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Power BI, how can you make a Google Analytics time filter

This activity is quite beneficial for enhancing your Google analytics<br>Power BI reports, statistics, and dashboards. Essentially, by<br>employing this filter, you will be able to improve your organization's<br>insights and completely investigate your business processes in order<br>to form more correct conclusions. You'll get a lot more insights, and<br>they'll be much deeper and more dependable.<br>

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Power BI, how can you make a Google Analytics time filter

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  1. Power BI, how can you make a Google Analytics time filter? Google analytic to power bi

  2. 1 • Power BI is one of the top business intelligence tools, but it lacks a filter for comparing different time periods. Google Analytics, on the other hand, provides a far more powerful time period comparison filter, but it's not a business intelligence tool and is just good for assessing web traffic.

  3. 2 • The filter that allows you to compare two periods of time is one of Google Analytics' most popular features since it allows businesses to assess their company's metrics using bespoke time periods that aren't tied to each other. This feature is particularly valuable for gaining a diachronic understanding of your company's data and how it has changed over time.

  4. 3 • To make the filter operate like the Google Analytics one, you must first equalise the values of both time intervals - because this filter allows you to select time periods of varying durations. The values of the various periods must then be normalised so that they can be compared without errors or malfunctions. • We only need to follow these two easy steps to add the filter to Power BI:

  5. 4 • 1)Create a model that allows a user to pick two different dates from the same date field. • 2)Create a DAX formula that returns the same result for both times. • Create a Model • To begin, launch Power BI and create a new 'Date' table. Making a copy of the existing table is all that is required. After we've made the copy, we'll need to link both tables with 1:1 correspondence and then construct a bidirectional filtering relationship between them, which we'll leave inactive for now.

  6. 5 • Once we've gathered all of the relevant tables, we'll need to develop a DAX formula to ensure that they all have the same value. The following is the formula we must use: • We write the original metric . • The table where the duplicate filter was applied, is expressed in 'ALL.'

  7. 6 • Finally, we activate the connection with 'USERELATIONSHIP.' • Now you can compare all the values which you want . • This activity is quite beneficial for enhancing your Google analytics Power BI reports, statistics, and dashboards. Essentially, by employing this filter, you will be able to improve your organization's insights and completely investigate your business processes in order to form more correct conclusions. You'll get a lot more insights, and they'll be much deeper and more dependable.

  8. Summary • Users can develop their own reports, dashboards, and visualisations without the help of IT. Use Power BI to replicate and analyse your Google Analytics data.

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