Professional Course

Enterprise Data Management

edX, Online
Length
12 weeks
Length
12 weeks
Visit this course's homepage on the provider's site to learn more or book!

Course description

Enterprise Data Management

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.

Who should attend?

Prerequisites

None

Course delivery details

This course is offered through Indiana University, a partner institute of EdX.

8-10 hours per week

Costs

  • Verified Track -$499
  • Audit Track - Free

Certification / Credits

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.

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