big data analytics and its future prospect

Big Data Analytics and its Future ProspectsBig Data Analytics and its Future Prospects

Convergence and its role in managing data effectively across industriesConvergence and its role in managing data effectively across industries

Swapnadeep Nayak

Sr. Research Analyst

Technical Insights - ICTTechnical Insights - ICT

26-09-2013

© 2013 Frost & Sullivan. All rights reserved. This document contains highly confidential information and is the sole property of

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Functional Expertise

� Experienced research and consulting professional in information and communication technology domain.

Specific functional expertise in:

- Analyzing and tracking recent technology developments in ICT across the globe

- Providing strategic recommendations on marketing strategy, market feasibility and competitor profiling

- Proposal writing, Client presentations

- Strategic support to the sales team

- Analyzing Case Studies on marketing and technical topics

Industry Expertise

- Diverse experience base in various information and communication technology markets including:

• Enterprise communications and infrastructure, mobile and wireless communication, network security with

specific emphasis on projects on technology/ R&D management, funding analysis and roadmapping

SWAPNADEEP NAYAK

2

specific emphasis on projects on technology/ R&D management, funding analysis and roadmapping

What I bring to the Team

- In depth understanding of both technology and management

- Extensive client interaction skill while working on research and consulting projects

- Teamwork & team management skills

Career Highlights

� Prior to Frost & Sullivan, market research experience with Ensine Knowledge Systems Pvt. Ltd

� Market research and product promotion experience with Philips Electronics India Ltd. as part of internship

� Software and website development experience through freelance and academic projects

Education

� Master of Business Administration specialised in Marketing and System from West Bengal University of

Technology (Kolkata, India)

� B.Tech in Computer Science Engineering from West Bengal University of Technology (Kolkata, India)

Swapnadeep NayakSr. Research Analyst

Technical Insights Information and Communication

Technologies

swapnadeepnayak @swapnadeepn@frost.com

Frost & SullivanSouth Asia

KolkataIndia

Focus Points

Agenda

• Why is Big Data Analytics important today ?

• Big Data Value Chain

• Security issues hindering Big Data adoption

• Recent trends in Big Data technology

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• How Big Data converges with technologies in other industries

• Potential Convergence Scenarios

• Potential opportunities for developers

• Conclusion

Why is Big Data Analytics Important Today ?

Big Data Big Data

AnalyticsAnalytics

Efficient information procurement is increasingly critical for businesses to

extract value from various data sources. Big Data Analytics refers to a set of

data management tools, appliances and techniques for effective analysis of

these aggregated business data from various data sources.

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� Big Data Analytics abolishes the limitations in scalability and slow processingspeed which exists in traditional data warehousing processes.

� Big Data Analytics is capable of processing both structured and unstructured datafrom various sources.

� Big Data Analytics empowers enterprises with real-time extraction of data fromvarious sources.

Importance of Big Data Analytics

Big Data

Big Data Analytics

BI

Big Data Value Chain

Big Data Integrated Platform

End UsersStorage Technology Processing TechnologyApplication Focused

TechnologyDistributors

Securing information at data acquisition

level

Securing information at data management

level

Securing Big Data with Security analytics

application integration

Security Technology Vendors

This slide represents various segment of Big Data which facilitates development of applications (analytics) for end users across various industries

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Computing Power VendorsStorage Vendors Analytics Application Developers

Source: Frost & Sullivan

Security Issues Hindering Big Data Adoption Key operational and technical issues (1/2)

Operational Issues

• Inter-nodecommunication

• Deployment is done with only minimal amount of security like password protection

• Addressing several critical issues with the architectural and operational flaws couldameliorate the overall security of Big Data platform.

Core issuesof security

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Technical Issues

Issuescommunication

• “Sharded” data

• Distributed cluster

• No Scalable security

Source: Google

Source: Google

• Nodes and application authentication

• Data protection at Rest

• Monitoring and Audit log

Security Issues Hindering Big Data Adoption Key operational and technical issues (2/2)

Less secured Protocol

Lack of TLC and SSL

Absence of choke-point

Constant movement of data

Operational Issues

Limitation with Kerberos

Security flaws with

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HDFS Proxy limitation

Model lacks scalability

Technical IssuesTechnical Issues

Security flaws with cloud environment

Lack of encryption with NoSQL

Absence of in-built monitoring features

Security Issues Hindering Big Data Adoption Strategies to address challenges

Encryption

Node

validation

Scalable

Security

Strategies to

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Kerberos

Usage

Evaluate Log

activities

SSL/TSL Layer

security

Strategies to address Big Data security issues

Recent Trends in Big Data Technology

Big Data space is experiencing rapid changes across various segments -- big data framework, storage, data processing andanalytical application segment.

Enhancement of distributed architecture framework for Big Data. Development of

novel platform.

Scalable data storage for Big Data leveraging cloud computing technologies.

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Trends in Big

Data Space

Scalable data storage for Big Data leveraging cloud computing technologies.

Improving data processing power with real-time data stream engine.

Analytics application development targeted towards specific industry segments such as health & wellness and energy.

Technology Clusters Benefitting due to Big Data Convergence

Big Data Big Data

Clean and Green Energy

Health & Wellness

Materials & Coating

Information & Communication

Technology

Advanced Manufacturing & Automation

• Clusters benefitting due to Big Data convergence are

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Big Data Big Data AnalyticsAnalytics

Coating

Sustainable Energy

Sensors & Control

Microelectronics

Medical Device Technology

Technology convergence are highlighted (in red).

Four Health and Wellness Technologies from the Top 50 TechnologyPool Benefit due to Big Data Convergence

Big Data Analytics

Biomarkers

Targeted Drug

Delivery

Targeted case specific

drugs for better treatment.

NextBio, a key player in the

space.

Computational and

laboratory analysis of

biomarkers. Determines

diseases during test

phases.

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Analytics with Health & Wellness

Next-Gen Sequencing

Personalized Medicine

Handling huge terabytes of

data coming from next-gen

DNA sequencing. BDA

simplifies the process.

Leverages predictive BDA

to address challenges for

specific diseases like

cancer. GNS Healthcare is

one of the key participants.

Six Information and Communication Technologies from the Top 50Technology Pool Benefit due to Big Data Convergence

Big Data Analytics with

Information and

Cloud Computing

Semantic

Virtualization

Data

New concept emerged

through Big Data

Analytics-as-a-Service and

Hadoop-as-a-Service.

Predictive analytics

successfully enrich

the results of

Providing visual

support to enterprise

data for better

Server virtualization helps to

bring down cost for storage

and computing resources thus

enabling cost-effective

analytics solution.

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Information and Communication

technology

Semantic Search

Augmented Reality

In-Memory Computing

Data Visualization

the results of

semantic search.

Hadoop Distributed File

System (HDFS) is being

used as the backend store

for in-memory Data grids

for real-time applications.

BDA helps to process huge

data collected from mobile

devices to render deep

insights for Augmented

Reality applications

data for better

understanding.

Big Data Convergence with Energy, Remote Patient Monitoring and Non-Volatile Memory

Big Data Analytics with

Microelectronics, Medical Device

Technologyand Sustainable

Next-gen Advanced

Other technologies from clusters like Sustainable Energy, Microelectronics and Medical Device Technology are alsoexperiencing convergence in recent days. These technologies are still in their emerging phase with few initiatives fromdevelopers working on the specific clusters.

Energy efficient Resistive

RAM (RRAM) helps Big Data

for development of advanced

analytical applications. Ex:

Crossbar Inc.

BDA enables efficient

monitoring of energy storage,

thereby helps in reducing the

electricity cost through

convergence. Ex: Stem.

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and Sustainable Energy

Next-gen Non-Volatile

Memory

Advanced Energy Storage

Remote Patient

Monitoring

Grid Energy Management

Drives actionable insights to

health professionals

monitoring remote patients

through monitoring systems.

Ex: Qualcomm Life

Big Data helps to manage

large decentralized power

network and enables

development of Smart Grid

and Smart Meters.

Potential Convergence Scenarios Convergence with Advanced Manufacturing & Automation, Medical Device Technology and Sensors & Control

Big Data

Analytics

Ubiquitous Wireless Sensors Ubiquitous

wireless sensors could converge with

Big Data Analytics for faster processing of sensor

data and facilitating new applications and services for home and office automation.

3-D Printing

BDA could be leveraged to analyze and identify potential trouble during 3-D printing. 3D printing being a new technology needs quality control tool before mass production.

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This convergencewill elevate surgical

accuracy. Surgical Robots are likely to be capable of diagnosis and performing

fully automated complicated operations successfully .

Surgical Robots

Energy HarvestingR&D activities on

converging BDA with energy harvesting has just started to enhance process control and monitoring. Wireless sensor platform and Big Data would enable predictive analysis at remote location monitoring for oil and gas industry

Potential Convergence Scenarios Convergence with Sustainable Energy and Sensors & Control

Big Data

Analytics

CBRNE Detection With gradual

collection of data at battlefields, big data

analytics can be used to map trends and patterns in

CBRNE detection across war zone as well as vast

geographies.

SuperconductorsSuperconductorapplications acrossvarious industries like transportation, healthcarecould leverage Big Data analytics to monitor electric power efficiency and diagnosis of propulsion systems and Magnetic Resonance Imaging system.

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Resonance Imaging system.

Wind PowerApplying analyticsand harnessing bigdata will allow utilities to tackle the intermittentnature of renewable energyand forecast power production from wind.

Potential Opportunities for Developers Viable Segments for New Entrants to attract investors

Analytics for Logistics

Big Data

Analytics in Banking and

Insurance

Smart Energy Management

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Analytics Applications

Analytics in Retail

Supply Chain Analytics

Green Telematics

Source: Google

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For Additional Information

Britni Myers

Corporate Communications

Information & Communication Technologies

(210) 477-8481

Britni.myers@frost.com

Swapnadeep NayakTechnical Insights

Sr. Research Analyst

033-6627-3360

swapnadeepn@frost.com

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