Identify BigQuery use cases

1. Check if you constantly analyze and visualize data from 3 or more sources.

You can use BigQuery or any other similar tool to create your Marketing Data Warehouse: to reduce time pulling data from different sources to consolidate your marketing data sources to see the overall impact of your marketing actions to share your marketing data with other departments/your service providers Check if: your marketing platforms are the common used platforms that have connectors to well-known datawarehouses (BigQuery, Snowflake) or your marketing platform can generate CSV files that can be send to the datawarehouses

2. Check your operation's data like timesheets and ask your colleagues, to check if members of your team spend more than half a day per month on manual reporting or use a BI/Dashboard that doesn't connect to all the data sources.

You can use BigQuery for your report automation: to consolidate your data in one place and connect it to your BI tool (BigQuery connects perfectly with Google (Google Sheet, Data Studio, Looker) and non-Google reporting/BI tools (Tableau, PowerBI, Qlik, Excel) if you don’t have access to some data sources and you can ask someone responsible for this source to send you the CSV files with the data you need to your GCP (cloud storage and then bigquery) so you can build your automated reporting with this data

3. Check if you have in-house SQL/R/Python expertise and if you require Advanced data analysis / Data manipulation.

You can use BigQuery: to manipulate the raw data rather than work with what the analytics platforms have to offer to explore BigQuery statistical functions and Machine Learning capabilities to connect to one source of data (your data warehouse in BigQuery for example)

4. Check with your analytics team and developers where you keep your analytics data and if consolidating in one place would be beneficial.

You can use BigQuery as your data consolidation / data sharing platform when: you have data in different sources and you want to store it in one place for the ease of use (analysis, reporting etc.) you need to share some of your up-to-date data with your partners, service providers but you don’t want to give them access to your advertising/analytics/crm platforms

5. Check with your analytics team and developers if you interact with or have the need to use raw unsampled Google Analytics data

You can use BigQuery to access raw unsampled Google Analytics data (free connection for GA360/GA4, use connectors for GA Universal) to: combine GA data with your first-party data combine GA data with other third-party data sources perform some advanced analysis using SQL on your GA data run some BQML models on your analytics data (combined or not with other sources) modify/manipulate your GA data for improved reporting build advanced audiences using GA data combined with other sources and than integrated to your marketing platforms

6. Hold a meeting with your analytics, seo and development teams to check for opportunities to automate certain items like the generation of reports, updating audiences and website content.

You can use BigQuery for your data activation in these ways: build your automated reports based on real-time BigQuery data to make informed and fast decisions build “intelligent” audiences in BigQuery (based on your GA, first-party and other data sources; enriched or not with BigQuery ML) and share them with your advertising platforms for better targeting or exclusion adapt your website content to users based on your BigQuery data and BQML predictions

7. Check with your team to see if you need to perform customers classification, sales forecasting, data segmentation, product recommendation or time-series forecasts on your data.

If you don’t have a data scientist in your team but want to try ML on your data you can use BigQuery for simple machine learning tasks.

8. Check the file sizes and performance of your Google sheets and excel files. If you have issues with performance BigQuery can help with the management and analysis on gigabytes/terabytes/petabytes of data

9. Ask your team if you need access to google ads data while maintaining end-user privacy or if you want to join your data with Google's event-level campaign data.

You can use BigQuery to access Ads Data Hub that contains Google’s event-level ad campaign data if: you want join your first-party data with Google’s event-level ad campaign data to: unlock insights improve advertising efficiency achieve data-driven business goals yield more effective campaign optimization you need access to complete google ads data while maintaining end-user privacy