Data analytics typically involves several key stages, including data collection, data cleaning, data processing, and data visualization. The data collected can be structured (like spreadsheets and databases) or unstructured (like social media posts and videos). Once the data is cleaned and processed, it is analyzed using various techniques to identify trends, correlations, and outliers

By leveraging tools like business intelligence software, machine learning models, and data visualization platforms, organizations can turn raw data into actionable insights, enhancing their ability to make informed, data-driven decisions. As the volume and complexity of data continue to grow, data analytics will remain a critical tool for businesses aiming to stay competitive in an increasingly data-centric world.

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