Category: Power BI

Matthew Roche dives into Power BI’s enhanced compute engine:

I’ve been seeing more questions lately about the dataflows enhanced compute engine in Power BI. Although I published a video overview and although there is feature coverage in the Power BI documentation, there are a few questions that I haven’t seen readily answered online.

A lot of these questions can be phrased as “what happens when I turn on the enhanced compute engine for my Power BI Premium capacity?”

Most of my responses start with the phrase “it depends” – so let’s look at some of the factors the answer depends on.

Click through for those factors.

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Imke Feldmann walks us through separating data from report in Power BI:

The other day I discovered a neat way to split up an existing Power BI report into a Golden Dataset and a thin report file with very few adjustments to the existing setup. Imagine you have a Power BI report published for some time already in an app with row level security. Now, you want to create other reports from the dataset as well and decide it’s time to create a golden dataset from which multiple other thin reports can also be fed from as well. But ideally you want to keep your published app, that many users are working with already, unchanged.

There’s a way to do this and Imke shows us the way.

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Paul Turley compares Power BI paginated and analytic reports:

This brings me to the subject of this post: Paginated and Analytic reports.

Before we had Power BI, we had Reporting Services. When the focus of my career and consulting practice became Business Intelligence – fifteen to about five years ago – most of the “BI reports” I created were in SQL Server Reporting Services (SSRS). We could create a variety of charts and reports that allowed users to drill-down from summary to details. We could create reports that allowed a user to drill-through, from one record or report item to another report that presented more details. With a little creativity, we could create reports that allowed users to click items that would filter other items on the same report. It took some work and time to create these interactive “drill-through-to-self” reports. Today, after transforming data into the right format for a tabular data model, this type of interactive functionality just magically happens in Power BI with very little report design effort. But, Power BI is primarily a tool for analyst users to create their own reports and to get answers to business questions rather than for IT developers to create reports that print or export perfectly to a PDF or Excel.

For now, Paul is asking for thoughts and questions with the promise that there will be an update to the post. So stop on by and ask a question or two.

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Soheil Bakhshi has an interesting challenge:

Many of you may already thought that we can use CALENDARAUTO() in DAX and we are good to go. Well, that’s not quite right. In many cases there are some Date or DateTime columns that must not be considered in our Date dimension. Like Birth Date or Deceased Date. More on this later in this post.

In this post I share a piece of code I wrote for myself. I was in a situation to identify the Start Date and the End Date of the date dimension many times, so I thought it might help you as well.

Read on for a solution when not all date columns are relevant.

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Ed Hansberry shows how to perform a conditional join in Power Query:

I am going to use two tables for this example, Fact.Sales and Dim.Customer. I only want my Fact Sales table to have customer info for the Buying Group Tailspin Toys. That info is in the Dim Customer table. I can do this several ways.

1. Do the merge, expand the Buying Group column from the Customer table, then filter to only show those rows.
2. Pre-filter the Customer table for Tailspin Toys in the Buying Group column, then do the merge. It would need to be an Inner Join, otherwise you will get nulls in the Sales table when you expand, and then you have to filter those out. Which you can do, but it is more steps.
3. You can bypass all of that and do it in one step.

I’m not going to bore you with how to do methods 1 and 2. Let’s do method 3, a conditional join!

Read on for the approach, which also can take advantage of query folding when possible.

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Gilbert Quevauvilliers has an easy method of constraining data sizes in Power Query:

How cool would it be to not have to manually update your dataset to keep data for last 2 Years (last year and this year to the current date)?

In this blog post I will show you how you can easily filter dates in Power Query to show dates for last year and year to date by using the GUI and not having to hardcode anything.

I must admit the first time I saw this was when I watching my good friend Reid Havens presenting. Thanks Reid!

Read on for the technique.

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