Speaker

Klaus Jürgen Folz

Klaus Jürgen Folz

Brunner BI - Lead Power BI Developer

Vienna, Austria

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• Bachelors in mechanical engineering
• More than 5 years of experience with Power BI, Python and SQL
• Lead developer of Measure Killer, the external tool for Power BI
• Microsoft certified Power BI-Data Analyst (PL-300)

Area of Expertise

  • Information & Communications Technology
  • Physical & Life Sciences

Topics

  • power bi
  • python
  • Machine Learning & AI

New ways to optimize shared datasets in the Power BI Service

In this session, we will take a look at a new approach to reduce the size and increase performance of our Power BI datasets and reports.

We all know the best practice to only load columns we need into our data model. In theory this makes perfect sense but in reality it is hard to achieve. We can use external tools for Power BI however to identify which columns are used and which are unused. This will help us shrink our dataset while making sure nothing breaks down in our reports.

As soon as we enter the Power BI Service, things get more complicated. Many people could have built reports on a centralized (shared) dataset in our organization. It becomes too risky to remove anything from that. The result is that our Power BI tenant gets bloated and the data is just piling up.

Even for this there are solutions out there and we will look at an automated way to optimize these datasets as well. It is possible that more than 50% of the size of the dataset is not used anywhere but nobody knew about it.

In this session you will learn to harness external tools for Power BI to optimize and shrink the size of your datasets especially in the Power BI Service. We will be able to declutter things and make sure everything is nicely organized.

Optimize and clean golden datasets in Power BI

Once we publish datasets and reports and our tenant starts to grow, it can get harder and harder to see which data is actually in use.

Golden datasets are a central piece of every BI architecture and can consume a lot of processing power and memory in a Power BI Premium capacity. So far, we have very limited options to optimize these datasets.

With the latest version of "Measure Killer", an external tool for Microsoft Power BI, we can analyze artifacts in the service. Measure Killer will find all reports connected to a dataset and analyze which columns and measures are used in which report. It will also identify the part of the data model that is not used at all.

Measure Killer lets you clean your model in an automated way (deleting unused measures and columns) and can generate a detailed documentation of your model and report.

The actions outlined above will improve performance, reduce refresh times and thus help you optimize your Power BI tenant.

This session is meant for any Power BI admin, developer or architect. You will learn how to optimize a centralized dataset in your Power BI tenant.

Introducing the "Measure Killer"

"Measure Killer" is a new External Tool for MS Power BI that helps you clean up your dataset, Power BI tenant and analyze your reports.

In this session we will show you:
-How to use it to reduce your model size for unused columns
-How to "kill" unused measures at scale
-Its model and report documentation features
-How to clean your shared datasets (MK can analyze multiple reports connected to one dataset)
-Its XMLA/Rest API capabilities (analyzing artifacts in the Power BI service / running at scale - currently under development)

You will require Microsoft Power BI Desktop and "Measure Killer" which are both free to download, install and use.
The XMLA/Rest API features of Measure Killer are a paid upgrade to the free version.

Measure Killer currently has 3,000 downloads and 300 weekly users since its public beta started in Oct 2022
Check it out at https://www.measurekiller.com or get it from the Microsoft store https://apps.microsoft.com/store/detail/XP8JN7N3RG4N6H

Data Saturday Gothenburg 2024 Sessionize Event

September 2024 Göteborg, Sweden

Klaus Jürgen Folz

Brunner BI - Lead Power BI Developer

Vienna, Austria

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