Big Data for Big Industries
Introduction: Why Does Big Data Matter to Me?
It’s no longer the case that
all possible insights about
an organization come only
from a structured data
warehouse full of vetted
data developed inside
one’s own four walls.
There is a new universe of data being created by smart meters, mobile devices,
social media, RFID, web logs, and other sources. Meanwhile, many industries have
only begun exiting the paper-based documentation era. It’s no longer the case
that all possible insights about an organization come only from a structured data
warehouse full of vetted data developed inside one’s own four walls. Embracing
big data means accepting that you can gain valuable insights about your organization, your customers, and the world at large from external sources, and by looking
at data in a new way.
Organizations in every industry need to explore big data and gain insights.
However, to date there has been a critical gap between big data and tools that
help businesspeople analyze it. CITO Research has endeavored to find new tools
and methods to help companies use big data to its full potential. With the right big
data tool, such as the QlikView business discovery platform, you can create a richer
model of your organization and the wider world, recognize events you would not
have discovered otherwise, and deliver a view from outside the organization of
trends that give you a competitive edge, make concrete business improvements,
and even save lives.
How the QlikView Business Discovery Platform
Helps with Big Data
CITO Research has conducted a deep dive analysis of the leading data discovery
vendor, QlikView. QlikView provides what it calls a business discovery platform, a
variant of data discovery, that delivers self-service BI.
Unlike traditional BI tools, in which predefined reports and dashboards are static
and limited to simple filters, selections, and drill-downs, CITO’s experience with
QlikView is that it enables business users to explore and streamline big data with
ease, on their own. QlikView is a robust platform that’s secure, app-driven, mobile,
and facilitates collaborative decision making.
With big data, the data itself and the structure of that data are both constantly
changing, often in unexpected ways. At the same time, no enterprise will be
throwing out its carefully structured databases. To reveal actionable insights, a
BI tool must simultaneously query structured and unstructured sources. With
QlikView, this is not only possible, but intuitive.
Once processed, data is then presented in an associative experience in which
every data point is associated with every other data point. In previous white
papers, we’ve compared it to a fiber-optic spider web, where everything is con-
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Big Data for Big Industries
nected. Pulling on one thread, or making a selection, lights up the related elements in other fields, showing you new paths through the data and revealing new
kinds of connections. That means user-driven analytical applications can be built
on the fly, to ask questions that occur as data arrives.
QlikView is a robust
platform that’s secure,
app-driven, mobile, and
facilitates collaborative
decision making.
CITO Research has found that QlikView is making a big difference in big data in
several industries. The following is a series of snapshots that showcase the breadth
and depth of business benefits and competitive differentiators being enjoyed by
companies that have implemented QlikView.
Big Data and Healthcare
Healthcare providers such as hospitals, clinics, home health providers, and rehabilitation and hospice facilities collect and store a great volume and variety of patient
data, from individual diagnostics to mass demographics. Turning that data into
actionable information has proven difficult. Many healthcare entities still struggle
to answer questions such as:
?? What volume of patients can we expect?
?? What is the likelihood that a patient will be a recurring patient, disregard
medical advice, or miss scheduled appointments?
?? How can we best supply a hospital with equipment and medicine?
?? How should a hospital be staffed?
?? How can we meet regulatory demands and new mandates without sacrificing
service levels?
?? How can we improve quality of care, patient satisfaction, and operating room
and emergency department performance while reducing costs?
The data collected by hospitals spans from operational data, such as supply chain
logistics and employee timesheets and work records, to medical data such as
X-rays and MRIs. Medical data is often unstructured—think of a doctor’s notes or
images—and thus doesn’t fit into conventional relational database frameworks or
BI tools. Yet it often must be cross-referenced with plenty of data that does reside
in those tools. The time saved, and the increase in accuracy achieved by combining all data sources in one view, are compelling to consider.
Healthcare providers collect vast troves of data but often don’t gain much
actionable insight because many processes are manual and different tools were
designed to work with different types of data and are frequently in the hands of
disparate groups. Now, healthcare providers can correlate patient-specific historical data with current lab results and relate that data to larger demographic data,
such as a cross-section of the population likely to get the flu this year as determined by the Centers for Disease Control or historical drug reactions and interaction results across age, gender, and ethnicity—all in one place.
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