Building Bridges — Best Practices for BI Teams Working with Data Teams
Implementing analytics at your company is a multi-team job. In Building Bridges, we focus on helping end-users, app builders, and data experts select and roll out analytics platforms easily and efficiently.
Selecting and implementing a new BI and analytics platform is a big decision and can be a vital part of an organization’s digital transformation. Rolling out a new platform involves everyone who’ll implement, maintain, and most heavily use such a platform.
Advanced analytics and BI democratize access to data, empowering more business users to develop insights, with less reliance on data professionals who have previously been gatekeepers of this information. As business teams become more involved with data in their day-to-day work, it’s natural that they should play a role in choosing the right platform and determining how it will benefit their organization.
Making these decisions — which platform to choose and how to put it into operation— requires buy-in from both the analytics and BI team (the probable end-users/frontline users) and the data team (who will prepare the data, build the models, and connect datasets).
Importantly, to make the best decision for your organization, each team must understand, acknowledge, and address the needs and concerns of the other.
Working together: Understanding priorities
Mutual understanding can only come about via dialogue between teams, so that they can understand the priorities and needs that their BI and analytics platform should meet. It’s important that the analytics and BI team clearly indicate their needs and that the data team understand what the BI platform will be used for and how they can build the right data model(s) to suit the analytics and BI team’s requirements.
To help achieve this, let’s look at some considerations that data teams and analytics & BI teams should discuss in the vital conversation about selecting and implementing a new platform, so that they both can get the most out of the process.
This article was originally published by Sisense, read more.