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Big data refers to extremely large sets of structured, semi-structured, or unstructured data that require advanced computing tools and techniques to process, manage, and analyze. It typically involves data from various sources and in different formats, including social media, transaction records, sensor data, and more. The analysis of big data can provide valuable insights and opportunities for businesses, organizations, and researchers.
Data warehousing is the process of collecting, storing, and managing large volumes of data from various sources in a centralized repository. It involves extracting data from different sources, transforming it into a consistent format, and loading it into a data warehouse. Data warehousing enables businesses to analyze data and derive insights to support decision-making processes. The data warehouse is designed to facilitate business intelligence activities, such as reporting, data mining, and data analysis.
Data analytics is the process of examining, cleaning, transforming, and modeling data to derive insights and support decision-making processes. It involves using statistical and computational methods to uncover patterns, trends, and relationships in data. The goal of data analytics is to turn data into meaningful and actionable insights that can be used to optimize business operations and drive innovation.