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Thats where data normalization comes in. Its a structured process that organizes data to reduce redundancy and improve efficiency. Whether you’re working with relational databases, datawarehouses , or machine learning pipelines, normalization helps maintain clean, accurate, and optimized datasets. Simple, right?
These tools will help make your initial data exploration process easy. ydata-profiling GitHub | Website The primary goal of ydata-profiling is to provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution.
Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Data Visualization: Matplotlib, Seaborn, Tableau, etc.
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