111 Approach - On Premises Enterprise BI Architecture & Design from a bird's-eye view.

111 Approach (One, One, One, Approach)

How fast can the data be provided and with what level of accuracy? What's the best approach?

The best approach is referred to as the 111 Approach. This approach accomplishes the following:

• Minimum BI interference/dependency to get the ball rolling
• Agile approach, a standard software engineering approach
• Self-serve BI by the business, an accuracy in providing the requirement before going to the IT department/Designers.
• Understanding the data in advance and getting feedback before design and production
• Providing relational information within the requirement

See the overall objective and complete agenda here: Overall Objective and Agenda

1 Day

Assuming you have a BI environment up and running, your data scientist is dealing with all the corporate data and suddenly he comes up with an idea. He imports some external data into any tool that he is comfortable with (in this case, I picked Power BI) and studies the data.

Finally, a new self-service report is created that is handed over to the analyst/business team for feedback.

1 Week

The data scientist asks the IT department to find an environment for the external data so that it can be shared within the team. The IT department copies the external data to an environment so that it can be accessed, but the IT department will not support this new entity, this is a one day job for the IT department.

Now the analyst/business team studies the data and provides feedback, documentation and most important part in the requirement for the IT department/designers.

At this point we have enough information/requirements to confirm the design.

1 Month (1 Sprint)

The IT department/designers now have the requirements and can start adding the new external data into the current corporate BI environment so that it follows all the BI standards. For example, the external data will be incrementally loaded, it will follow in the auditing process, data cleansing, framework reports, etc.