PivotTables, or pivoting, is by far the best analytical power of Excel. You digest the data and play with it on the fly. Heck, PowerBI is pretty much PivotTables with pretty visuals, just a lot smarter (because of DAX).

While PowerBI offers many stunning looking visuals including matrices, they do not include out of the box/easy to use pivoting experience. You could use hierarchies to some extent, but they are fixed and can only be changed while in Edit mode.

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Lower dates granularity-linear split

When creating a budgeting prediction, most of the time we are creating it on the higher granularities. Rarely we do it on a daily basis.

But sometimes we are required to match budgets to actual sales on lower granularities than the one we previously set (e.q. the manager wishes to see how would the budget split look like if we were to split it on a daily basis to see which days are above average).

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High cardinality columns are often the problematic part of the data modeling in most environments, including PowerBI.

Since the PowerBI data model resides on a columnar database, having high cardinality columns impact both performance and the size of the model. This is especially the case with columns having more than 2 millions of distinct values. These columns can occupy almost half of the data model size and are hard to compute fast DAX code against them.

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In this article, we will see how to combine different dimensions and facts inside a single matrix table visual.

This approach helps us create fewer measures and tables, but at the same time, it provides us with greater design possibilities, like conditional formatting across the whole column even though there are different measures invoked inside the column. The previous would be impossible without this technique.

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In the report below, you can see how PowerBI is becoming more googled term than Microsoft Excel in most of Western Europe and Australia.

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Regardless of the people job title, preparing and analyzing data becomes an integral part of their work. Most people for this purpose use Excel, because it is the fastest and most flexible tool for processing and analyzing data. But as the data sources and analysis needs increase with each day, traditional methods of processing and analyzing data in Excel become slow and limited.

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PowerBI has a lot of visuals that can help you visualize geo-data. I’ve used most of them, and I can guarantee that none of them come even close to the newly introduced Mapbox Visual. Even those that are pay to use like ArcGis has some flaws (slow rendering time, terrible Heatmap, limited lasso etc). Mapbox also has its premium subscription option, but you need to subscribe only after your visual is viewed more than 50.000 times a month, and that is far above the normal PBI monthly report usage. Which means it's basically free with all features included!

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With the finals just around the corner, hope you will enjoy exploring the main statistics of the world cup! :)

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ABC analysis is one of the most commonly used categorization techniques. This technique divides subjects of analysis (Products, Customers, Inventory etc.) into different categories based on subject importance.

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The Internet is full of valuable online free sources which, if used correctly, can bring great incremental value to company employees.

One of those sources is Eurostat, the statistical office of the European Union. On the official pages of Eurostat, you are able to pull pretty much any statistical data about the Macroeconomic environment of the member states. They provide free access to their databases, and even an API connection, so you can always have the latest available data at your disposal.

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