Automate Your External Reporting With the Modern Data Stack
With the right infrastructure, reporting can become truly routine. Even more than that, it’s a chance to demonstrate your value to the company and customers.
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Pedram Navid
April 27, 2021
11 minutes
Best Practices for Reliable Reporting
dbt, a popular tool for in-warehouse transformations, not only manages your SQL models, but also automates all provided infrastructure for building a reliable software project. For reporting purposes, these include tasks like creating documentation and testing data quality.
Document Your Data Models
To supplement data that you report externally, your partners will also need a data catalog, explaining what it is you’re sharing. If you’re on vacation and a customer asks your teammates what a particular attribute means, they’ll also be grateful to you for writing documentation that gives a quick answer.
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dbt makes it easy to add documentation as you’re building models, and automatically creates a documentation website that lists out all of the fields in those models. Right out of the box, you can share that list of columns as a data catalog for your partners.
Test, Don’t Stress
To avoid embarrassing data quality errors and easily diagnose broken joins or missing data, dbt lets you define tests on schemas (for example, make sure foreign keys are valid) and data (verify that last_active_date
>= account_created_date
).
By running tests every time your model builds, you can be confident that data quality issues won’t make it into the reports you share. If you have contractual commitments about reporting uptime or how each column needs to be formatted, testing can keep you safely in compliance.
Version Control: Saving Your Work
All of the work you do in dbt, whether writing a data model or configuring tests and documentation, is part of a single “project.” The whole project is easy to put under version control, so you’ll never lose your work, and multiple people can collaborate on building a project at the same time.
Data Sharing: The Final Mile
Once the E, L, and T are finally done, it’s time to get the report to your customers. Emailing a flat file takes time and is error prone: you might attach the wrong file or forget to CC an important stakeholder. Besides, I always feel conflicted sending customer info through such an open system.
Additionally, as your company grows, you’ll have more and more reports to share each quarter. To scale your reporting, here are a few suggestions for how this final step in the process can be automated away.
Share Resources From Your Data Warehouse
Many cloud data warehouses, such as Snowflake or BigQuery, allow you to grant external users read-only access to particular tables or datasets. Besides freeing you from needing to “deliver” any data to an external system, your partners always know where to find the most recent version of your report.
Dashboards
You might already be using a tool like Looker, Metabase or Data Studio for internal business intelligence. These platforms all support sharing data with people outside of your organization. You can provide partners with a link to click on, or set up automatic email delivery of particular slides. And just like sharing data from the warehouse, your customers can be sure that they are looking at the most up-to-date data.
Sync With Key Business Systems
What if your reporting moved directly into your customers’ business systems? Hightouch lets you sync data from your warehouse to any SaaS tool. No custom engineering required — everything is SQL based, so you can reuse the data transformations you’re already doing.
With Hightouch, shared data will always be up-to-date; unlike the warehouse and dashboard approach, your customers will never need to access your systems for an update. Everyone will be on the same page, because they’ll always be looking at the exact same data.
To see how Hightouch’s approach to operational analytics can power your reporting, set up a demo with a data expert.