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AI for Data Observability With Enterprise Guardrails

Latest AI technology helps improve data observability outcomes

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AI for Data Observability with Acceldata
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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.
Acceldata AI

Leverage the Power of AI to Improve Data Observability

Acceldata’s technology provides enterprises with the ability to tailor the use of AI for Data Observability to their unique technical environment and business scenarios. This includes providing the means to control how AI capabilities are applied at an individual asset level, with desired guardrails that ensure that business context, regulatory requirements, and the proper balance of human oversight with AI autonomy are taken into consideration.

Anomaly detection

Improve data reliability by studying and alerting on anomalies in data freshness, data profiling, and data quality changes, ensuring the trustworthiness of data.

Cost control & forecasting

Auto-learn cost consumption patterns, including seasonality, and alert users to prevent runaway consumption. Forecast consumption based on learned behavior.

Rule and policy application automation

Leverage generative AI and large language models (LLMs) to streamline bulk policy creation. Easing effort and preventing errors and omissions due to human oversight.

Data asset description generation

Automatically generate human readable descriptions for data assets, policies, and rules to facilitate seamless communication between the technical and business owners of data assets.
Compute & Query Observability with Acceldata

Anomaly detection

 Improve data reliability by studying and alerting on anomalies in data freshness, data profiling, and data quality changes, ensuring the trustworthiness of data.

Cost control & forecasting

Auto-learn cost consumption patterns, including seasonality, and alert users to prevent runaway consumption. Forecast consumption based on learned behavior.

Data asset description generation

Automatically generate human readable descriptions for data assets, policies, and rules to facilitate seamless communication between the technical and business owners of data assets.
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