How to set up scheduled queries in BigQuery and send the results to Slack

In this video you'll learn how to set up scheduled queries in Google BigQuery and send the results to a specific channel in your Slack account using Zapier.
This flow is great for limiting the chance of duplications appearing in key data sources.
You could also use this flow to achieve the following:
1. Get a list of problematic accounts that need to be addressed.
2. Get a count of the number of tickets opened in the last 24 hours.
3. Get a count of the number of refunds requested in the last 24 hours.
4. Get a list of tasks which are overdue, grouped by owner.
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[@chrism3790]

As useful as this may at first seem, scheduled queries are absolute nightmares.
Analysts often don't know how to sustainably scale data models or how to write incremental load jobs, and end up writing spaghetti ETL code with scheduled queries, with dependencies and schedule constraints between them, and the complexity blows up super quickly. Then they forget to set a service account to run them, and the scheduled queries fail when they leave the company.
A few other major downsides:
- No version control
- No deployment process
- No query tags
Avoid them.

[@theanalystsplaybook]

These are great points Chris. Thanks for sharing.

[@hemdatascience369]

Hi ProjectBI, Thank you for the walk through.
Can you suggest me " How to deal, when the Scheduled Query does not work properly ? "

[@theanalystsplaybook]

Hey Hem. I'm not sure what you mean exactly. What do you mean by "does not work properly"? The process will fail if the query does not successfully run. If you notice that you are not receiving a message to Slack, then you would revisit the scheduled query and troubleshoot the failing query. BigQuery gives you a lot of indicators for why a query is failing.