Data quality management is a critical part of digital transformation, without which any Data Lake or Corporate Data Warehouse (CDS) cannot evolve and evolve effectively.
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Managing complex information systems requires high quality primary digital data. Inaccurate data leads to incorrect decisions.
Quality management allows you to control the quality of data at all stages of the life cycle of data movement - from source systems to data transfer to external systems.
Data Quality Framework is our data quality management solution that allows you to:
Keep records of data quality across all storage layers and after any transformations.
Proactively respond to any data issues before these issues appear in reports.
Visualize data quality checks in the user interface.
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The Data Quality Framework helps companies effectively manage data quality and develop Data Lake, a crucial part of digital transformation.
Monitor the quality of downloaded data on all layers of the Lake data in real time
Visualization of different data quality metrics
Automatic dispatches to managers in case of data problems
Single point of quality control throughout the data management lifecycle
Decision functions
Grafana
Python
PostgreSQL
FastAPI
Process stack
Early detection of anomalies and their timely elimination without affecting the company's business
Automated proactive detection of incorrect data
Significantly speed up the process of finding errors in data
Prompt resolution of problems with data sources (duplicates, blank records, incorrect values)
Improving Transparency of Lake Data Quality
Faster response to reporting failures
Effect of implementation
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