A/B testing (or split testing) is one of the most powerful tools in an analyst’s toolbox: it allows you to compare two (or more) versions of a web page, feature, or user experience — and determine which version truly performs better.
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When building data-driven solutions — whether dashboards, reports, or analytical pipelines — you often focus on selecting, transforming, or visualizing data. But to make all that work, you need a well-structured database behind the scenes. That’s where Data Definition Language (DDL) comes in.
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JSON (JavaScript Object Notation) has become the universal language for exchanging data between applications. Whether you’re pulling data from APIs, storing logs, or dealing with semi-structured data in a data lake — JSON is everywhere.
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Have you ever imported a dataset into Tableau, Power BI, Looker Studio, or Qlik Sense—only to find that several identical rows suddenly appear as one?
If so, you’ve likely encountered BI tool data deduplication, a fundamental behavior across nearly all modern Business Intelligence platforms.
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