Introduction of Big Data and Analytics

1. Dr. Sanjeev Kumar

2. • Big Data
Big data is a term that describes the large volume
of data – both structured and unstructured – that
inundates a business on a day-to-day basis.
• Key Aspects of Big Data
• Volume (Terabytes, Records, Transaction, Tables, Files)
• Variety ( Structured, Unstructured, Semi structured)
• Velocity ( Batch, Near Time, Real Time, Streams)
BIG DATA

3. WHY BIG DATA IMPORTANT
 Making Good Use of the Data.
 Benefit From Speed, Capacity and Scalability of Cloud Storage.
 Data Visualization
 Organization Can Find New Business Opportunities.

4. Big Data can lead to efficiency improvements, increased
sales, lower costs, better customer service, and/or improved
products and services.
Using information technology (IT) logs to improve IT
troubleshooting and security breach detection, speed,
effectiveness, and future occurrence prevention.
Cont...

5. BIG DATAANALYTICS

6. SOFTWARE USED IN BIG DATA
 Hadoop
 Open source, Java-based programming framework
 Design Clusters
 Map Reduce
 Powerful Model for Parallelism
 Based on Rigid Procedural Structure
 Pig
 Procedural Data-Flow Language
 Used by Programmers and Researchers.
 Hive
 Declarative SQLish Language
 Used by Analysts for Generating Reports.

7. CHALLENGES OF BIG DATA
 Finding the Signal in the Noise
 Data Silos
 Inaccurate Data
 Technology Moves Too Fast
 Lack of Skilled Workers

8. FUNCTIONS OF BIG DATA
 Get Value From Data
 Data Integration Key
 Clean and Maintain Data
 Remove Duplicates
 Verify New Data
 Update Data
 Implement Consistent Data
Entry

9. APPLICATION AREAS OF BIG DATA

10. FUTURE SCOPE OF BIG DATA
 The Connectivity Internet in the Cloud Raises a Range of
Privacy and Security Concerns.
 On the Technical Front, New Algorithms and Methods are
Needed to Cope With Time-Varying Network Latency and
Quality-of-Service.
 New Algorithms are Also Needed that Scale
to the Size of Big Data, Which Often Contain
Dirty Data that Requires New Approaches
to Clean Effectively.

11. CONCLUSIONS
Big data allows organizations to create
highly specific segmentations and to
tailor products and services precisely to
meet those needs.
This approach is well-known in
marketing and risk management but can
be revolutionary elsewhere.