Data has become ‘the’ corporate asset of the twenty-first century. In this course, you will learn how organizations manage data through the many disciplines of enterprise data management, such as governance, modeling, engineering, and analytics.
Over the last decade, technology has given us the ability to generate, obtain, and analyze data in more ways than ever before. It has become essential for you to develop the understanding of managing data on an enterprise level.
In this course, Big Picture: Enterprise Data Management, you will learn about the various disciplines of data management. First, you will discover what data governance is and how you might want to implement a governance program for your organization. Next, you will cover data modeling and data architecture, including the topics of MDM and Blockchain technology. Then, you will explore the disciplines of database administration and data development. Finally, you will learn about business intelligence and reporting, big data and data engineering, and data science, including data analytics, machine learning, and data visualization.
By the end of the course, you will have a firm understanding of enterprise data management and why you need an enterprise data strategy, what the various disciplines do, and how to build a data-driven culture in your organization.
Joe is a senior data engineer and has worked as a data management professional in various capacities and titles for the last nineteen years. In his current role, Joe is working to build a competency around big data, predictive analytics, and BI development.
Course Overview Hi everyone. My name is Joe Cline, and welcome to my course, Big Picture: Enterprise Data Management. Have you ever the phrase knowledge is power? Well you can't have knowledge without information nor get information without data. Over the last decade, technology has given us the ability to generate, obtain, and learn from data in more ways than ever before. So I ask you this. Are you ready to take a high-level survey of this exciting, but often misunderstood field? That's great because some of the major topics we will cover in this course will include the various disciplines within enterprise data management, the roles, responsibilities, methodologies, and technologies for each of these disciplines, and talk about some of the hot technologies and topics, such as master data management, big data, and blockchain in the enterprise. This is an introductory course, so no experience is necessary. But after completing this course, you should feel comfortable diving deeper into the pool of enterprise data management with courses on Enterprise Data Governance, Enterprise Data Architecture and Master Data Management, Data Modeling, and others. I hope you'll join me on this journey to learn about managing data with the Big Picture: Enterprise Data Management course only at Pluralsight.
Course Introduction Hello and welcome to my course, Big Picture: Enterprise Data management. This is an introductory course to managing data on an enterprise scale. Since this is an intro course, no experience is assumed. My name is Joe Cline, and so you'll have some confidence in the quality of information you'll get from this course, check out my LinkedIn page. Or better yet, send me an invite to connect. Any time you have a question about the course or data management in general, shoot me a tweet @mrjoedata. You might be thinking, hey Joe so what am I going to get out of this course? Well like I said, this is an introduction course to data management on an enterprise scale. What do I mean by enterprise? Well, enterprise is the term often used to refer to the entirety of an organization or the organization's technical infrastructure. And because this is an introduction course, we'll be looking at the data management aspect of the enterprise from a 50, 000 foot view. Because each organization is unique, I can't give you one solution to implement in any one of the areas we'll learn about, but this course is the beginning to understanding the roles, disciplines, methodologies, and technologies common in a data-driven organization. Let's go onto the next video where I'll introduce you to the concept of the data lifecycle.
Preparing an Enterprise Data Strategy Hi, and welcome back to Big Picture: Enterprise Data Management. I'm Joe Cline. In the course introduction, we briefly talked about the DAMA wheel and the steps of the data lifecycle. We also talked about how the data lifecycle is cyclical and can be a little complicated for an introductory course, so I broke the steps out into three different parts. In this module, we'll discuss the first part: preparing an enterprise data strategy, focusing on the disciplines around governance, architecture, and modeling. Let's get started.
Managing and Working with Data Hello and welcome back to Big Picture: Enterprise Data Management. I'm Joe Cline. In this module, Managing and Working with Data, we'll get into the administration and engineering aspects of data management. By the end of this module, you'll have learned what database administration is, the DBA and what they do, enforcing data quality through data governance policies, compliance auditing, database development and developing DAOs for the application, and data integration and the development of ETL.
Getting Value from Data Welcome back to Big Picture: Enterprise Data Management. I'm Joe Cline. In this module, we'll explore the data management disciplines for getting value from your data. We'll start with data engineering, sometimes called big data engineering, and discuss how it's more than ETL development and why what data engineers do is sometimes referred to as data munging or data wrangling. Next, we'll look at business intelligence, or simply BI, what the BI developer's responsibilities are, and some of the tools they use. We'll then get into the disciplines that have come to be associated with the term data science, EDA or exploratory data analytics, statistical data analytics, the core of data science, predictive modeling with machine learning algorithms, and data visualization. But before we get into data engineering, let's talk a little bit about big data and what that means. I'll see you in the next clip.
Course Summary Well this is it, the end of the course. Now if you made it this far, you should congratulate yourself as we've covered a lot of information within the data management space in a very short period of time. Let's take a look at how far we've come. Even though we've covered a lot, we've done it at a very high level, but we talked about the data lifecycle and DAMA, big data and Hadoop, blockchain technology and how that might fit into the greater enterprise architecture, the various roles throughout the data management space, some methods, as well as the many technologies used by data management professionals, and the various disciplines they specialize in, like data governance, data architecture, data modeling, database and data warehouse administration, data development, data integration, data engineering, business intelligence, exploratory data analysis, statistical data analysis, predictive modeling and machine languages, and finally data visualization. I want to say thank you for taking Big Picture: Enterprise Data Management. I hope you found it as fun as I did putting it together. But more importantly, I hope you found some value in it. So where do we go from here? Well, if you found any of the particular disciplines or topics discussed in this course interesting and want to learn more about them, stay tuned for more courses here on Pluralsight where I plan to get into a deep dive for each one. And if you have any suggestions on a course topic or have a question or comment about a course, shoot be a tweet @mrjoedata. I'd love to hear from you. You can also see what I'm up to on my blog, datanomicon. blog. That's. b-l-o-g. I'm Joe Cline, and until next time, go model something awesome.