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What is a Data Dictionary?


A Data Dictionary is a central repository of metadata (data about data). This typically consists of metadata elements such as data object names and definitions, database schema, column or row names, data types, lineage details, and more. The purpose of a data dictionary is to standardize technical terminology to be used by technical people and business people alike.

Data needs across campus are soaring, yet uncollected, inconsistent, and impossible to aggregate. Data silos are impairing decision-making and ultimately preventing institutions from progressing toward their strategic goals.

EAB Study

June 7, 2017

Why is a Data Dictionary important?

Maintaining a Data Dictionary guards against information inaccuracy by:

  • Establishing a process for sustainable data quality
  • Offering an online central repository of data definitions and reporting specifications
  • Fostering a culture of transparency and cross-functional collaboration
  • Clarifying and refining business processes
  • Improving data validity and reliability
  • Providing an impetus to continue dynamic, not static, discussions
  • Facilitating the process to attain one data "language."
  • Encouraging users to be the authority on data from their functional areas

Data Cookbook: Where the Magic Happens

Data Cookbook is Pepperdine's official Data Dictionary. A collaborative online data dictionary and data management solution, Data Cookbook is an established, well-supported tool for data governance that helps facilitate community knowledge and information sharing at Pepperdine.

The Data Cookbook sources the searchable dictionary on this website. It offers the curious a deeper dive into data, reporting, and technical definitions, providing history, versioning, and the ability to offer feedback. Additionally, it includes a Community workspace where Pepperdine and other higher ed institutions can share their definitions.

Stakeholders can click the logo below and sign in with their WaveNet credentials to access the full Data Cookbook.


Data Cookbook

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