Power BI has been improving on monthly basis and we get to learn new features in this tool every now and then.

Recently working within a project I felt an extreme need of organizing my measures in some way. I ended up adding so many measures based on the requirements that my original dataset started looking messy. I recently came across Measure tables term in Power BI. Trust me, this measure table is an amazing way to organize all the measure calculations, specially when you have so many of them in your report.

Today in this blog I will take you through the steps of creating these measure tables in Power BI by taking a simple example. 

If you are Power BI enthusiastic, what all links you should have handy with you. I compiled a list for you.

This blog is about how to use SEARCH/FIND function when <find_text> is a list values.

The article is about how to extract Date Time From Texts In Several Scenarios.

Sometimes we want to compare the data from certain month with the data from same month but in previous year.   

For example you may want to compare the sales data for each month in 2019 vs. 2020. You may not easily find out that which months in 2020 has more sales compared to 2019 and which month has relatively negative result compared to 2019.   

Therefore we have a way to highlight the decrease data.

Whenever we have targets, typically, they're at the month or at the year level. All are other data like sales purchase is typically at the level. Now we want to analyze both these data together there is a challenge one data is at the year level another data is at the day level. To deal with such scenarios we have options of creating a day level table or creating a measure that can give us the Day level target.

In this blog we are going to take the approach of creating a Table, that will provide us data at the day level.

We recently helped The Oil & Gas Technology Center (OGTC) and Microsoft to facilitate a codeless Power Platform hackathon to solve industry challenges like tackling CO2 emissions, avoiding downtime, increasing asset efficiency, etc. Intelligent Plant provided a live connection to vendors historians some of which contained years of data using the Industrial App Store.  Rightfully, the participants (engineers, data scientists and others) went ahead and tried to extract RAW data from data silos containing 5+ years of data for multiple sensors at 1s frequency, but is this the right approach?

You have implemented Row Level Security to restrict users to view data accordingly but you want to create a dynamic Admin role that can be assigned to any user to view all data and at the same time, you do not want to assign Admin permission to the user.