Ascend Use Case
Data Lake Ingestion
Ascend enables you to ingest data from anywhere into your data lake, and easily enrich, transform, and stage your data for downstream use cases and tools. Ascend simplifies the management of tiered storage by continuously syncing sources with your data pipelines, and allowing data teams to tap into the intermediate data sets between transformation steps. Ascend’s DataAware Intelligence tracks all data lineage and user activity to deliver end-to-end accessibility and governance controls.
Zero Maintenance
Data Ingest Pipelines. Ascend monitors your data sources and propagates any changes downstream.
Reduced Compute Cost
of running pipelines. Ascend automatically optimizes your data pipelines & infrastructure.
More Access to More People
Empower data science & analytics teams with direct access to pipeline optimized files.
How it Works
- Choose from one of Ascend’s many prebuilt data connectors, or write your own and Ascend will run it for you
- (Optionally) specify data transformations in SQL, Python, Java, or Scala
- (Optionally) specify data destination(s) (similar to your data source)
- Ascend automatically backfills all your data, coordinating your data transforms, and synchronizing the results with your data destinations
- Ascend monitors your data sources for changes, watching for new data, modified data, and (yes, even) deleted data; when changes are detected, Ascend efficiently propagates those changes automatically
What to Expect
- Reliable Data Integrity: Ascend manages all data and updates as they happen with guaranteed data accuracy, automatic lineage tracking, and dependency management
- Deduplication of Redundant Storage and Operations: Ascend eliminates duplicate operations and redundant data sets, significantly decreasing storage costs and improving performance for repeat queries and operations.
- Automated Storage Maintenance: Ascend completely automates tedious storage tasks such as garbage collection of stale data, intelligent backfilling, and incremental data with minimal reprocessing.
