Data Analytics:-

  • Data Analytics is defined as the process of investigation of datasets to pull out the conclusions about the information they contain.
  • Data analytic is a method to enable you to take raw data and expose design to get valuable comprehension from it.
  • Data Analytics give ideas to individuals and organizations for making sense of data.
  • They use many different tools and methods that helps organizations to make decisions and succeed.

Types of Data Analytics:

  1. Descriptive data analytics
  2. Diagnostic data analytics
  3. Predictive data analytics
  4. Prescriptive data analytics

Tools used by Data Analyst:

  1. Statistical analysis tools.
  2. General-purpose programming languages.
  3. Standalone predictive analytics tools
  4. Data modeling tools
  5. ETL tools
  6. SQL consoles

From this book you will learn these topics in detail:

  • Data science with their relationship
  • Data science workflow
  • A plot generated by matplotliblity
  • How to measure the distance between points A and B
  • The curse of dimensionality
  • Data Clustering
  • Algorithms and applications
  • Data Mining
  • Data mining in marketing
  • Data Science and Analytics With Python
  • Healthcare data analytics
  • Technologies for Web applications
  • Machine learning engineering system and health management
  • Music Data mining
  • Data Mining use cases with business analytics applications
  • Relational data clustering
  • Vector machines
  • Text mining classifications
  • Clustering and applications of text mining
  • Visualization of text mining
  • Algorithm of text mining

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