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Summary : This article equips DataAnalysts with a solid foundation of key Data Science terms, from A to Z. Introduction In the rapidly evolving field of Data Science, understanding key terminology is crucial for DataAnalysts to communicate effectively, collaborate effectively, and drive data-driven projects.
The following figure represents the life cycle of data science. It starts with gathering the business requirements and relevant data. Once the data is acquired, it is maintained by performing datacleaning, data warehousing, data staging, and data architecture. What is Cross-Validation?
Here, we’ll explore why Data Science is indispensable in today’s world. Understanding Data Science At its core, Data Science is all about transforming raw data into actionable information. It includes data collection, datacleaning, data analysis, and interpretation.
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