Metadata Models 🏷️📓

A Data Warehouse without Metadata is like a library with 1 million books but no catalog and no labels on the shelves. You have the data, but you don't know what it means or where it came from.

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1. What is Metadata?

Metadata is data that describes other data. It provides the "Who, What, When, Where, and Why" of the information stored in the warehouse.

2. Types of Metadata

1. Technical Metadata: Information primarily used by IT staff and DBAs to manage the system.

   • Schema Details: Names of tables, columns, and their data types (e.g., Sales_Amount is a Decimal).
   • Source Mapping: Documentation of which column in the Source DB (like MySQL) maps to which column in the DW.
   • Data Lineage: A history of where the data came from and what "Transformation Rules" (like currency conversion) were applied to it.
   • Indexing Info: Details about how the tables are sorted and indexed for speed.

2. Business Metadata: Information used by managers and analysts to understand the business meaning of reports.

   • Data Dictionary: Clear definitions for every term (e.g., "'Profit' = 'Revenue' minus 'Total Expenses'").
   • Ownership & Contact: Who is responsible for this data? (e.g., "The Marketing VP is the owner of lead generation data").
   • Security & Privacy Labels: Identifying which columns are "Private" (like Customer Names) and who has permission to see them.
   • Reporting Logic: Explanations of how "Calculated Metrics" are created (e.g., "Customer Health Score is based on 5 different factors").

3. Operational Metadata: Information about the "Health" and "History" of the warehouse operations.

   • Job Run History: Records of when the ETL process started, when it ended, and if it succeeded or failed.
   • Data Freshness: A timestamp showing exactly when the data was last "Refreshed" from the source.
   • Error Logs: Details about any "Dirty Data" that was rejected during the loading process (and why).
   • Usage Stats: Monitoring which reports are used most often and which users are accessing the system.
   • Audit Trails: Records of who changed what metadata and when, ensuring the system remains trustworthy.

3. Importance of Metadata

• Mapping: It tracks how data moves from a transactional DB to the warehouse.
• Searchability: It allows users to find the correct data for their reports.
• Quality Control: It records which parts of the data were cleaned and how.
• Lineage: If a report shows a wrong number, metadata helps you trace the error back to the original source.

Summary

• Metadata is "data about data."
• Technical metadata manages the warehouse operations.
• Business metadata helps managers understand the meaning of reports.
• Without metadata, a warehouse becomes a "Data Swamp" where nothing can be found.

Quiz Time! 🎯

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