Webcast : ER/Studio Enterprise Team Edition

Geek Sync | The 4Cs of Effective Data Cataloging and Business Glossaries

Presenter: Scott Taylor and Steve Hoberman

It is important to create effective data catalogs and business glossaries that help users better understand and use the data assets of your organization. That involves organizing and documenting your data assets and their definitions in a way that is accessible and understandable to both technical and non-technical users:

  • Identify data assets: Start by identifying the data assets within your organization, including databases, data warehouses, data lakes, and other data repositories.
  • Gather metadata: Collect metadata about your data assets, such as table names, column names, data types, descriptions, and relationships between tables. This information will help users understand the structure and purpose of the data.
  • Define business terms: Create a list of common business terms and their definitions that are used within your organization. These terms should be clear, concise, and consistent across the organization.
  • Map data assets to business terms: Link the data assets to the relevant business terms, so users can understand the relationship between the data and the business concepts.
  • Establish a data catalog: Organize the data assets and their metadata in a centralized and searchable data catalog. This can be a simple spreadsheet, a dedicated software tool, or a custom-built solution.
  • Create a business glossary: Compile the business terms and their definitions in a centralized and searchable business glossary. This can be a document, a wiki, or a dedicated software tool.
  • Ensure accessibility: Make both the data catalog and business glossary accessible to all relevant stakeholders, including data analysts, data scientists, and business users.
  • Maintain and update: Update the data catalog and business glossary to reflect any changes in the data assets or business terms. Establish a process for reviewing and approving updates to ensure accuracy and consistency.
  • Promote data catalog and business glossary usage: Encourage the use of the data catalog and business glossary within your organization by providing training, documentation, and support.
  • Monitor and measure: Track the usage of the data catalog and business glossary, and gather feedback from users to identify areas for improvement.

To find the value data has to offer, it must be structured. A simple way to describe the basic structure needed for your relationship and brand data are the 4Cs: Code, Company, Category, and Country.

  • A CODE tells something is unique: IDENTIFIERS
  • A COMPANY tells who owns it: HIERARCHIES
  • A CATEGORY tells what kind of relationship it is: TAXONOMIES
  • A COUNTRY lets you know where it is: GEOGRAPHIES

About the presenters:

Scott Taylor, The Data Whisperer, has helped countless companies by enlightening business executives to the strategic value of proper data management. He focuses on business alignment and the “strategic WHY” rather than system implementation and the “technical HOW.” As Principal Consultant for MetaMeta Consulting he helps Enterprises and Tech Brands tell their data story. His new book – TELLING YOUR DATA STORY: Data Storytelling for Data Management is available now. He lives in Bridgeport, CT where he often kayaks in Black Rock Harbor. He can also juggle pins and blow a square bubble.

Steve Hoberman has been a data modeler for over 30 years, and thousands of business and data professionals have completed his Data Modeling Master Class. Steve is the author of nine books on data modeling, including The Rosedata Stone and Data Modeling Made Simple. Steve is also the author of Blockchainopoly. One of Steve’s frequent data modeling consulting assignments is to review data models using his Data Model Scorecard® technique. He is the founder of the Design Challenges group, creator of the Data Modeling Institute’s Data Modeling Certification exam, Conference Chair of the Data Modeling Zone conferences, director of Technics Publications, lecturer at Columbia University, and recipient of the Data Administration Management Association (DAMA) International Professional Achievement Award.

Topics : Data Modeling,Enterprise Architecture,

Products : ER/Studio Data Architect,ER/Studio Enterprise Team Edition,

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