How can you ensure data warehouse usability for end users?

One of the key requirements to get from the users is the relationship between the individual data entities: one-to-one, one-to-many, many-to-many. For example one customer can have many invoices. This information is key to the design of the data warehouse. By getting this correct the data warehouse will provide accurate information, the flexibility to be used for new requirements and have a structure that new data entities can easily be added to.

But also remember this will never be set in stone. User needs always change. Make sure your DW can change and be altered as needed when things change.

To ensure data warehouse usability for end users, focus on creating a user-friendly interface with easy navigation and efficient data retrieval. Incorporate advanced search features and customizable dashboards for better data visualization and access. Continuously collect user feedback to understand and address their needs, making necessary adjustments for improvement. Offer thorough training and support, helping users to maximize the data warehouse's capabilities. Emphasize maintaining high-quality and consistent data, as this builds user trust and reliability in the system. By concentrating on these key areas, you can significantly enhance the usability and effectiveness of the data warehouse for its users.

Also try not to bring in useless data. It will slowly make your ETL larger and larger and slower and slower. I have had to completely rebuild an existing ETL process due to the daily processing taking over 24 hours.

Careful consideration must be given when extracting data about the same entities, for example customers, from different systems. During the transform process the data from the different sources must be precisely matched and assigned a unique key. Manual intervention, or AI, may be needed where there is no data that can provide an automated, accurate match.

Reports and graphs are key. Without them you are just storing data. Make sure they are giving the needed information and make sure those that are using them feel comfortable with them and you.

Once the DW is in a good place and has gone through testing with end users building error and data checking is very important. Waiting until someone brings up issues makes the users not trust the data and it’s hard to regain that trust.

A data warehouse becomes more usable when it is accessible and well catalogued , if a search about data lands in your catalogue and if catalogue provides precise information , people tend to trust the data , once they trust the data they question it , once it is easily questionable , they come back to it again , if any one link gets missed in the journey of an user , you miss the user.