Leveraging AI and ML to improve data quality
In today's world, the constant influx of data from various sources makes it nearly impossible for data to be completely error-free. Just about anyone can generate and share data, the danger of putting out 'bad' data is on the increase, making it essential to check, and double-check work data, especially when its origin is questionable.
Furthermore, organisations are spending on deriving insights without any consensus on definition of data quality and no systematic way to sustain high quality data which results in high operational cost and challenges with integration, metadata, curation, governance and master data management issues.
Data Scientists are spending 80% of their effort on data engineering and data preparation challenges versus focusing on model optimisation and algorithms.
As part of this webinar, we shall discuss and see a demo of DQLabs.ai about how we can leverage artificial intelligence and machine learning to combine processes, technologies to improve, monitor data quality and prepare 'ready-to-use' data.
You can sign up for the webinar here.
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