Contrary to popular belief, self-service analytics done right consists of much more than just pulling numbers from dashboards.
In order to actually drive value between the data team and the data self-servers out in the business, teams need to align on the intricacies of the end-to-end self-service program from the start. That way, they ensure the initiative is actually meaningful and value-generating for the business.
A helpful, easy to remember analogy for understanding self-service analytics
Four clear reasons that reinforce that self-service analytics aren’t going away
How the concept of Everyday AI makes self-service more scalable and more valuable
For those working with data, running into roadblocks because of siloed data is frustrating and, not to mention, has a tangible cost. Think lost time, incomplete data projects, incorrect models, and more. This ebook takes a deeper look at how all of this is relevant in the context of self-service analytics and how critical adopting a culture of data sharing is.