AI supported data language recipes
AirOps is a free productivity web app created by developers of the same name. It's the ideal database management system for data engineers, data analysts, software developers, and other similar professions. It's packed with a set of handy features that are all easy to use and essential to making your workload more efficient and effective.
AirOps uses a number of AI-powered recipes for diagnosing and drafting SQL queries, writing Python scripts, writing a human-friendly description for complicated queries, and more. The app is completely free to use for individuals and small teams and can be linked to major data warehouses.
Streamlining data science through AI
You can utilize a selection of recipes which includes Query Writer, SQL Fixer, Query Updater, SQL Query Optimizer, Question Suggestor, Table Documenter, Query Explainer, Python Script Creator, Generate dbt Config, dbt SQL, and dbt Python Creator—all ready to use as soon as you log in to your Sidekick account or your team's AirOps Workspace. These AI-supported recipes are all beginner-friendly.
To use, make sure your data warehouse is connected to Sidekick to use this web app. Currently, Snowflake, Redshift, BigQuery, and Postgres databases are supported, but more will be added in future updates. You can also receive some sample data to tweak and play around with when you sign up and before you link your data warehouse to your Sidekick account.
The service is also SOC-2 Type 1 Certified to ensure every data you input in the app is safe and not stored within the servers. However, one drawback of this web app is while it's free to use, it comes with a usage cap. The limit is reasonable enough to be used by a team of small people, while larger organizations might have trouble with it.
Great data companion for small teams
AirOps is an excellent tool to make the lives of data professionals easier and streamlined with the help of artificial intelligence. It's free to use by anyone but comes with a usage cap that might hinder larger teams from processing large sets of data, but enough to run a small team. Overall, with its compatibility with major data warehouses and efficiency to use, its advantages trump over its flaws.
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