Improve data quality, reliability, and performance
Data observability empowers data practitioners with insights to improve data quality, reliability, performance, and efficiency
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Leverage a rich set of analytics to simplify and automate data engineering tasks
Data Quality Automation: Use data profiling, recommendations, and automation to quickly establish data quality policies without writing code.
Scale Data Reliability: Leverage templates, tagging, and applying policies in bulk to scale out data reliability efforts and coverage.
Continuous Monitoring: Use comprehensive dashboards, detailed insights, and real-time alerts to fix incidents swiftly and prevent future outages.
Predict and prevent data reliability and performance incidents
Monitoring: Monitor and track data health to ensure issues are identified and addressed rapidly. Simplify root cause analysis with insights that correlate metrics across data, pipelines, infrastructure, and user layers.
Prediction: Spot early warning signs of future incidents with trending analysis, allowing adjustments to be made before service levels are impacted.
Prevention: Use workload analysis, recommendations, and simulations to ensure your platforms are always right-sized to meet requirements to prevent data issues.
Reduce and align costs with insights into resource utilization patterns and spend
Best Practices: Simplify administration and establish consistent best practices with cost dashboards, utilization anomaly detection, and configuration recommendations.
Identification Inefficiencies: Reduce costs without sacrificing performance with automatic detection of resource inefficiencies and other consumption anomalies.
Spend Confidently: Plan and optimize spend by analyzing consumption in detail, monitoring usage, and placing guardrails to prevent runaway use and cost.
What Acceldata data practitioner customers are saying
Burzin Engineer, Founder & Chief Reliability Officer, PhonePe
"Acceldata supports our hyper-growth and helps us manage one of the world’s largest instant payment systems. PhonePe’s biggest-ever data infrastructure initiative would never have been possible without Acceldata."
Ashwin Prakash, PubMatic Data Analytics Engineering Leader
"Acceldata provided the data observability tools and expertise to improve our data pipeline reliability. They helped us optimize HDFS performance, consolidate Kafka clusters, and reduce cost per ad impression, which is one of the most critical performance metrics.”
Wanlapa Linlawan, Head of Analytics Platform, True Corporation
"Acceldata’s tools fixed our analytics pipeline issues, improved visibility into our data systems, and recommended ways to scale and optimize our systems to meet future requirements. They helped True Corporation transition to open-source technologies, allowing us to reduce licensing costs, while delivering mission-critical analytics across the enterprise.”
Ready to start your data observability journey?
Start a free trial or request a demo to begin your
data observability journey.
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