Connect Power BI to Google BigQuery Use the public datasets to develop your skills and demonstrate the power of both platforms for FREE In this example we use the actual wholesale sales data for the US state of Iowa that is one of the public datasets https://www.selectdistinct.co.uk/2023/09/07/connect-power-bi-to-google-big-query/ This is a great starting point for anyone wanting to build their skills with data that can be refreshed #PowerBI #BigQuery #PublicData

1. Power BI Tips
and Timesavers
Analyse public data sets like
the Iowa Liquor sales
Connect to

2. A Quick Guide to Connecting Power BI to BigQuery
Power BI is a leading business intelligence platform, with powerful features for
self-service analysis
BigQuery is a fully managed cloud-based data warehouse platform for you to manage
your data
The great thing about both of these platforms is that they both have a really useful
free tier, enabling you to use some of the excellent public datasets to build your skills

3. Google Public Datasets are a great resource for
learning
Google has made a variety of public
datasets available
You can access these and query
them and use them to develop your
skills
The marketplace in Google Cloud
Platform is where you need to head
to find the public datasets

4. Google Public Datasets are a great resource for
learning
We are going
to use this one

5. Google Public Datasets are a great resource for
learning
The great thing about this data set is that is real data,
updated monthly and it has plenty of variation for you to try different techniques on

6. Google Public Datasets are a great resource for
learning
Click the view data set button and you are taken straight to the data set in Google
BigQuery

7. Google Public Datasets are a great resource for
learning
Effectively this is a database with a single table called ‘Sales’

8. Connect Power BI to BigQuery
Step 1. Click on Get data on
the ribbon, then click more...
at the bottom of the menu

9. Connect Power BI to BigQuery
Step 2. Select Database, then scroll
down to Google BigQuery

10. Connect Power BI to BigQuery
Step 3. Connect Power BI to Google BigQuery by clicking the
connect button
If you are already logged in then thats all there is to do
If you are not already logged in then you may be taken to a
login screen for authentication
From here you can go into the advanced option and explicitly
write the SQL to retrieve the data you need

11. Connect Power BI to BigQuery
From here you can go into the advanced option and explicitly
write the SQL to retrieve the data you need
Or, if you click OK you are presented with a navigator screen
Scroll down to find the Iowa Liquor sales database, then select
the sales table. Ensure there is a green tick next to the table
If the data set was small then you could simply click load....BUT
This data set contains over 27 million rows so we will need to
strip it back
We will just load the last 2 years as an example
Click Transform Data then Import

12. Limit the data in Power Query
On the date column, select
the drop down arrow
Then date filters, In the
previous
Now make sure the filter is
set as below to retain the
newest 2 years of data

13. Limit the data in Power Query
(You may want to filter down further to shrink the
data set and avoid costs, so feel free to add more
filters before loading the data to Power BI)
For this example, we want a large data set so we will
use the full 2 years
Now select Close and Apply from the ribbon
You will then see a loading screen with a count of
how many rows have been loaded
Typically there is around 2.5m rows per year

14. Limit the data in Power Query
After the data has loaded you can then
begin to visualise the data
We will look at sales over the two years
Select a line chart visual and set the X
axis to date (month)
set the Y axis to sale-dollars
finally set the year as the legend to
compare the last two years on the same
chart

15. As you have seen its actually quite easy to connect Power BI to BigQuery
and use these public data sets for your own learning and development
By exploring the data you can begin to see real patterns in seasonality,
identify best sellers, leading stores and use some of the more complex
geo location data to present the data in easy to understand ways

16. For more Tips, Tricks and
Timesavers, visit our website
Business Analytics Blog – Select Distinct
Credit: simon.harrison@selectdistinct.co.uk