Bringing Data Science into the Business

Paths

Bringing Data Science into the Business

Authors: Paul Foran, Benjamin Culbertson, Emilio Melo

Before a business can benefit from data science, it must be ready for it. This skill addresses how data science fits into a business, and how it is used to quantify and solve... Read more

What you will learn:

  • Determine if data science is an appropriate fit for a project
  • Quantify a business problem
  • Communicate constraints and outcomes of a data science project proposal

Pre-requisites

Learners are expected to have cursory knowledge of data science applications and techniques.

Beginner

Courses in this level of the path address how to determine if data science is an appropriate solution for a given problem.

Analyzing Business Requirements for Data Science

by Paul Foran

Nov 13, 2019 / 51m

51m

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Description

Data Science has certainly become a ‘hot topic’ for all businesses. Investing in Data Science activities for your business can certainly yield some hidden gems in your data sets and lead to valuable IP or improvements in operational efficiencies for your organization! In this course, Analyzing Business Requirements for Data Science, you will learn the strategic, practical and technical skills to discover if data science can indeed benefit your organization. First, you will see how to gather and manage the right stakeholders with a view to providing a solid Data Science story to your company that adds REAL business value. Next, you will discover how to determine and risk assess your data science business and technical requirements. Finally, you will explore how to quantify the business problems and learn what to do when mitigating the risk of a project not yielding business value. When you're finished with this course, you will have the skills and knowledge of Analyzing business requirements for data science needed to guide you through the process of managing and delivering a data science project to your organization

Table of contents
  1. Course Overview
  2. Determining if Data Science Is an Appropriate Fit for the Organization
  3. Quantifying the Business Problem

Intermediate

This level of the skill addresses communication of expectations and constraints to the business stakeholders.

Communicating Expectations to the Business

by Benjamin Culbertson

Sep 20, 2019 / 44m

44m

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Description

Discover critical skills in communicating barriers and solutions to data acquisition for model training. In this course, Communicating Expectations to the Business, you will learn foundational knowledge that will aid you in managing stakeholders' expectations of data science, machine learning, and augmented intelligence solutions. First, you will learn what is needed for a data science solution. Next, you will discover the four main sources of historical data that can be used to train models for a solution that will generate insights that will be used by a team, and what barriers you may encounter in acquiring that data. Then, you will examine an innovative solution, synthetic data generation, that will aid in transforming existing data while maintaining the data's character, personality, and richness. Finally, you will explore how to communicate solutions and expectations to stakeholders on data availability and formatting, and ask for a go/no-go decision. When you're finished with this course, you will have the skills and knowledge of communicating challenges around availability of data, and strategies needed to overcome barriers to bring needed historical data to your data science and machine learning solution.

Table of contents
  1. Course Overview
  2. Reviewing Available Data with Stakeholders
  3. Communicating Barriers to Data Access to Stakeholders
  4. Recommending Next Steps Based on Available Data

Advanced

The final level of the skill discusses ethical and legal issues that apply to data science projects.

Understanding Ethical, Legal, and Security Issues in Data Science

by Emilio Melo

Dec 13, 2019 / 1h 1m

1h 1m

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Description

With all the scandals hitting the news related to privacy, security breaches and bias issues, understanding how to properly manage data has become an increasingly demanded skill on the business world. In this course, Understanding Ethical, Legal, and Security Issues in Data Science, you will gain the ability to handle Azure-hosted data in a secure, highly available and compliant way. First, you will learn about the Shared Responsibility Model in the cloud, and your duties on this model. Next, you will discover authentication and authorization options in Azure, as well as how to maintain the data highly available. Finally, you will explore how to handle legal, compliance and ethical aspects in Azure. When you’re finished with this course, you will have the skills and knowledge of Data Management needed to host your workloads in the Microsoft cloud.

Table of contents
  1. Course Overview
  2. Authentication and Authorization Methods
  3. Determining Data Availability
  4. Assessing Ethical and Legal Data Compliance