Overview of Self-service BI

There were considerable limitations in the traditional Business Intelligence approach. Especially in reporting and dashboard creation in the presentation layer. Typical BI projects were following the process, gathering the BI requirement, and implementing the data warehouses or data marts. Then the presentation layer, as covered in the previous section. However, when the new dashboard requirement comes, the developer has to work on that and it takes time to deliver the new requirements. Until they deliver the new dashboards, the business user has to wait for days, even months. Predominantly because of this reason, the BI end-user is always limited with analytical capacity.

They are unable to throw ad-hoc queries for their new analysis. Further, because of this reason, most BI projects end up unsatisfactory or failures. Because of these limitations, it was clearly identified the requirement for a new methodology for doing BI. Then self-service BI originated.

With the arrival of self-service BI, preceding limitations disappeared. Without going through the entire cycle of BI and always demanding the help of the IT team, business users are able to connect to data and start their own analysis as desired. With that, not only tech-savvy people but non-technical users were also able to do their own analysis using self-service BI tools. Simply, they serve on their own using these kinds of BI tools. The below image explains the self-service BI approach:

During the self-service BI process, only one actor plays each role which is a Business Intelligence user. The BI user can be a Data Analyst, Data Engineer, computer programmer, Business Analyst, Manager, company CEO, or any user who works with data. As you read this book, you will fall into one of those categories. As a BI user, after you install the self-service BI tool, and then you connect to the sources on your own and extract data. Then, you can perform the data shaping tasks, or else what we called cleansing and blending data. After the do the transformation, you can connect multiple tables(queries) and build models. Finally, in this process flow, you can visualize the data and generate actionable insights. In order to make this happen, the self-service BI tools have a built-in simplified manner so anyone can understand how to use them even if they are not a tech-savvy person. Because the entire process flow is performed by the BI user, it means the user serves him/herself the BI. That is why we called it a self-service BI.

We can consider Excel as the first self-service BI tool offered by Microsoft. We can call it a self-service BI tool because it has characteristics of a self-service BI tool. However, due to the limitations that you cannot store more than 1 million rows in excel, which led to the need for a separate self-service BI tool with robust and rich characteristics such as ETL, cleanse data, modeling, and allow analytic capabilities with unlimited data volume. Then, Microsoft Power BI came into the market. Today, Microsoft Power BI is one of the popular self-service BI tool filled with rich, stable, powerful capabilities to serve self-service BI requirements.

Hope this was helpful.