How to Reduce the Load on Data Team

As businesses become more data-driven the demand for the data teams has increased as well. Data-driven decision making means that business user will be interacting with the data teams more often due to the technical know-how required to use business intelligence or any other related tools.

Traditional BI tools require its users to have a technical background to use it. This means more workload for the data teams because the non-technical people mostly use BI tools. This situation intensifies more in a business that is data-driven and operating in a very competitive environment.

If you are operating in a fiercely competitive industry, then you have to utilize the data in your hand to get a deeper insight into your users. Understanding user behavior is an edge against the competitors and armed with this idea, product managers try to get the maximum from analyzing customer event data. The more product managers ask questions the more burden added to the shoulders of the data teams.

Self Service Tools

Self-service culture is gaining more popularity every day. Self-service BI tools are the saviors of the data teams that are burdened by the requests of the product teams.

There few things you can do implement a self-service culture successfully:

Having a proper data model is the first step to building a self-service culture. If your data is densely normalized, it would be hard to analyze it for the non-technical people even with the most user-friendly UI.

Use Self Service Analytics tools. It’s essential to use a product analytics tool which allows your non-technical people to efficiently create reports from scratch without asking assistance from the data team.

With the self-service product analytics tool such as Rakam, your product teams can get a deep insight on user behavior without being a burden to data teams.

Increase the understanding of data for business users. Even though self-service analytics tool such as Rakam doesn’t require it’s users to have a technical background it’s still advisable to educate your non-technical people on data analytics.

Organizing 1 hour a week SQL workshop would be super good considering the learning difficulty of SQL your business users can start seeing immediate benefits by playing with data.


Can Ozuysal