Data error is data-cancer. Hard to detect and spreads fast Detect data errors early and autonomously with AI/ML
Trusted data, without coding
Autonomous Data Monitoring for Cloud and Lake
Data Warehouses, Lakes and Clouds are notoriously error prone. The process of validating their Data Quality (DQ) is laborious manual work and is far from satisfactory. Unfortunately, >95% of your data is dark data – unmonitored, unvalidated and unreliable. Every step it moves downstream, errors get exponentially compounded. It takes 10x cost to fix it, if you can detect it all. What you don’t detect is unmitigated business risk.
When is DataBuck powerful?
Current data monitoring and validation tools and processes fare very poorly under these conditions listed below, and DataBuck is perfect for these:
- Cloud/Lake use
- Dynamic data, for example, operational and transactional data
- High volume of data
- New sources or changing structures of data
- Data is being used for purposes it was not intended for when it was collected? (New uses for data)
What Is DataBuck?
Data errors due to “Systems Risks” are the biggest contributors to untrustworthy data. As ETL jobs move data around, errors creep in and steadily multiply like cancer across an enterprise. For every step the error spreads, it takes 10x more cost and effort to fix it.
DataBuck is an autonomous data quality validation s/w. It automatically detects 100% of all Systems Risks with minimal human intervention using AI/ML. It automatically sets 1,000s of validation checks and their thresholds. It is >10x faster than any other tool or your own custom scripts. AI/ML enables the tool to be set up and validate entire databases or schemas in just a few clicks.
Customer’s report benefits of:
(i) Higher trust in reports, analytics & models
(ii) Lower data maintenance work & cost
(iii) 10x efficiency in scaling Data Quality ops
People productivity
boost >80%
Reduction in unexpected errors: 70%
Cost reduction >50%
Time reduction to onboard data set ~90%
Increase in processing speed >10x
Cloud native
Simplify Data Quality Monitoring and Data Quality Validation with DataBuck
Gartner Cool Vendor Award for Data Validation & Data Quality
An innovative tool that Gartner has recognized has the potential to change the big Data landscape. Big Data Quality Validation and Data Matching is done autonomously and effortlessly by Machine Learning algorithms that learn the expected behavior of data without manual intervention. Without coding, Data Quality deviations are picked out.
IDC Innovator Award in
Data Quality
AI/ML-powered Data Quality validation tool, DataBuck, was recognized by IDC for innovative solution in the DQ space. DataBuck’s AI/ML-powered business rule discovery automates a tedious, labor intensive and time consuming process for validating Data Quality from 6-9 months to just a few days.
Machine Learning-Guided Cloud and Lake Data Monitoring and Validation Tool
DataBuck can validate your Big Data autonomously and at 10x speed of any other data validation tool or your own custom scripts. Clean data in 3 clicks and no-coding.
Privacy of our customers is important to us, a sample of a few organizations that trust DataBuck
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Financial Services
• Top-3 US Bank
• Top-3 African bank
• Top-3 Middle Eastern bank
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Healthcare
• Top-10 US Hospital
• Top Telehealth provider
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Hi Tech
• Fortune-50 Hi Tech manufacturer
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Retail
Top-3 Retail IoT services provider
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Streaming
• Top-3 Streaming music service
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Government
• 3rd largest city is US
Privacy of our customers is important to us, a sample of a few organizations that trust DataBuck
-
Financial Services
• Top-3 US Bank
• Top-3 African bank
-
Healthcare
• Top-10 US Hospital
• Top Telehealth provider
-
Hi Tech
• Fortune-50 Hi Tech manufacturer
-
Retail
Top-3 Retail IoT services provider
-
Streaming
• Top-3 Streaming music service
-
Government
• 3rd largest city is US