Real-time Analytics in Bigdata EcosystemACCESS DATA REAL-TIME

What is 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. But it’s

not the amount of data that’s important. It’s what

organizations do with the data that matters. Big

data can be analyzed for insights that lead to better

decisions and strategic business moves.

Data is ExplodingToday, every 2 minutes we are generating same amount of data that was created from the beginning of time until the year 2000.

Every minute we spend over 200 million emails, generate almost 2 million Facebook likes, send over 250 thousand tweets, and upload over 20,000 photos on Facebook.

90%

Over 90% of all the data in the world was created in the past 18 months.

Google alone processes 40 thousand search queries per second, making it over 3.5 billion in a single day.

Over 100 hours of video are uploaded on YouTube every minute and it would take you around 15 years to watch every video uploaded by users in one day.

If you burned all the data created in just one day onto DVDs, you could stack them on each other and reach the moon – twice.

The number of bits of information stored in the digital universe is thought to have exceeded the number of stats in the physical universe in 2007.

The big data industry is expected to grow from US $10.2 billion in 2013 to about US $54.3 billion by 2017.

TECHNOLOGIES FOR REAL-TIME

ANALYTICS SOLUTION

Apache Kafka

Fast, scalable, and durable

Based on modern-cluster centric design

Handles hundreds of megabytes of reads and writes per second

Designed to allow a single cluster to serve

Apache Storm

Free, open-source, distributed, and real-time computation system

Simple and can be used with any programming language

Fast, guaranteed data processing, easy to set up and operate

Integrates with queuing and database technologies

Spark

Open-source, distributed computing framework

Addresses critical challenges to advanced analytics in Hadoop

Supports in-memory processing and is faster than MapReduce

Offers integrated framework for advanced analytics

Druid

Open-source infrastructure for real-time exploratory analytics

Druid’s real-time nodes employ lock-free ingestion for append-only data sets

Leverages memory mapping capabilities and uses distributed architecture

Druid offers multi-dimensional filtering

Companies and their Big Data Solutions WHAT THE COMPANIES OFFER

Enterprise big data initiatives face a massive challenge in processing and pulling value out of volume. But, the right big data services can process huge volumes of data to extract the kind of actionable insights that can truly drive a business forward.

Big data analytics accelerators and aggregators

Partnerships and alliances with major big data solutions vendors

Big data maturity roadmaps and reference architecture

Starting point to endpoint implementation assessments

Industry-specific key performance indicator (KPI) toolkits

Innovative industry frameworks tailored for specific industry needs

Big data labs and Centers of Excellence (CoEs) across multiple locations that focus on product evaluation and performance benchmarking

Employee count: 15,000+www.mindtree.com

Technology used:

In-house experts use technology, proven frameworks and tools and domain expertise to turn problems into successful business outcomes, delivering data visualization, enterprise data management, business intelligence and data analytic solutions under one umbrella.

Central to Cognizant's strategy around discovering and driving business value in big data is our innovative suite of solutions. Each leverages big data technologies to deliver enhanced insight and analytics to various industries.

Solution accelerators

Big data lab on demand

Idea to implementation

Data visualization and analytics

Technology evaluation and piloting

Big data strategy and roadmap definition

Employee count: 100000+www.cognizant.com

Technology used:

• Big Data Analytics Value Assessment (BAVA) Framework

• iSMART (integrated Social Media Analytics and Reporting Tool

• SCOREL (stock correlation analytics)

• SmartNode

• Hadoop

Cybage’s expertise covers an array of relevant tooling, frameworks, and building blocks. The pre-verified and gaps-addressed core Hadoop frameworks remove the guesswork out of implementation. The Big Data insights, and cloud infrastructure has made it imperative for products and services to create and deliver experiences through digital channels and infrastructure.

Coordinated infrastructure and workflow frameworks

Quick Analytics

NoSQL databases: MongoDB, Cassandra, HBase, and Neo4j

Distributed log processing: Flume, Scribe, and Chu kwa

Hadoop-focused QA: Comprehensive big data verification, cluster benchmarking, and performance tuning

Specialized test methodology: Purpose-engineered statistical test methodology for big data solution verification

Focused big data test team: Dedicated QA Architect and big data test team

Employee count: 5,000+www.cybage.com

Technology used:

Sqoop, Hive, PentaHo, SSRS, Cognos, and Qlikview, Hadoop

To help organizations make sense of their data, Persistent has developed ShareInsights – A unique platform that allows organizations to analyze an overlay of enterprise data with public or cloud sources to derive meaningful insights. An open platform, ShareInsights enables users to mine meaningful insights from the data sources that matter to them and share them with a wide audience. Users can quickly and easily on-board new use cases and summarize large volumes of unstructured data.

Multi-Faceted Data allowing user to gain interesting insights

Quick Analytics

Seamlessly share insights on Facebook or the ShareInsights Gallery

Library of algorithms and integration with third party datasets, including public datasets

Built-in visualizations

Drill down capabilities to find particular behavior

Analyzes unstructured text

Employee count: 8,000+www.persistent.com

Technology used:

Hadoop, Sqoop, SciDB

Benefits of Big DataWHAT YOU CAN ACHIEVE WITH BIG DATA

Big Data

Dialogue with

Consumers

New Products &

Services

Risk Analysis

Faster and Better

Reduced Cost

Customize in Real Time