big data v1.0

Big Data Analytics: Source of Competitive Advantage and Enabler for Blue Ocean Business Models

Suresh Arorasuresh_arora@hotmail.com

Outline

• Objectives• What Is Big Data?• Challenges with Legacy BI applications• Applications of Big Data• Business Models• Technology• Market for Big Data• Risks & Limitations of Big Data• Conclusions

Objectives• To identify ways by which Big Data can become source of

competitive advantage for businesses Shortcomings of Legacy Business Intelligence (BI) applications Identification of industries/sectors which can benefit from Big data an-

alytics

• To identify strategies to capture and create value from Big Data Business drivers for Big Data Identification of business models around Big Data

• To identify various technologies for capturing and analyz-ing Big Data Identifies different approaches to store Big Data (e.g., HDFS, Cas-

sandra, MangoDB etc. ) Big Data Platform (Apache Hadoop project)

• To identify markets for Big Data products

Outline

• Objective and Methodology• What Is Big Data?• Challenges with Legacy BI applications• Applications of Big Data• Business Models• Technology• Market for Big Data• Risks & Limitations of Big Data• Conclusions

What Is Big Data?

Big Data is a term that describes large volumes of High Velocity, Complex and Variable data that require advanced techniques and technologies to enable the Capture, Storage, Distribution, Management, and Analysis of the information

Big Data analytics is the process of examining and interrogating big data as-sets to derive insights of value for decision making

1 Kilobyte 1,000 bits/byte1 megabyte 1,000,0001 gigabyte 1,000,000,0001 terabyte 1,000,000,000,0001 petabyte 1,000,000,000,000,0001 exabyte 1,000,000,000,000,000,0001 zettabyte 1,000,000,000,000,000,000,000

Characteristics of Big Data The “BIG” in big data isn’t just about volume

How Is Big Data Different?

1) Automatically generated by a machine (e.g. Sensor embedded in an engine)

2) Typically an entirely new source of data (e.g. Use of the internet)

3) Not designed to be friendly (e.g. Text streams)

4) May not have much values– Need to focus on the important part

Outline

• Objective and Methodology• What Is Big Data?• Challenges with Legacy BI applications• Applications of Big Data• Business Models• Technology• Market for Big Data• Risks & Limitations of Big Data• Conclusions

Challenges with Legacy BI applications

• Management of unstructured data is a very large problem

• Performance of conventional databases (RDBMS) degrades

with increase in data volume

Outline

• Objective and Methodology• What Is Big Data?• Challenges with Legacy BI applications• Applications of Big Data• Business Models• Technology• Market for Big Data• Risks & Limitations of Big Data• Conclusions

Sectors which can benefit from Big Data

Common Big Data Customer ScenariosGain competitive advantage by moving first and fast in your industry

IT infrastruc-ture opti-mization

Legal discovery

Social net-work analysis

Traffic flow optimization

Web app op-timization

Churn analysis

Fraud detection

Natural re-source explo-ration

Weather forecasting

Healthcare outcomes

Life sciences research

Advertising analysis

Equipment monitoring

Smart meter monitoring

Outline

• Objective and Methodology• What Is Big Data?• Challenges with Legacy BI applications• Applications of Big Data• Business Models• Technology• Market for Big Data• Risks & Limitations of Big Data• Conclusions

Big Data Framework Big Data is Big Business

CrowdsourcingSentiment Ana-lysis, Network Analysis

Cluster Analysis, Multidimensional Analysis

Predictive Model-ing

Outline

• Objective and Methodology• What Is Big Data?• Challenges with Legacy BI applications• Applications of Big Data• Business Models• Technology• Market for Big Data• Risks & Limitations of Big Data• Conclusions

Technology Driven mainly by Open Source initiatives

Apache™ Hadoop project

Apache™ Cassandra project

Apache™ HBase project

Apache™ Hive project

Apache™ Solr project

Outline

• Objective and Methodology• What Is Big Data?• Challenges with Legacy BI applications• Applications of Big Data• Business Models• Technology• Market for Big Data• Risks & Limitations of Big Data• Conclusions

Market for Big Data Growth rate of Big Data industry is much higher than average

growth rate of IT industry

Outline

• Objective and Methodology• What Is Big Data?• Challenges with Legacy BI applications• Applications of Big Data• Business Models• Technology• Market for Big Data• Risks & Limitations of Big Data• Conclusions

Risks of Big Data Will be so overwhelmed

– Need the right people and solve the right problems

Technological considerations– Open source– Scalability & Performance issues

Many sources of big data is privacy– Self-regulation– Legal regulation

The Need for Standards Become more structured over time Fine-tune to be friendlier for analysis Standardize enough to make life much easier

Outline

• Objective and Methodology• What Is Big Data?• Challenges with Legacy BI applications• Applications of Big Data• Business Models• Technology• Market for Big Data• Risks & Limitations of Big Data• Conclusions

Conclusions Big Data is a large and fast growing market Leveraging Big Data for insights can enhance productivity and

competitiveness for companies Harnessing Big Data will enable businesses to improve market in-

telligence For IT professionals it means lot of new job opportunities in the

area of data analytics

Thank you