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Top Data Cleaning Techniques & Best Practices for 2024

Knowledge Hut

In the context of data science , clean data is crucial because the quality of your data directly impacts the reliability of your analysis and the outcomes of your algorithms. It's a foundational step in data preparation, setting the stage for meaningful and reliable insights and decision-making.

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20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

Source Code: Visualize Daily Wikipedia Trends with Hive, Zeppelin, and Airflow (projectpro.io) 7) Data Aggregation Data Aggregation refers to collecting data from multiple sources and drawing insightful conclusions from it. to accumulate data over a given period for better analysis.