IBM Systems Magazine, Mainframe - January/February 2017 - SE14
ARTICLE: BUSINESS INTELLIGENCE
Businesses rely on analytics, big data and BI to guide decisions
n the space of a few years, businesses have come to depend on
the wealth of information gleaned from big data, analytics and
business intelligence (BI). While some business decisions still may
be guided by gut feel, today most decisions are based on data
culled from customers, the marketplace and business operations.
This puts a bigger demand on IT systems and software, as the
flood of data may be coming from structured data, unstructured
data, mobile and social media. Further, data must be analyzed in
real time, and many enterprises need in-transaction analysis as
well. Enterprises are also looking for skilled employees who can
make sense of the data and help drive business decision-making.
The Spark Advantage
IBM has recognized the shift in analytics and is working to help
clients meet their data challenges successfully through the use
of open-source resources. That's why IBM has made a major
commitment to Apache Spark, putting 3,500 IBM developers and
researches to work on Spark-related projects. Spark is an open
source, in-memory analytics resource supported by the Apache
Foundation. IBM has made Spark available on z Systems* and
Linux* on z*. This is a major advantage; many clients use their
mainframe systems for storing high-value data, which can now be
accessed by Spark.
"The recent growth and adoption of
Apache Spark as an analytics framework
and platform is timely and helps meet
these challenging demands," says Mythili Venkatakrishnan, IBM
senior technical staff member and z Systems architecture and
technology lead for analytics. (See "IBM Brings Apache Spark's
Analytics Power to Linux and z Systems Servers," ibmsystemsmag.
Analytics Across Industries
Just about every sector and industry, from retail to manufacturing
to finance, is using some form of analytics-including predictive
analytics. Retailers are using predictive analytics to forecast top
sellers and expected customer behavior. (See "Retailer Optimizes
Analytics to Drive a More Customized Client Experience,"
Fraud detection is another key use of predictive analytics
that many businesses are employing to monitor and detect
fraud before massive damage can be done to the business.
(See "Analytics Can Be Your Best Defense Against Corporate
Businesses welcome the insights that big data and analytics
provide and are incorporating BI tasks
into their IT shops and business units. The
result is better decisions for the business
and better results for customers.
BY SHIRLEY S. SAVAGE
14 // 2017 ibmsystemsmag.com/buyersguide
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