Data observability solution delivers comprehensive insights into performance, data quality, and cost

Acceldata, the market leader in Data Observability, today announced an integration with Databricks to reduce operational data complexity and maximize return on Databricks investment. Acceldata’s data observability for Databricks improves data trust, optimizes performance, and provides spend intelligence for an enterprise’s Databricks environment through a single management dashboard.

The Acceldata Databricks integration offers:

Trust: Deliver high-quality data on time, every time
Scale: Improve data engineering productivity and accelerate adoption
Control: Ensure resources are used efficiently and with guardrails to align cost to value

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The Acceldata integration tracks end-to-end data pipeline performance and quality inside and outside of Databricks to ensure data reliability and improve data trust across the entire data environment. The solution includes data performance optimization features, such as automated stability tracking, which help enterprises eliminate bottlenecks and prevent data incidents, which is aligned with an alerting and notification system that enables data teams to predict issues and accelerate remediation. Cost intelligence dashboards offer utilization insight and usage guardrails that improve resource efficiency, eliminate waste and align cost to value for improved spend intelligence and budget forecasting.

“Data observability offers visibility into the entire data pipeline to help customers observe the overall quality and health of their data end-to-end to help predict potential issues and prevent costly data disasters,” said Rohit Choudhary, founder and CEO, Acceldata. “With this integration, Acceldata Data Observability Cloud offers customers an added layer of cost intelligence to help detect and decrease inefficiencies to optimize performance and maximize their Databricks investment.”

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