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Data and analytics refers to the management and study of raw data to improve decision-making, business operations, and outcomes. It’s a systematic process that extracts insights from data, enabling businesses to identify business risks, challenges, and opportunities – faster, more accurately, and with greater relevance.
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Exploratory Data Analysis (EDA) is the process of analyzing a dataset for the purpose of identifying, describing and visualizing patterns. It is one of the most important steps in data science because it helps us understand our data better and make better decisions about how to proceed with it. The main goal of EDA is to get an overview of your data using different methods such as histograms and boxplots, so that you can quickly identify any potential issues with your dataset, such as missing values or outliers. You can also use EDA to visualize your data so that you can understand it better. Read More: https://hsndigitally.com/what-is-exploratory-data-analysis-in-data-science/
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