Training for Business Users
Another important requirement is training and knowledge bases for users. In almost all cases, the business users will have varying backgrounds and skillsets, and not everyone of them will be ready to start performing analysis on their own. Making trainings and knowledge bases easily available to users will help bridge this gap.
Part of the training will likely be technical training for how to use the tool (bring in data, create visuals, apply filters, etc.). The other part will be functional training, so users can understand where the data is coming from, how it’s formatted, and how it should be used. A lot of this functional information can be managed through data dictionaries/catalogs as well as documentation for users to review when the data owners aren’t available to provide their own explanation.
One final requirement I want to call out is the need for data governance. For self-service business intelligence and analytics to work well, the data sources need to be accurate. This sounds obvious, but to successfully implement this, there needs to be organizational alignment on what the source of “truth” should be for the various systems.
Processes will need to be put in place to ensure data accuracy, as well as settings enabled on your data access layer to guarantee that data curators can properly manage user access privileges to the data. Working with the business to clearly define what a certified data set means and what factors each certified data source must have is an important step to achieving data accuracy and self-service analytics.