The DataKitchen DataOps Platform consolidates the management of all the people, tools, operations, and environments in your entire data analytics organization.
Several elements facilitate a controlled data pipeline to increase collaboration and data quality and reduce errors and time to deployment.
Kitchens: Repeatable, virtual work environments, which enable team members to make changes independently and experiment without breaking production.
Recipes: Single-direction processes built to automate the execution tools and hardware that drive your production pipeline, from data access to data transformation to value delivery. And, every step of a recipe supports automated tests to catch errors in real-time.
Variations: Different modifications of a recipe that define specific parameters for use when compiling the recipe at runtime.
Orders: Recipe executions are the run information, providing you with the process analytics to show how your teams are reducing errors, speeding deployment, and improving productivity.
Ingredients: Any processed data or analytic component can be saved as a reusable Ingredient so other team members can access, reuse, and incorporate into other Recipes or Kitchens.
DataKitchen offers its platform functionality via its web app, command line interface, and REST API.
- Web App (UI): A full-featured UI includes recipe graph visualizations and both a form-based editor and a file-based editor.
- Command Line: DataOps users can also work via DKCloudCommand, the command line tool for interacting with the DataKitchen API. DKCloudCommand requires Python 3.8.
- API: Most all of the platform features available via the web app and command line tool are also available directly via the DataKitchen API.
Updated 3 months ago