Ascend Use Case

Accelerating BI & Analytics cuts down the time it takes to ingest new data feeds into Business Intelligence and Analytics tools by 90%. As a single, flexible, and seamless ETLT platform, enables users to ingest data from anywhere, transform it using SQL, Python, Scala, or Java—depending on the business needs and user preference—before writing the transformed data feeds directly into the BI or visualization tool of your choice. Ascend makes building data pipelines truly self-service, so what used to take weeks or months of effort and trial-and-error, now takes minutes.

Ensure Data Quality

Easily explore and validate your data and create a validation component that will run every time new data appears.

Increased Flexibility

For ingesting, transforming, and using a variety of data feeds in your preferred analytics tool

Visualize Pipelines

Simplify complex queries into easy to understand sequential operations thru a modern DAG-based GUI

How it Works

  • Connect directly to any source with the flex code data connectors and Ascend will automatically collect and persist the data
  • Specify data transformation logic with SQL, Python, Java, or Scala
  • Quickly and easily iterate on transformations and check output records and partition profiles at every step.
  • Ascend automatically processes and aggregates new data to use in your preferred analytics tools
  • Write the resulting data directly to a Looker, PowerBI, or other BI tools or write it directly to a data warehouse, blob store, and more.

What to Expect

Check out our documentation to learn more about integrating with your BI tools.