Dirty Data is Costing You
If you’ve ever analysed data, you know the pain of digging into your data only to find that the data is poorly structured, full of inaccuracies, or just plain incomplete. You’re stuck adapting the data in Excel or writing complex calculations before you can answer a simple question.
Data preparation is the process of getting data ready for analysis, including data discovery, transformation, and cleaning tasks—and it’s a crucial part of the analytics workflow. A recent Harvard Business Review study reports that people spend 80% of their time prepping data, and only 20% of their time analysing it. And this statistic isn’t restricted to the role of the data stewards. Data prep tasks have bled into the work of analysts and even non-technical business users.
Data preparation is the process of getting data ready for analysis, including data discovery, transformation, and cleaning tasks—and it’s a crucial part of the analytics workflow. A recent Harvard Business Review study reports that people spend 80% of their time prepping data, and only 20% of their time analysing it. And this statistic isn’t restricted to the role of the data stewards. Data prep tasks have bled into the work of analysts and even non-technical business users.
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