Many analytics teams are looking to be more effective with their time so it is spent more on using data to reach business goals and less on routine reporting.  To solve for that, many are looking to make part of their analytics program self-service.

What does it mean for an analytics program to have a self-service component?  What are the steps an analytics organization needs to take to achieve this?  What are the key roles that need to part of the team?  Is self-service analytics a cliche or wishful thinking?

On this week’s episode of the 33 Tangents podcast, Jason and Jim are joined by Jon Narong to discuss their experience with organizations wishing to make data more self-service.  They cover the benefits, what organizations need to plan for, and the risks & potential pitfalls.

We know your time is limited, so it means a lot to us that you would spend some of your time with us. If you have found this episode to be valuable, we would appreciate if you would share it.

And if we are getting you hooked, don’t forget to subscribe, like, and recommend on your favorite podcast platform.

The 33 Tangents video simulcast is now available on YouTube

Subscribe on Apple Podcasts

Subscribe on Google Podcasts

Listen on TuneIn

Listen on Amazon Music

Website: www.33sticks.com

Email: [email protected]

Twitter: https://twitter.com/33Sticks

Facebook: https://www.facebook.com/33sticks/

YouTube: https://www.youtube.com/channel/UC8KUpp_LygXotCrKgR9ZoBg