Power BI Time-Intelligence: Beyond the Basics
Power BI Dataset Refresh: Beyond the Basics


Power BI Time-Intelligence: Beyond the Basics

Level: Intermediate

Summary: Everything you need to know about time-intelligence in Power BI with a heavy focus on DAX and date tables.

Goals:

  • Understanding the importance of a “good” date table and how it can be effectively leveraged to simplify complex time-intelligence calculations.
  • Working knowledge of the most common DAX time-intelligence functions, how they work under the covers, their limitations, and how to extended them to accommodate a variety of common business requirements.
  • How to detect, modify, and control DAX evaluation context in a standard pattern that can be universally applied to solve any time-intelligence calculation requirement.

Abstract: Time-Intelligence refers to analyzing calculations and metrics across time and is the most common type of business intelligence reporting. Power BI has a lot of built in capabilities to help you get started but these alone are not enough for most real-world solutions.

The key to mastering time-intelligence in Power BI is a good date table and understanding how to control the filter context. This session will teach you about both!

In this (demo-heavy) session, we’ll quickly review Power BI’s built-in time intelligence capabilities and why you should avoid them! We’ll also cover the importance of a good date table, what attributes it should include, and how it can be leveraged to simplify complex time-intelligence calculations. Finally, we’ll breakdown many of the 40+ DAX time-intelligence functions, showing you how they work under the covers (hint: filter context) and how they can used in combination to accommodate complex business logic.


Power BI Dataset Refresh: Beyond the Basics

Level: Intermediate

Summary: Ever wondered what’s happening under the covers when refreshing a Power BI dataset? Why is it slow? Can we make it go faster? This is your session!

Goals:

  • Build a deeper understanding of the underlying data structures in a Power BI dataset and how they come into play when a Power BI dataset is refreshed.
  • Discover a variety of dataset refresh strategies, their trade offs, and how to determine which is the best fit for your specific scenario.
  • How to identify and fix common bottlenecks faced during the dataset refresh process.

Abstract: Ever wondered what’s happening under the covers when refreshing a Power BI dataset? Why is it taking so long? Can we make it run faster? Is there some sort of resource bottleneck I’m running into? How can I tell?

Refreshing a Power BI dataset can be a resource intensive workload and depending on your specific requirements (e.g. speed, availability, data volume, etc) it may not be feasible to process the entire model each time.

In this session, you’ll learn about…

  • the internal data structures behind a dataset (including the difference between a regular and calculated column!)
  • what happens and in what order when you refresh a dataset
  • several common refresh strategies and the associated trade offs
  • how monitor and detect common resource bottlenecks

Spoiler: yes, the data model matters and so do data types! We’re also going to use words like encoding, compression, and JSON but in a very business-friendly way 😉