For Database (Data Warehouse)

[kamrankhan]

I often use Google Sheets for data entry and also for live data analysis in Power BI to gain insights. I'm considering whether it's better to connect Google Sheets with a data warehouse first and then use it in Power BI desktop, or if it's better to use Google Sheets directly in Power BI desktop. Please suggest.

[Anonymous · Accepted solution]

Hi @kamrankhan ,

If the data is relatively small and needs to be updated in real time, using Google Sheets directly in Power BI may be the best option. However, if you are working with large datasets or need advanced data management and analytics capabilities, it may be more beneficial to connect Google Sheets to the warehouse first.

Here are two ways to connect to Google Sheets.

1. Power BI Desktop connects directly to Google Sheets.

For the first way, it is convenient and quick to realize the direct connectivity effect, as well as reflecting the data on Power BI Desktop in real time and quickly. At the same time it avoids the extra costs associated with warehouse.

However, it has its drawbacks as well, it cannot handle large data sets and once it encounters a large data set it will degrade the performance of Power BI. It also reduces the quality of protected data when not using a warehouse.

2. Connect to Google Sheets through the warehouse, and then use Power BI Desktop to connect to the warehouse.

For the second approach, warehouse is designed to handle large amounts of data, making it suitable for growing data sets. It can also perform complex queries and analysis on data before it reaches Power BI.
However, setting up and maintaining a warehouse is more complex and requires some specialized knowledge, and the cost of a warehouse is higher, especially if you need high performance and storage capabilities.

Best Regards

Yilong Zhou

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[kamrankhan]

Thank You .....!

[R1k91]

Warehouse is always a good idea when you need to collect data from multiple sources, at different timings and normalize them to get insights later.

Power BI desktop let you do this at some extent behind the scenes, with Power Query you extract data, transform and load in the VertiPaq database.

I've seen many people getting rid off warehouses loading and traforming everything in a single Power BI Desktop file but I think it's a limited solution.

When you need to reuse logic (for example to get the Item dimension), you need to copy and paste the same M code over and over again. this yields to data duplication and it's error prone (this is where dataflows come in).

having a centralized DW gives you the possibility to centralize the logic (and data), avoid data duplication and get a better control. finally a centralized DW helps you to reuse a "golden model" with multiple reports on top of it.