Data analytics is a pretty mature discipline; we’ve been using analysis and statistics to make sense of data for a very long time. In recent times, SQL-based analytics—things like calculating sums and averages over different groupings of data—have been foundational for organizational strategy and competitive edge, powering dashboards and forming the basis of KPIs (Key Performance Indicators).
Data science, now, is a newer kid on the block. What’s the difference between data science and the traditional SQL-based analytics? Who needs data science anyway?
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