26m

26m

Start Course
Description

Customers today have more choice than ever. To stay competitive, businesses need to adopt a customer centric approach. This session explores how businesses can capitalize on providing a great customer experience and the privacy regulations impacting this.

Table of contents
  1. Consent, Compliance, and the Impact on Customer Experience

AI & Communication: Meaningful Data from New Sources

by Big Data LDN

Dec 17, 2019 / 26m

26m

Start Course
Description

In this session, Curtis Peterson will cover how the huge sets of data unearthed from real time communications (think instant messaging, video conferencing, etc.) are finally beginning to yield meaningful analysis with the help of AI. The presentation will outline: why so much data gets trapped in media and how to overcome this, the impact RTC data will have the analytics side of business, and how these technologies could further disrupt communications within the next 5 years.

Table of contents
  1. AI & Communication: Meaningful Data from New Sources

Real-time Personalised Customer Interaction at Scale

by Big Data LDN

Dec 17, 2019 / 27m

27m

Start Course
Description

How do you build a customer interaction platform that is agile enough to respond to constantly changing requirements and still able to perform at scale? This is the challenge the Customer Interaction team set out to solve at Paddy Power Betfair. You will learn how they rebuilt their promotional platform moving from one based on a closed slow relational database to a high-performance agile platform that integrates promotions from 3rd parties. You will see how this transformation has enabled marketing to continuously innovate and apply timely, relevant personalized offers to hundreds of thousands of customers across two brands, even during massive spikes in traffic.

Table of contents
  1. Real-time Personalised Customer Interaction at Scale

Data: The Musical, with LW Theatres

by Big Data LDN

Dec 17, 2019 / 24m

24m

Start Course
Description

It’s the glittering West End. London theatre is in a golden age. What goes on behind the scenes? Pricing, performance schedules, how many tickets released, and to whom. How is data being used to create audiences for the future? It’s quite the production, and one that LW Theatres is well versed in. Tom Wilson, Data Scientist for the LW Theatre Group, will raise the curtain on the following case study topics: accessing customer insights by integrating ticket system data into a purpose-built data warehouse, consolidated legacy data (including info on a decade of ticket sales) into an accessible hub, and how to reduce overhead with marketing automation, building more targeted marketing with a wider array of modeled data segmentation. Tom will share the LW Theatres journey from inception to implementation, along with some interesting plans for the future!

Table of contents
  1. Data: The Musical, with LWTheatres

Self-service and Tableau Community at Lloyds Banking Group

by Big Data LDN

Dec 17, 2019 / 25m

25m

Start Course
Description

Lloyds Banking Group has seen a rapid growth in BI Self-Service and data driven culture through the roll-out of Tableau across its reporting and analytics landscape. A key factor underpinning the team's success has been the thriving analytics and Tableau community they managed to build. This community started in the Analytics Centre of Excellence and has organically grown to reach every department across the group. In this session, Pippa Law and Fred Thomas will give you a flavor of what their BI Self-Service capability looks like now and share the life cycle of their community from the first tentative baby steps to delivering real business value.

Table of contents
  1. Self-service and Tableau Community at Lloyds Banking Group

The Digital Hero’s Journey: Using Big Data to Uncover Business Value and Meaning at Work

by Big Data LDN

Dec 17, 2019 / 22m

22m

Start Course
Description

Big data has big power. It has the power to make CX professionals and their companies heroes or losers. Those that successfully use data to uncover customer experience issues are not only able to provide business value and drive positive change in their organisations, but also find more meaning in their work, report boost in motivation, reduce burnout, and minimize turnover. In this session, Marina Shapira will follow in the footsteps of the digital CX heroes to teach their formula for success and discuss how it can be implemented in your business. Key topics include: How to keep teams motivated in the workplace, the key steps in the digital hero’s journey, and examples of real digital heroes.

Table of contents
  1. The Digital Hero’s Journey: Using Big Data to Uncover Business Value and Meaning at Work

Using Location Intelligence to Place Solar Panels in Rwanda

by Big Data LDN

Dec 17, 2019 / 28m

28m

Start Course
Description

Meshpower, a start-up working in Rwanda, has lots of great data and a sizable location intelligence problem. This session showcases how Meshpower is beginning their journey of using analytics to help communities across Rwanda, and how they are using Alteryx to help solve their location intelligence business problems.

Table of contents
  1. Using Location Intelligence to Place Solar Panels in Rwanda

Embedding Intelligence into the Heart of Customer Operations

by Big Data LDN

Dec 17, 2019 / 25m

25m

Start Course
Description

Big Data LDN 2019 | Embedding Intelligence into the Heart of Customer Operations – Stories from Companies Who Dared to Be Different | John Spooner

Table of contents
  1. Embedding Intelligence into the Heart of Customer Operations

The Art of Customer Conversations

by Big Data LDN

Dec 17, 2019 / 31m

31m

Start Course
Description

What makes a great customer experience and who does it well? What role do data and technology play in transforming the customer experience? How can businesses harness these capabilities to transform the experience for their customers and drive value to the bottom line? In Jo’s session, she will give an overview of the building blocks you will need to create great customer conversations, as well as suggestions on how to get started. She will share lessons learned from her own experience of leading a major transformation experience at British Airways that delivered personalized interactions at scale across the airline’s multiple interactions with customers in multiple channels.

Table of contents
  1. The Art of Customer Conversations

How to Build a Fully Autonomous Card Fraud Detection System

by Big Data LDN

Dec 17, 2019 / 31m

31m

Start Course
Description

In 2016, inspired by the opportunities that AI would open up, Dmitri Lihhatsov started studying this branch of Computer Science and eventually joined Revolut, a global FinTech startup, to fight fraud using the newly acquired knowledge. In just under 1 year, Dmitri built Sherlock, a machine-learning-based fraud detective that continuously monitors the transactions of over 8 million Revolut users and protects them from having their money stolen by fraudsters

Table of contents
  1. How to Build a Fully Autonomous Card Fraud Detection System

At Last! The Real-time Customer Experience

by Big Data LDN

Dec 17, 2019 / 22m

22m

Start Course
Description

Redis enables instant experiences for your applications, combining the advantages of the highest performance, seamless scalability and high availability. Redis is not just the fastest database on the market today but it also includes a comprehensive set of data structures and functions that take Redis Labs capabilities reach far beyond base caching. In this session we will demonstrate how Redis provides a real-time platform for bringing together data streams from multiple channels of your business, transform, consolidate, analyze, and deliver sub millisecond tailored responses to your customers.

Table of contents
  1. At Last! The Real-time Customer Experience

Governance and MDM

Headlines about privacy breaches and GDPR have brought corporate responsibility for data into sharp focus, threatening severe consequences for failure. Data quality and security issues are undermining the gains promised by the data revolution. These sessions provide answers and advice from a wide range of experts and highlights both the pitfalls to avoid and the barriers to clear to ensure success.

Data Privacy Mythbusting

by Big Data LDN

Dec 17, 2019 / 24m

24m

Start Course
Description

Is customer trust dead? Trūata’s Chief Data Scientist, Dr. Maurice Coyle looks at this question and explores some of the myths around the use of personal data and consumer privacy. This session will debunk some of the most common data privacy myths as well as sharing valuable insights into the effective use of privacy-enhanced analytics for data-driven organizations.

Table of contents
  1. Data Privacy Mythbusting

Demystifying Data – What They Don’t Tell You at Data School

by Big Data LDN

Dec 17, 2019 / 23m

23m

Start Course
Description

Join this session to learn: Why data management is the ‘best technology’ available to you, how a systems based approach can help you think differently about your data issues, how identifying the ‘job to be done’ can help you start writing a data strategy, the top 4 things your data strategy should have, and how to take your data strategy from ideation to implementation.

Table of contents
  1. Demystifying Data – What They Don’t Tell You at Data School

Optimizing Your Data Value Chain with Agile Data Management

by Big Data LDN

Dec 17, 2019 / 20m

20m

Start Course
Description

Data is the fuel of digital business and transformation, but access to unified data that is governed, secure, and trusted is one of the toughest barriers to overcome. In this session, Ioana Stama will show how you can make data truly pervasive throughout your organisation and make it insightful and action-oriented, so that you can benefit from a 360-degree view of everything. Specifically, you will learn how to: optimize your data value chain and easily access, govern, and share all data with greater consistency and control, deliver consistent, IT-curated data that conforms to your enterprise data model and standards, and reduce the time your business users spend searching for and preparing data, so they can spend more time analyzing it..

Table of contents
  1. Optimizing Your Data Value Chain with Agile Data Management

Data at SEGA Europe

by Big Data LDN

Dec 17, 2019 / 26m

26m

Start Course
Description

SEGA is one of the leading interactive entertainment companies in the world. Their studios include Sports Interactive, Amplitude, The Creative Assembly, Hardlight ,and Relic Entertainment. SEGA is responsible for games such as Football Manager and the Total War series. This talk covers the types of data that are collected at SEGA, how the data is processed including utilizing the cloud for Big Data, and how this data is made accessible to end users throughout the business and beyond.

Table of contents
  1. Data at SEGA Europe

Keep Your Data Lake from Getting Hadooped

by Big Data LDN

Dec 17, 2019 / 27m

27m

Start Course
Description

With a valuable commodity such as what is now presented in the form of data, there needs to be a concerted effort to ensure the safety and security of this information. Various security controls that were once seen as sufficient in the past need to now be supplanted in favor of better controls such as multi-factor authentication, biometrics, and WebAuthn. These controls help to address users from the perspective of fine grained access control, data access and audit. Data security risks are higher now than they have ever been before and it is incumbent upon stewards of data to ensure that there is a zero trust approach to avoid the pitfalls of an error, manipulation of breach.

Table of contents
  1. Keep Your Data Lake from Getting Hadooped

Top 10 Privacy Tips & Tricks in Big Data

by Big Data LDN

Dec 17, 2019 / 30m

30m

Start Course
Description

In this presentation, Tudor Galos, Privacy Consultant and founder of Tudor Galos Consulting, will talk about top 10 privacy tips & tricks in Big Data scenarios that can be implemented by any B2B and B2C company. Topics include: how to write effective privacy notices and policies to explain your data subjects what you do with their data, how to map your internal big data flows, what the mandatory Register of Processing Activities should contain, how to demonstrate compliance with GDPR and ePrivacy, how to monitor privacy compliance, and balancing legitimate interests vs. data subject rights. There will be case studies and best practices from over 50 customers at Tudor Galos Consulting.

Table of contents
  1. Top 10 Privacy Tips & Tricks in Big Data

Data Governance as a Customer Service

by Big Data LDN

Dec 17, 2019 / 26m

26m

Start Course
Description

The skills you need to get a data governance program up and running, retain its momentum, and see it through are the same skills needed for service excellence. Data governance is about serving up the best possible data to your organisation, providing the data that’s needed when it’s needed safely and conveniently. If you offer data governance as a service and you embed that ethos into your business community, as with any good service provider, you’ll have customers queuing up for it.

Table of contents
  1. Data Governance as a Customer Service

7 AI Quick Win Projects

by Big Data LDN

Dec 17, 2019 / 31m

31m

Start Course
Description

Starting to do AI in your business can be risky. You might have a skills gap, insufficient data, or problems putting things into practice. Step over the risk with one of these quick-win projects. Each project includes simple selection criteria, ways to identify the ROI, and a project checklist. Pick the perfect one for you today.

Table of contents
  1. 7 AI Quick Win Projects

Delivering Value with Intelligent Data Governance

by Big Data LDN

Dec 17, 2019 / 17m

17m

Start Course
Description

In a time where governing data is becoming more complex and the need for good data is increasing, organisations are rapidly realizing that the capabilities of the past won't scale for future needs. The realization that data governance without implementation is just documentation, and that documentation is instantly obsolete, is hitting home with many. In this session, Stephen Holyer will explore how to scale data governance to improve quality, access, and compliant use of data to drive business value.

Table of contents
  1. Delivering Value with Intelligent Data Governance

The Culture Competition – Personalisation vs. Privacy

by Big Data LDN

Dec 17, 2019 / 20m

20m

Start Course
Description

In the challenge to provide better services, companies are increasingly turning to greater personalization. In many cases, personalization is in competition with regulatory initiatives focused on personal information. This can be further impacted by the expectations of different age groups in how interaction between company and consumer will take place. These same generational expectations affect company culture and governance regarding how data is used, managed, and valued internally as well as externally.

Table of contents
  1. The Culture Competition – Personalisation vs. Privacy

DataOps for AI and Digital Transformation

by Big Data LDN

Dec 17, 2019 / 27m

27m

Start Course
Description

Organizations are under competitive, disruptive, and regulatory pressures. Leveraging data and AI at the speed of business is the biggest differentiator. However, 81% of organizations don’t understand their data provides little to no value. For those aiming to succeed in digital transformation and AI, DataOps is essential to get to business-ready data providing automated, curated, and trusted data pipeline between data providers and data consumers. That means a scalable, agile, and faster path to achieving business objectives. In this session, IBM presents DataOps methodology with demonstrations to help you maximize your people, process and technology to accelerate journey to AI and digital transformation.

Table of contents
  1. DataOps for AI and Digital Transformation

Big Data LDN: A GDPR Retrospective

by Big Data LDN

Dec 17, 2019 / 26m

26m

Start Course
Description

The date May 25, 2018 was a fateful day for many companies that process and store client data, particularly across the EU. On this day, GDPR went into effect and no one really knew quite what its effects would be. This talk will take you through our company’s journey to compliance - the indexers we used to append & delete client data, and a retrospective of how this affected our data processing operations. This will walk you through the design through implementation, as well as expectation vs. real demand. Eventually, what we imagined would be requested by hundreds of clients at best ended up being requested by tens of thousands and growing. Learning how to manage this new compliance demand alongside our day to day data engineering tasks and processes was no easy feat.

Table of contents
  1. A GDPR Retrospective

GDPR: A Sword Not a Shield

by Big Data LDN

Dec 17, 2019 / 29m

29m

Start Course
Description

Most businesses regard GDPR as a pure drain on costs with no return. However, there are ways that you can use GDPR to enhance your business, in particular by finding out more about your competitors' businesses. Dai Davis, a Solicitor, Chartered Engineer, and an experienced GDPR practitioner, discusses these tactics, which are much more important than the actions taken or likely to be taken by the Information Commissioner. In addition, Dai will discuss how to protect your own business against these tactics.

Table of contents
  1. GDPR: A Sword Not a Shield

Drive Business Growth While Satisfying GDPR and CCPA

by Big Data LDN

Dec 17, 2019 / 18m

18m

Start Course
Description

Data driven organisations today are extensively leveraging customer data in data science and analytics environments for secondary purpose processing often falling under more complex privacy controls. This presentation will discuss how automation and risk of re-identification integrated with new privacy-preserving approaches can address privacy compliance while still preserving the analytical value of the data. This leads enterprises to a new era of leveraging automation and state of the art techniques to address privacy compliance.

Table of contents
  1. Drive Business Growth While Satisfying GDPR and CCPA