Page 8 - Cyber Warnings

Big Data Implementation is Not Just About Technology
How to Gain Maximum Business Value from Big Data

By Branko Primetica, Chief Strategy Officer, eGlobalTech

The business case for leveraging “Big Data” has been discussed extensively in conferences and
publications worldwide—and its value could not be clearer. Big Data is on the mind of every
business and technology leader from almost every industry sector imaginable. In addition, a
growing market of tools and techniques is now available to help organizations effectively
analyze large volumes of disparate, complex, and variable data in order to draw actionable
conclusions. Nevertheless, many of these same leaders are challenged in terms of successfully
realizing the benefits that Big Data has to offer, mainly because these leaders:

 Believe that it is revolutionary and technology-focused, rather than an iterative and cyclical
process
 Cannot determine the value of the data available to them, a challenge which is multiplied
when the fact that this data is consistently and rapidly expanding in terms of volume, variety,
and velocity (in part, due to factors such as IoT, social media, video and audio files)
 Are concerned about security and privacy issues

Although these challenges can seem overwhelming, they can be alleviated through a
methodical process focused on improving an organization’s mission performance. The key is to
adopt a use case-driven approach to determine how and when to begin a Big Data migration.
Assuming that the organization has already developed a Big Data strategy and governance
framework, this iterative approach begins with the business’ non-IT stakeholders who support
the organization’s primary or core functions. Step one is to use their institutional knowledge to
define and prioritize a set of business needs/gaps which would improve their ability to perform
their jobs more effectively. Once defined, the march towards Big Data begins in an iterative,
phased manner.

Following the prioritized order, the next step is to decompose each business need into a use
case (including items such as process flows, actors and impacted IT systems). This
decomposition will also help to facilitate the identification of all available data assets that touch
upon the use case (both private and public). In doing so, it is critical to brainstorm as broadly as
possible. For example, if a municipal government was trying to determine where to best position
staff and assets during adverse weather conditions in order to reduce impact on citizens, they
might use local weather reports, traffic camera feeds, social media reports, road condition
reports, 911 calls reporting vehicular accidents, sensor data, radar maps, population maps, road
maintenance schedules, traffic signal times, business/school closures, etc.— not just the
obvious traffic and weather reports. Each data asset should be assessed for quality (to
determine if cleanup is required) and mapped to its primary data source. Once the organization
has a handle on the data and data sources that will be analyzed to support the use case,
defining the proper security and privacy requirements for the Big Data analytics solution should
be more straightforward (instead of defining a broad set of security controls for a Big Data

8 Cyber Warnings E-Magazine – February 2016 Edition
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