B IG DATA
For business analytics to
be successful in meeting
an organization’s needs
for decision support, it
fundamentally needs to be
able to consider all data
sets relevant to solving
a particular business
question.
compression techniques have resulted in organizations being able to get insights from data quicker.
As organizations come to terms with managing
big data and harnessing them through systems and
converge their usage with traditional data sources,
the business analytics to guide decision-making is
itself evolving. This article will focus on how analytics has been influenced by big data and what
practices will emerge in years to come through observations within Hewlett Packard.
UNITED WE ARE “BIG,” DIVIDED WE MAY
BE SMALL
For business analytics to be successful in meeting an organization’s needs for decision support,
it fundamentally needs to be able to consider all
data sets relevant to solving a particular business
question.
Traditional business intelligence (BI) and enterprise data warehouse (EDW) environments focus
on the usual data generated from business operations. This is data generated through point of sale
transactions, customer data, financial, business
planning data, inventory management systems, etc.
Businesses today, however, also have access
to two other key forms of data. The first of these can
be loosely categorized as “human information”; this
form of data comes from having increased knowledge of customers through e-mail, social media
and other marketing channels, but also from an organization’s institutional data in the form of documents and customer support call records, as well
as video, audio and image sources. This data tends
to be unstructured in format.
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A N A LY T I C S - M A G A Z I N E . O R G
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