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 A survey by found that 76% of data scientists consider data preparation their least favorite part of their job. This may be because data preparation can be a complex and time-intensive task, consuming hours, days, and sometimes even weeks of…

A clear understanding of data health enhances data quality and trustworthiness. This is where data exploration comes into play.  Data exploration provides extensive insights into the characteristics of your data. You can uncover data anomalies and learn how to address…

Знаете ли вы, что только 3% компаний имеют данные, соответствующие базовым стандартам качества? Качество данных имеет важное значение для любого бизнеса, использующего данные для анализа, принятия решений и инноваций. Однако качество данных не происходит автоматически. Это требует…

Machine Learning (ML) focuses on developing algorithms and models that enable computers to learn from and make predictions or decisions based on data. It encompasses various techniques, such as supervised learning, unsupervised learning, reinforcement learning, and more. In ML, getting…

The pursuit of accelerated business growth hinges on data-driven strategies. McKinsey suggests that companies who use consumer behavior insights strategically perform 85% better in sales growth compared to their peers. But, the traditional manual data preparation process, which often involves…