What is Big Data Analytics?

What is Big Data Analytics?

Big data analytics refers to the systematic processing and analysis of large amounts of data and complex data sets, known as big data, to extract valuable insights. Here are some key points:

  1. Data Exploration: Big data analytics allows organizations to uncover trends, patterns, and correlations in raw data. By analyzing diverse sources such as IoT sensors, social media, financial transactions, and smart devices, analysts make data-informed decisions.
  2. Advanced Techniques: It involves techniques like data mining, statistical analysis, and predictive modeling. These methods help transform raw data into actionable intelligence.
  3. Frameworks and Tools: Big data frameworks (e.g., Hadoop) enable distributed storage and processing across a network of computers. These frameworks handle structured, semi-structured, and unstructured data.
  4. Types of Analytics:

  • Descriptive: Understand historical data and summarize it.
  • Diagnostic: Identify reasons behind past events.
  • Predictive: Forecast future outcomes using statistical models.
  • Prescriptive: Suggest optimal actions based on data

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