Bridging Two Worlds: Big Data and Enterprise Data
- by Dain C. Hansen
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The big data
world is all the vogue in today’s IT conversations. It’s a world of volume, velocity,
variety – tantalizing us with its untapped potential. It’s a world of transformational
game-changing technologies that have already begun to alter the information
management landscape.
One of the reasons that big data is so compelling is that
it’s a universal challenge that impacts every one of us. Whether it is healthcare,
financial, manufacturing, government, retail - big data presents a pressing
problem for many industries: how can so much information be processed so quickly to deliver the ‘bigger’ picture? With big data we’re tapping into new
information that didn’t exist before: social data, weblogs, sensor data,
complex content, and more. What also makes big data revolutionary is that it turns
traditional information architecture on its head, putting into question
commonly accepted notions of where and how data should be aggregated processed,
analyzed, and stored. This is where Hadoop and NoSQL come in – new technologies
which solve new problems for managing unstructured data. And now for some worst practices that I'd recommend that you please not follow:
Worst Practice Lesson 1: Throw away everything that
you already know about data management, data integration tools, and start completely
over.
One shouldn’t forget what’s already running in
today’s IT. Today’s Business Analytics, Data Warehouses, Business Applications
(ERP, CRM, SCM, HCM), and even many social, mobile, cloud applications still
rely almost exclusively on structured data – or what we’d like to call
enterprise data. This dilemma is what today’s IT leaders are up against: what
are the best ways to bridge enterprise data with big data? And what are the
best strategies for dealing with the complexities of these two unique worlds?
Worst Practice Lesson 2: Throw away all of your existing
business applications … because they don’t run on big data yet.
Bridging the two worlds of big data and enterprise
data means considering solutions that are complete, based on emerging Hadoop
technologies (as well as traditional), and are poised for success through
integrated design tools, integrated platforms that connect to your existing business applications, as well as and support real-time analytics.
Leveraging these types of best practices translates to improved productivity,
lowered TCO, IT optimization, and better business insights.
Worst Practice Lesson 3: Separate out [and keep
separate] your big data sandboxes from all the current enterprise IT systems.
Don’t mix sand among playgrounds.
We didn't tell you that you wouldn't get dirty doing this. Correlation between the two worlds is key. The real advantage to analyzing big data comes when you can correlate it with the existing data in your data warehouse or your current applications to make sense of the larger patterns.
If you have not
followed these worst practices 1-3 then you qualify for the first step of our
journey: bridging the two worlds of enterprise data and big data. Over the
next several weeks we’ll be discussing this topic along with several others
around big data as it relates to data integration. We welcome you to join us in
the conversation by following us on twitter on #BridgingBigData or download our latest
white paper and resource kit:
Big Data and Enterprise Data: Bridging Two
Worlds.
