Stop runaway consumption. Maximize ROI on Databricks spend

Maintain continuous control over your Databricks lakehouse, underutilized clusters, inefficient workflows and jobs, DLTs, SQL warehouses, notebooks and runaway queries.

Forecast your future spend with 96-98% accuracy.

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TRUSTED BY ENTERPRISE DATA TEAMS WORLDWIDE

Timothy C.

Senior Expert of Data Governance - Enterprise

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.

Acceldata User

Small - Business

It helped to improve data and pipeline reliability and cost-optimization.
‍

Be efficient in fine-tuning, support, and maintenance tasks

For data-driven enterprises operating at Petabyte scale, Acceldata Enterprise Data Observability is the only viable choice today!

Stop

runaway consumption and cost spikes with timely alerts

Trace

why & who of cost overruns with 65% faster MTTR

Forecast

data and compute budgets with 97% accuracy

X-ray Databricks account usage, Optimize ROI with precise tips.

Try Acceldata free for 30 days

Identify wasted spend in 30 minutes

Connect your data sources or use sample demo data

Guided experiences and email/phone assistance

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Reduce runaway consumption with Acceldata

For Finops Teams

Reduce infrastructure costs by 20% in first 2 weeks

75% decrease in downtime per incident and anticipate cost spikes using anomaly detection and root cause analysis with multidimensional utilization drilldowns and accurate chargebacks

Prevent incidents and inefficient resource utilization and wastage with a cost-aware culture across teams using automated thresholds and remediation with contextual reporting, timely alerts, automated recommendations, and detailed RCA

Analyze current contract plans and budgets, and create 96-98% accurate spend forecasts and cost allocations using department/project level chargeback and AI-driven budgeting

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Improve Data Ops & infrastructure with Acceldata

For Platform Teams

Operational health checks to improve Data Ops & infrastructure

Switch from batch or periodic sprints to continuous, automated, real-time monitoring and optimization of resources: underutilized clusters, workflows, DLT pipelines, job runs, notebooks and queries.

Stretch your Databricks DBUs and avoid runaway consumption. Enforce guardrails and stay abreast of latest best practices via automated codification into your data observability solution

75% fewer performance-related incidents, and reduce time spent on finetuning, support and maintenance with continuously-ON monitoring, RCA, automated remediation with recommendations, alerts and notifications

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For Platform & data Teams

360^o view into Databricks spend and infrastructure utilization

Continuous, granular visibility into spend and workload utilization through dashboards, resource monitors, trends, and contextual drilldowns pinpointing to root causes of issues and ownership

Awareness of feature utilization, overspend, suboptimal queries, and overprovisioning - through usage information across entities such as clusters, workflows, job runs, queries & notebooks, with insights into chargeback by org, BUs, teams, projects, and users.

Loop in the right team members at the right time with relevant reports directly inboxed to you and with timely alerts and notifications through multiple channels: Slack, email, ServiceNow tickets, MS Teams, Jira, and others.

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Struggling with Pipeline Reliability in Databricks?

Ensure trusted data, accelerate insights, and pipeline visibility across your Databricks environment.

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Metrics

Speed up migration to Databricks Lakehouse

Acceldata’s capabilities such as data drift, schema drift, reconciliation help speed migration to Databricks. Migrate thousands of pipelines across hundreds of sources with ease.

15%

faster migrations and faster time-to-delivery

20%

faster load time and 10% faster query runtime within 2 weeks

20%

productivity improvement in admin and support within a month

10%

productivity improvement in data engineering within a month

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Empower data engineers with self-service workload optimization

Cluster and Compute Rightsizing

Optimize the size and performance of your Databricks lakehouse and clusters

Table optimization

Optimize data layouts such as tables and clusters

Cluster and Compute Rightsizing

Optimize jobs run as well as query structure and performance

MAXIMIZE DATA QUALITY AND ELIMINATE DATA OUTAGES

A single pane of glass across your data environment

Continuously ensure reliability of data and pipelines across your data landscape, in addition to cost and operational optimization

Data Quality Policies and Anomaly Detection

Ensure the reliability and timeliness of data across your data landscape with Acceldata’s continuous and automated data quality monitoring platform.

Leverage anomaly detection and a flexible and highly scalable framework with policies for all the 6 Dimensions of Data Quality (accuracy, completeness, consistency, freshness, validity and uniqueness), data reconciliation, schema drift, and data drift.

Data Pipeline Observability

Gain end-to-end visibility and insights into your data assets and pipelines from start to finish to ensure data gets delivered properly and on-time.

Eliminate operational blindspots and clogged, slow, inefficient or stopped pipelines by continuously observing pipelines such as Kafka and Airflow.

Shift Left and the “1 x 10 x 100 Rule” of Data Quality

Detect problems at the beginning of your data landscape to isolate issues before they hit your Databricks Lakehouse or before they affect downstream analytics and consumption.

Implement the “1 x 10 x 100 Rule” of Data Quality that states that the cost of fixing a problem increases exponentially as you move from the source or ingestion zone to the consumption zone or Databricks Lakehouse, where it finally lands up

Observability Into All Data Across Your Landscape

Get visibility into all your data in Databricks and across your entire data stack: data-at-rest, data-in-motion, and data-for-consumption.

Trace transformation failures and data inaccuracy across tables and columns with detailed data lineage and by pinpointing the exact root cause.

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Explore all the ways to experience Acceldata for yourself.

Expert-led Demos

Get a technical demo with live Q&A from a skilled professional.

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Experience the power
of Data Observability firsthand.

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Meet with Us

Let our experts help you achieve your data observability goals.

Stop runaway consumption. Maximize ROI on Databricks spend

Users Love Us

Timothy C.

Acceldata User

Be efficient in fine-tuning, support, and maintenance tasks

Stop

Trace

Forecast

X-ray Databricks account usage, Optimize ROI with precise tips.

Try Acceldata free for 30 days

Reduce infrastructure costs by 20% in first 2 weeks

Operational health checks to improve Data Ops & infrastructure

360o view into Databricks spend and infrastructure utilization

Struggling with Pipeline Reliability in Databricks?

Speed up migration to Databricks Lakehouse

Empower data engineers with self-service workload optimization

Cluster and Compute Rightsizing

Table optimization

Cluster and Compute Rightsizing

A single pane of glass across your data environment

Data Quality Policies and Anomaly Detection

Data Pipeline Observability

Shift Left and the “1 x 10 x 100 Rule” of Data Quality

Observability Into All Data Across Your Landscape

Ready to get started

Expert-led Demos

30-Day Free Trial

Meet with Us

360^o view into Databricks spend and infrastructure utilization