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Sri Raghavendra Educational Institutions Society (R)

(Approved by AICTE, Accredited by NAAC, Affiliated to VTU, Karnataka)

Sri Krishna Institute of Technology

www.skit.org.in

Title: Why is Big Data Analytics Important?

CO addressed: CO1

Course: Big Data Analytics

Presented by: Mr. P. Kiran Kumar

Department: ISE

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/skit.org.in

(Approved by AICTE, Accredited by NAAC, Affiliated to VTU, Karnataka)

Sri Krishna Institute of Technology

Why is Big Data Analytics Important?

Big Data Analytics is important because it enables organizations to process massive volumes of structured and unstructured data, discover hidden patterns, predict future outcomes, and make faster, data-driven decisions.

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1. Reactive – Business Intelligence (BI)

2. Reactive – Big Data Analytics

3. Proactive Analytics

4. Proactive – Big Data Analytics

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/skit.org.in

(Approved by AICTE, Accredited by NAAC, Affiliated to VTU, Karnataka)

Sri Krishna Institute of Technology

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1. Reactive – Business Intelligence (BI)

Focus: What happened?

  • Uses historical data stored in data warehouses.
  • Generates reports, dashboards, charts, and KPIs.
  • Helps managers monitor business performance.
  • Supports predefined reports and ad hoc queries.
  • Decision-making is based on past events.

Examples:

  • Monthly sales reports
  • Employee attendance dashboard
  • Annual profit analysis

Limitation:

  • Only explains past performance.
  • Cannot predict future trends.

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/skit.org.in

(Approved by AICTE, Accredited by NAAC, Affiliated to VTU, Karnataka)

Sri Krishna Institute of Technology

2. Reactive – Big Data Analytics

Focus: What happened in very large datasets?

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  • Analyzes huge volumes of data (TBs or PBs).
  • Uses technologies such as Hadoop and Spark.
  • Processes structured, semi-structured, and unstructured data.
  • Can analyze logs, social media posts, clickstreams, sensor data, etc.
  • Still reactive because it mainly analyzes existing data.

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Examples:

  • Analyzing billions of website clicks
  • Examining customer reviews from social media
  • Processing server log files

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Advantage over BI:

  • Handles much larger and more diverse datasets.

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/skit.org.in

(Approved by AICTE, Accredited by NAAC, Affiliated to VTU, Karnataka)

Sri Krishna Institute of Technology

3. Proactive Analytics

Focus: What is likely to happen?

Uses advanced analytical techniques such as:

  • Predictive analytics
  • Machine learning
  • Data mining
  • Statistical analysis
  • Text mining

These techniques forecast future events instead of only analyzing the past.

Examples:

  • Predicting customer churn
  • Forecasting sales
  • Detecting credit card fraud
  • Predicting equipment failure

Limitation:

  • Traditional databases struggle with very large datasets.
  • Limited scalability and slower processing.

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/skit.org.in

(Approved by AICTE, Accredited by NAAC, Affiliated to VTU, Karnataka)

Sri Krishna Institute of Technology

4. Proactive – Big Data Analytics

Focus: What will happen, and what should we do?

This is the most advanced stage.

It combines:

  • Big Data technologies
  • Artificial Intelligence
  • Machine Learning
  • Real-time analytics
  • High-performance computing

Capabilities:

  • Real-time decision making
  • Predictive and prescriptive analytics
  • Detect hidden patterns
  • Personalized recommendations
  • Automated intelligent decisions

Examples:

Netflix recommending movies instantly, Amazon product recommendations

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