Enterprise Data Management

This course is a part of Information Systems, a 3-course MicroMasters series from edX.

High-quality information is the key to successful management of businesses. Despite the large quantity of data that is collected by organizations, managers struggle to obtain information that helps them make decisions. While operational processing systems help capture, store, and manipulate data to support day-to-day operations of organizations, reconciled systems -- sometimes referred to as data warehouses or business intelligence (BI) systems -- support the analysis of data, thus, enabling decision making.

With the advent of big data systems, organizations have turned to enterprise data management frameworks to manage and gain insights from the vast amount of data collected. While storage costs themselves are relatively affordable, the bigger challenge has been finding an appropriate mechanism to manage the data as many technologies (e.g., relational databases, data warehouses) have limitations on the amount of data that can be stored.

This course focuses on realizing the business advantage and business potential of operational, reconciled, and big data systems as well as data assets in supporting enterprise data management strategies and enterprise data analytics.

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What you'll learn

• Design relational databases that are used to manage operational systems.
• Query relational databases using Structured Query Language (SQL).
• Understand issues relating to data quality, describe the principles of data profiling, and master data management.
• Understand the need, definition, and types of data integration.
• Understand the meaning and architecture of data warehouse.
• Understand how to visualize data using graphical marks.
• Learn the physical and cognitive roots of vision.
• Learn to build more complicated visualizations and utilize data stories to deliver deeper, wider, and richer information.
• Understand the important questions that data governance seeks to address.