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Acceldata has opened quite a few doors for us at Nestle. We have started with the Data Reliability features of the product and moved into the Cloud/Cost Optimization aspects.
Chidambararajan M.
IT Consultant - Enterprise
Acceldata is giving the better quality checks for the data sources and the maintenance of the environment is good.
Aman C.
Data Quality Engineer - Enterprise
Acceldata is reducing more of the human effort that the sustain team was putting where we can have the notifications if the DQ jobs and recon jobs fail.
Ankit B.
Senior Technical Lead - Enterprise
We are using power of Acceldata for our data quality issues. Its integration is simple and we are able to identify various data quality issues quite easily.
Jayanth Reddy G.
Senior DevOps Engineer - Enterprise
This combination of usability, seamless integration, and robust features makes Acceldata a powerful tool for enhancing data reliability and performance.
Acceldata User
Mid-Market - (51 - 1000 emp.)
The Tool is able to provide end-end Reconciliation feature as well Data Quality feature
Your Environment
Why Go All-In?
Complex enterprises demand comprehensive solutions. If your enterprise looks like this, then Acceldata Enterprise Data Observability is the only choice today!
All Data Formats
All data types including structured, unstructured, and streaming data.
All Data Aspects
Quality, freshness, drift, operational parameters, cost, and others.
All Data Stages
Data at rest, data in motion and data for consumption.
New to Data Observability?
Download this 2-pager to quickly learn what it is, how it can help you, and why it's essential today.
Acceldata is the most complete Enterprise Data Observability solution
Cloud or on-premises, all data stacks, all data types, comprehensive integrations, petabyte scale
Shift Left
In a data pipeline, every stage inherits the problem of the previous. Shift left is the most cost-efficient path to reliable data.
Landing zone
Monitor the file cadence in your landing zone, track file freshness, file volume, alert to anomalies to catch problems at the source.
Raw zone
Improve data quality with AI based and manual rules, detect data and schema drift, alert on quality threshold breaches, quarantine bad data as per your business requirements.
Consumption zone
Optimize your warehouses and clusters, improve inefficient queries, know the most efficient users.