[White Paper] The Art and science of Data Quality Engineering

Every year, poor data quality costs organizations an average $12.9 million – Gartner.

Apart from the immediate impact on revenue, over the long-term, poor-quality data increases the complexity of data ecosystems and leads to poor decision making.

Our White paper discusses data quality concisely, outlining the various concepts and techniques used to improve data quality. It also provides a comprehensive overview of modern data quality engineering, highlighting the different applications and methods that are currently in use.

Download your copy of the whitepaper to know the art and science of data quality engineering.

Understand the essentials of Data quality engineering:

  • Importance of data quality in digital world
  • Data quality engineering framework
  • Different types of data quality issues and how to fix them
  • Best practices – Data quality management
  • How Kairos makes data quality management easy and seamless

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