LII:Enterprise Data Management

Title: Enterprise Data Management

Author for citation: Ramesh Venkataraman, Jingjing Zhang, Vijay Khatri

License for content: Unknown

Publication date: 2023

This is an Indiana University course that is released on the edX platform. The 12-week course gives students an opportunity towards "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." The course is free to take, with a Verified Certificate of completion available for $499. (Note that the free Audit track expires November 7, 2023.) The course requires on average eight to 10 hours a week of effort.

The edX course description:

"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 ...

Verified Learners will need to purchase a textbook in order to successfully complete the course. See the FAQ for details.

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."

About the authors

The instructors for this course are Aaron Perry and Jie Li. See each professor's profile for full details.

General layout and contents of the course

No syllabus is publicly provided. The EdX page notes that one of either of this books is required for Verified Learners:

• Print: Hoffer, Jeffrey A.; Ramesh, V.; Topi, Heikki (2019). Modern database management (Thirteenth edition ed.). Boston: Pearson Education. ISBN 978-0-13-477365-0. 

• eText: Hoffer, Jeffrey A.; Ramesh, V.; Topi, Heikki (2019). Modern database management (Thirteenth edition ed.). Boston: Pearson Education. ISBN 978-0-13-479229-3. 

The course

: The course can be found on the edX site, under the Business and Management category. Access to the class starts August 15, 2023. Note the free audit track closes November 7.