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Addressing Storage Challenges to Support Business Analytics and Big Data Workloads
1. W H I T E P AP E R
Ad d r e s s i n g S t o r a g e C h a l l e n g e s t o S u p p o r t B u s i n e s s
An a l y t i c s a n d B i g D a t a W o r k l o a d s
Sponsored by: IBM
Laura DuBois
September 2012
E X E C U T I V E S U M M AR Y
Today, business analytics projects are being initiated to improve business and customer
operations across nearly every business sector while having a transformative effect on
many businesses. Traditional data warehousing and online analytical processing
approaches, combined with new analytical processing run against streaming and real-
time data, enable firms to react dynamically to different customers, users, suppliers, and
other key stakeholders. What was once just information, delivered on a periodic and
point-in-time basis, has now been transformed into insight with data and analysis
available in real time and at any moment.
The benefits that firms can derive from business analytics and big data projects are
broad. Growing customers, identifying the most profitable customers, and measuring
and increasing retention rates are benefits realized by telecommunications providers.
Call centers for firms in many sectors can leverage analytics processes to measure
and improve operational efficiency and/or customer service. Banking institutions can
mitigate business, security, and privacy risks; reduce fraud; and manage compliance.
In addition, healthcare providers can transform and automate financial and other
operational processes as well as personalize patient care.
S I T U AT I O N O V E R V I E W
B i g D a t a a n d t h e F o u r V s
The convergence of intelligent devices (consumer products such as smartphones and
tablets, smart cars, smart buildings, smart infrastructure, etc.), social networking,
pervasive broadband networking, and analytics ushers in a new era for business
analytics that is redefining relationships among producers, distributors, and
consumers of goods and services.
In the past, enterprises only had to deal with a finite and manageable number of data
sources. However, today's business environment includes not only more data but also
more types of data than ever before. The combination of data from a variety of data
sources and in a variety of formats is a key challenge with which business analytics and
big data projects must contend. Another component of big data is velocity, or the speed
at which information arrives and is analyzed and delivered. The velocity of data moving
through the systems of an organization varies from batch integration and loading of data
at predetermined intervals to real-time streaming of data. The former can be seen in
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