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$0.12 per hour + Actual Cost of your chosen runtime.
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$0.2 per hour of compute + Cost of your chosen runtime
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$0.1 per hour
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$6,999/month
upto 250 users + $14.99
each additional
Free
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$0.12 per hour + Actual Cost of your chosen runtime.
$9,999 for upto 100 users + $99.99 each additional
Free
Free
$ 0.2 per hour of compute + Cost of your chosen runtime
Free
$0.1 per hour
Free
$3000 for upto 1000 jobs/pipelines + $2.99 each Additional
$4.99 per job/pipeline per Month
Enterprise
$14,999/month
upto 1000 users + $9.99
each additional
Free
Free
$0.12 per hour + Actual Cost of your chosen runtime.
$19,999 for upto 250 users + $79.99 each additional
Free
Free
$ 0.2 per hour of compute + Cost of your chosen runtime
Free
$0.1 per hour
Free
$6000 for upto 3000 jobs/pipelines or $1.99 each Additional
$4.99 per job/pipeline per Month
Trial
Free
Professional
$6,999/month
Platform Capability
Data Catalog, Lineage, Governance
Users
Enterprise Catalog
Source Support
Static Lineage
Code Lineage
Data Quality & Trust Index
Data Policies
Data Governance
upto 250 users + $14.99 each additional
Platform Capability
Data Engineering ETL & ELT (Pipeline & Workflows)
Design Studio
Pipeline Design
Job Run
Free
Free
$0.12 per hour + Actual Cost of chosen runtime.
Platform Capability
Data Models (AI & ML)
Design Studio
Model Design (AI & ML)
ML Flow Dashboards
Experiments & Model Run
$9,999 for upto 100 users + $99.99 each additional
Free
Free
$ 0.2 per hour of compute + Cost of your chosen runtime
Platform Capability
Scheduler (Airflow)
Design Studio
Job Scheduling
Free
$0.1 per hour
Platform Capability
Operations & Observability
Dashboard
SMS, Email & Slack Alerts (Package)
SMS, Email & Slack Alerts (A la Carte)
Free
$3000 for upto 1000 jobs/pipelines + $2.99 each Additional
$4.99 per job/pipeline per Month
Enterprise
$14,999/month
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Industry leaders are choosing NuoData
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Modernizing Financial Reporting for a Global Bank
Outcomes:
Successfully converted 95% of MS-SQL stored procedures to Spark SQL automatically
Reduced report generation time by 70%, from hours to minutes
Increased data processing capacity by 5x without significant cost increase
Improved data freshness, with updates now available hourly instead of daily
Achieved 40% reduction in overall IT infrastructure costs
Boosting sales with AI-driven customer insights.
Outcomes:
Identified high-value customer segments, increasing campaign ROI by 40%
Boosted sales in targeted regions by 25% through tailored marketing offers
Reduced data preparation and analysis time by 60%, enabling quicker decision-making
Reducing fraudulent claims and operational costs with AI
Outcomes:
Reduced fraudulent claims by 35%, saving over $2M annually
Cut down claims review time by 50%, accelerating payouts for genuine claims
Improved operational efficiency, freeing up fraud investigation teams for higher-value tasks
Enhancing Data Discovery and Governance for a Big Credit Card Company
Outcomes:
Reduced time spent searching for relevant data by 70%.
Enhanced data context and understanding across the organization.
Increased collaboration between technical and non-technical users.
Streamlined data operations with a single source of truth for all data assets.
Implementing Efficient and Collaborative Data Quality Management for a Retail Giant
Outcomes:
Reduced time to create and run data validations by 80% (from hours to minutes)
Democratized data quality management, involving both technical and business users
Improved debugging and resolution of data quality issues through centralized metadata and lineage information.
Decreased number of data quality incidents by 40% within six months
Cost savings by eliminating the need for separate data quality tools
Modernizing Financial Reporting for a Multi-National Corporation
Outcomes:
Reduced monthly financial close process from 10 days to 3 days
Improved data quality, with a 95% reduction in data discrepancies
Automated 80% of data transformation tasks, reducing manual effort by 60%
Achieved compliance with regulatory reporting deadlines, avoiding potential fines
Enabled self-service analytics for finance teams, reducing IT dependency by 70%
Streamlining E-commerce Data Integration for Real-Time Analytics
Outcomes:
Reduced data integration time by 75%, from 2 weeks to 3 days
Increased data freshness, with updates now available every 15 minutes instead of daily
Achieved 99.9% data accuracy, eliminating manual errors
Saved 30 hours per week of engineering time previously spent on maintaining data pipelines
Enabled real-time inventory management, reducing stockouts by 40%
Modernizing Legacy ETL Processes for a Financial Services Firm
Outcomes:
Automated migration of 85% of existing PowerCenter mappings to Databricks
Reduced migration time by 80%, from an estimated 12 months to 2.5 months
Lowered operational costs by 60% through cloud-based scalability and reduced maintenance
Improved data processing speed by 3x due to Databricks' distributed computing capabilities
Modernizing Financial Reporting for a Global Bank
Outcomes:
Successfully converted 95% of MS-SQL stored procedures to Spark SQL automatically
Reduced report generation time by 70%, from hours to minutes
Increased data processing capacity by 5x without significant cost increase
Improved data freshness, with updates now available hourly instead of daily
Achieved 40% reduction in overall IT infrastructure costs
Boosting sales with AI-driven customer insights.
Outcomes:
Identified high-value customer segments, increasing campaign ROI by 40%
Boosted sales in targeted regions by 25% through tailored marketing offers
Reduced data preparation and analysis time by 60%, enabling quicker decision-making
Reducing fraudulent claims and operational costs with AI
Outcomes:
Reduced fraudulent claims by 35%, saving over $2M annually
Cut down claims review time by 50%, accelerating payouts for genuine claims
Improved operational efficiency, freeing up fraud investigation teams for higher-value tasks
Enhancing Data Discovery and Governance for a Big Credit Card Company
Outcomes:
Reduced time spent searching for relevant data by 70%.
Enhanced data context and understanding across the organization.
Increased collaboration between technical and non-technical users.
Streamlined data operations with a single source of truth for all data assets.
Implementing Efficient and Collaborative Data Quality Management for a Retail Giant
Outcomes:
Reduced time to create and run data validations by 80% (from hours to minutes)
Democratized data quality management, involving both technical and business users
Improved debugging and resolution of data quality issues through centralized metadata and lineage information.
Decreased number of data quality incidents by 40% within six months
Cost savings by eliminating the need for separate data quality tools
Modernizing Financial Reporting for a Multi-National Corporation
Outcomes:
Reduced monthly financial close process from 10 days to 3 days
Improved data quality, with a 95% reduction in data discrepancies
Automated 80% of data transformation tasks, reducing manual effort by 60%
Achieved compliance with regulatory reporting deadlines, avoiding potential fines
Enabled self-service analytics for finance teams, reducing IT dependency by 70%
Streamlining E-commerce Data Integration for Real-Time Analytics
Outcomes:
Reduced data integration time by 75%, from 2 weeks to 3 days
Increased data freshness, with updates now available every 15 minutes instead of daily
Achieved 99.9% data accuracy, eliminating manual errors
Saved 30 hours per week of engineering time previously spent on maintaining data pipelines
Enabled real-time inventory management, reducing stockouts by 40%
Modernizing Legacy ETL Processes for a Financial Services Firm
Outcomes:
Automated migration of 85% of existing PowerCenter mappings to Databricks
Reduced migration time by 80%, from an estimated 12 months to 2.5 months
Lowered operational costs by 60% through cloud-based scalability and reduced maintenance
Improved data processing speed by 3x due to Databricks' distributed computing capabilities
Modernizing Financial Reporting for a Global Bank
Outcomes:
Successfully converted 95% of MS-SQL stored procedures to Spark SQL automatically
Reduced report generation time by 70%, from hours to minutes
Increased data processing capacity by 5x without significant cost increase
Improved data freshness, with updates now available hourly instead of daily
Achieved 40% reduction in overall IT infrastructure costs
Boosting sales with AI-driven customer insights.
Outcomes:
Identified high-value customer segments, increasing campaign ROI by 40%
Boosted sales in targeted regions by 25% through tailored marketing offers
Reduced data preparation and analysis time by 60%, enabling quicker decision-making
Reducing fraudulent claims and operational costs with AI
Outcomes:
Reduced fraudulent claims by 35%, saving over $2M annually
Cut down claims review time by 50%, accelerating payouts for genuine claims
Improved operational efficiency, freeing up fraud investigation teams for higher-value tasks
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