IRJET- A Scrutiny on Research Analysis of Big Data Analytical Method and Clou...
Brochure_Big-Data_Offerings
1. www.persistent.com
Big Data
B R O C H U R E
Persistent’s Big Data Offerings
“Enterprise data
will increase 650%
over the next five
years.“
- Gartner Research
“IDC predicts the
market for big data
technology and
services will reach
$16.9 billion by
2015, up from $3.2
billion in 2010. That
is a 40 percent-a-
year growth rate —
about seven times
the estimated
growth rate for the
overall information
technology and
communications
business.”
- IDC
“IDC forecasts that
the Big Data
technology and
services market will
grow at a 27%
compound annual
growth rate (CAGR)
to $32.4 billion
through 2017.”
- IDC prediction
According to IDC 2014 Digital Universe study, “From 2013 to 2020, the digital universe will grow by a factor
of 10 - from 4.4 trillion gigabytes to 44 trillion. It more than doubles every two years.”
Enterprises today are faced with having to deal with this avalanche of Big Data coming at them from a wide
variety of sources including: internal teams, public entities, social media, web applications, data centers,
etc. Enterprises are also discovering that insights derived from analyzing this body of Big Data can help
them improve customer satisfaction and gain a competitive advantage. However, the challenge that
enterprises often face is the lack of expertise in building Big Data solutions capable of analyzing these
volumes of data and deriving real conclusions that are meaningful to their business objectives.
Persistent recommends that enterprises consider Big Data as the third data stack in the organization,
DataStack 3.0. Persistent has introduced DataStack 3.0 as a way to help enterprises think about how Big
Data fits into their organization’s data infrastructure. DataStack3.0 provides the ability to perform deep
analytics at a fraction of the cost, in an agile manner while integrating with traditional data infrastructure.
OfferingsPortfolio
Persistent has been at the forefront of the Big Data revolution for over 4 years, working on key
technologies, building platforms and creating solutions to solve Big Data problems - whether it is
developing Hadoop algorithms to solve computational problems, or building Text Analytics techniques to
analyze unstructured text and perform sentiment analysis. Our Big Data focus has been in 3 areas -
Engineering, Solutions, and Services.
Engineering - (Analytical Application Development)
Solutions for multiple data types that use Hadoop platform tools including Nutch, Hive, Pig, JAQL
and more
Developing connectors to load data into Hadoop's distributed file system (HDFS)
Helping leading software vendors build applications using Hadoop and NoSQL technologies
Code contributions to open source projects like Hadoop, Hive and SciDB
Significant experience on core Hadoop APIs as well as eco-system of open source projects
surrounding Hadoop, such as Hive, MongoDB, Cassandra Hbase, Sqoop, and PIG /JAQL
Services around Big Data
Hadoop/MapReduce Programming Services
Developing custom applications to fit in MR paradigm
exposed by Hadoop
Porting existing applications on Hadoop using
MapReduce
Tuning existing MapReduce programs to improve
performance
Implementation Services
Installing and integrating Hadoop clusters on
new machines
Configuring Hadoop settings for optimal
performance
Monitoring Hadoop clusters