One of the most frequently asked questions when starting a Data Warehousing initiative is: “What best practices should I be following?”
In this series of posts, we will outline our recommendations to follow when building a data warehouse – starting with data warehousing documentation.
Data Warehousing Best Practice: Documentation
A successful data warehouse implementation boils down to the documentation, design, and the performance of the solution. If you can accurately capture business requirements, you should be able to develop a successful solution that will meet the needs of the enterprise.
Create documentation standards.
Begin by creating standards for your documentation, data structure names, and ETL processes which will be the foundation upon which your deliverables will be produced. An excellent data warehousing project has robust and easy-to-understand documentation.
What documentation should I have?
Here are some of the major pieces of documentation all data warehousing projects should have:
- Business Requirements Document defines the project scope and high-level objectives from the perspective of the executive management team and the project sponsor.
- Functional / Informational Requirements Document outlines the functions which users must be able to complete at the end of the project. This documentation will include use cases and focus on what information the users need from the warehouse.
- Fact/Qualifier Matrix is a powerful tool that will help the team associate the metrics and dimension attributes to the metrics defined in the Business Requirements Document.
- Data Model is a visual representation of the data structures of the data warehouse. Data models are visual aids used to ensure the data and reporting needs of the business are captured. Data models are also utilized by the DBAs to create the data structures which will hold the data.
- Data Dictionary is a comprehensive list of data elements found in the dimensional model, their business definition and the source database name, table name and field name from which the data element was created.
- Source to Target ETL Mapping Document is a list focusing on the target data structure and defining the source of the data (database name, table name and column name) and any transformation which the source element goes through before landing in the target table.
- Data Model Best Practices for Data Warehousing
- What Are Data Warehouses?
- Top 3 Requirements for Creating a Data Warehouse Solution
- Measuring Data Warehouse Performance
- MiCORE’s Passion for Data