Jun 21

Jun 21 Dimensions of Self-Service in Power BI: Part 2 - The Dimensions of Learning

Kurt Buhler

Data Culture & Adoption

PART 2: THE DIMENSIONS OF LEARNING

*Ways to think about*
*user learning paths*
*for successful Power BI self-service*
CLICK FOR PART 1

IN THIS SERIES

It’s important to equip users with data literacy & skills if we ever want to be successful with self-service analytics

With Managed Self-Service in Power BI
, there are a lot of options. How do we ensure everyone has the skills they need to use tools properly? This is an important part of our strategy; even if we make good decisions about which tools are used for which use-cases, it won’t make a difference if users don’t know how to use them.

In this article, I visualize my thoughts on the different dimensions of learning self-service tools in Power BI, and share tips to proactively manage these dimensions.
When depicting the self-service learning paths in this way,



it can be easier to reflect on your self-service strategy - how certain tools & users will be supported to answer business problems, and how they will be managed.
- Primary Tools (Previous article)

Different base self-service tools & approaches used to address business problems with data.

A user selects a node on this axis based on the problem they try to address.

*Example: Dataset creation*
- Learning Milestones / Components for each tool Methods, concepts & mechanisms used within a tool to be effective with it. A user should always be progressing along this axis; a user should always be learning. Example: Using date dimension tables in the data model instead of auto date/time
- Different approaches Ways to approach a specific business data problem using tool components, together. A user selects a node on this axis based on the problem & their own knowledge. Example: Creating date tables [and columns] with DAX calculated tables & datetime functions
- Change in the tools & platforms over time How any of the above change o

📌 Dimensions of Self-Service in Power BI: Part 2 (Jun)
🏢 Data Goblins
📍 Jun