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Every digital interaction generates data. This data can provide invaluable insights and drive effective decision-making when managed effectively. However, according to a survey, up to 68% of data within an enterprise remains unused, representing an untapped resource for driving business growth….

What is a data quality framework? A data quality framework is a set of guidelines that enable you to measure, improve, and maintain the quality of data in your organization. The goal is to ensure that organizational data meets specific…

Generative AI has had a transformative impact across numerous sectors and industries — and data management is no exception. The full extent of GenAI’s implications for data governance is yet to be determined. Areas such as data access, extraction, and…

Data completeness plays a pivotal role in the accuracy and reliability of insights derived from data, that ultimately guide strategic decision-making. This term encompasses having all the data, ensuring access to the right data in its entirety, to avoid biased…

Working with large volumes of data requires effective data management practices and tools, and two of the frequently used processes are data ingestion and ETL . Given the similarities between these two processes, non-technical people seek to understand what makes…