For Data PRACTITIONERS

Improve data quality, reliability, and performance

Data observability empowers data practitioners with insights to improve data quality, reliability, performance, and efficiency

Accelerate Development

Leverage a rich set of analytics to simplify and automate data engineering tasks throughout the development lifecycle

  • Design: Optimize solution design the first time by easily comparing data and technologies to deliver solutions with the best quality, performance, and cost metrics.

  • Development: Quickly search, explore and validate data sets and let Acceldata automatically generate data quality rules for monitoring post-production.

  • Deployment: Simplify tuning for scale with bottleneck analysis, configuration recommendations, and a simulator to ensure performance meets requirements.

Prevent Incidents

Site reliability engineers can predict and prevent performance, reliability and quality incidents with comprehensive monitoring, analytics, and automation

  • Monitoring: Track the health of data and processing with anomaly detection and alerts to ensure issues are identified as quickly as possible. Simplify root cause analysis with insights that correlate metrics across multiple layers, including data, processing, platform and infrastructure.

  • Prediction: Spot early warning signs of future incidents with trending analysis, allowing adjustments to be made before service levels are impacted.

  • Prevention: Configure systems to be self-tuning and self-healing with an auto-action framework that includes dozens of runbooks and extension points for custom routines.

Improve Resource Efficiency

Architects and administrators can reduce costs and align to data strategy with insights into utilization patterns, configuration, and spend

  • Best Practices: Simplify administration and ensure best practices are in place with cost intelligence dashboards, anomaly detection, configuration recommendations, and many other environment analytics.

  • Identification of Waste: Lower costs without sacrificing performance with automatic detection of resource inefficiencies such as unused data & services, over or
    under-sized deployments, configuration mismatches, and other anomalies.

  • Spend Intelligence: Budget owners can efficiently plan and optimize spend by analyzing current and forecasted consumption at a department-level. Monitoring and analysis of usage limit guardrails prevent runaway consumption
    and costs.

What Acceldata 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."
Read the Case Study

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.”
Read the Case Study

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.”
Read the Case Study

Ready to start your data observability journey?

Start a free trial or request a demo to begin your
data observability journey.