BigQuery is a fast, serverless, and easy-to-use data warehouse built by Google. Because the pricing model is pay-as-you go, BigQuery can be cost-effective for startups and enterprises. Dataform allows you to manage all data processes happening in your Bigquery warehouse, turning raw data into datasets that power your company’s analytics.
Dataform provides a powerful alternative to BigQuery scheduled queries. Schedules can be triggered by API, webhook or a time of your choosing. Success and failure alerts are sent to your team by Slack or email. Detailed run logs show exactly which SQL statements ran when, making debugging simple. And our parallel execution strategy minimises schedule durations and simplifies dependency management.
BigQuery costs $5 for every terabyte processed, so it’s important to keep track of the volume of data your pipelines are processing each day. Dataform provides simple reports for each of your schedules detailing how much each individual query within the schedule cost. When costs start to rise, use Dataform’s incremental tables to reduce your query costs with a few lines of code.
The Dataform web IDE is natively integrated with GitHub and GitLab. Version controlling your SQL has never been easier: create branches, commit changes, revert files and create pull requests without ever needing to touch the command line.
If your business is scaling fast and you want to ensure data quality, make your life easier, leverage engineering best practices and remain BI tool agnostic then don’t hesitate to use Dataform for a second!
Having modeled data using other tools in the past, this is much simpler and an easier environment to code in. The code compiles in real time and lets you know if there are errors in the syntax. It also helps generate a dependency graph for the data pipeline which is insanely useful.
After using Dataform for a while I really discovered the power of integrating an IDE with an ETL tool. The web based IDE completely eliminates the hassle of maintaining local dev environments.