Data analytics is the process of collecting, organizing, and analyzing data to extract valuable insights. It helps businesses and organizations make informed decisions, predict trends, and optimize operations.
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Data analytics is the process of collecting, organizing, and analyzing data to extract valuable insights. It helps businesses and organizations make informed decisions, predict trends, and optimize operations.
There are four main types:
Descriptive Analytics – Summarizes past data to identify trends.
Diagnostic Analytics – Analyzes data to determine why something happened.
Predictive Analytics – Uses historical data to forecast future trends.
Prescriptive Analytics – Suggests the best course of action based on data insights.
Some of the most popular tools include:
Programming languages: Python, R, SQL
Visualization tools: Tableau, Power BI
Big Data platforms: Apache Hadoop, Spark
Cloud services: AWS, Google Cloud, Microsoft Azure
Big Data refers to extremely large datasets that traditional data processing methods cannot handle efficiently. Data analytics tools and techniques help process, analyze, and extract insights from Big Data, enabling businesses to make data-driven decisions.
Machine learning automates the analysis process by identifying patterns and making predictions based on historical data. It improves decision-making by providing real-time recommendations, detecting anomalies, and enabling predictive analytics.