Three "Housekeeping" Trends Impacting Big Data and Analytics Strategies
As the Big Data marketplace moves closer to a point of mass-maturity,
business leaders have begun to take new approaches to implementation and
utilization. Advanced analytics solutions have made their way into a range of
industries and regions, and companies that successfully align these
investments with core goals and requirements will enjoy more progressive
improvements to operational sustainability, intelligence and general
However, there is some housekeeping that must be addressed as organizations
embark on Big Data and analytics initiatives. Data preparation, information
governance and security are three fundamental elements of effective analytics
strategies, yet, ironically, each has been largely ignored by many
organizations in the rush to realize the promise of Big Data.
This is an unusual blog for me. Usually I talk about how organizations can
more effectively leverage data and analytics to power their business.
However, as I conduct more Big Data Vision Workshops, I have come to realize
that a big part of the success of these engagements is the ability to
“listen and comprehend.”
Here are some observations and tips for “listening and comprehending”
more effectively. I’ve classified this as “facilitation” because I seek
to “facilitate” a dialogue with the client where I can learn enough about
the client’s business to help them build the right B... (more)
[Note: I have been trying to write this blog for several years. But instead
of trying to perfect the concept, perhaps the best approach is to simply put
the idea out there and let it percolate amongst my readers. My University of
San Francisco Big Data MBA students will get a chance to test and refine the
approach outlined in this blog.]
Data is an unusual currency. Most currencies exhibit a one-to-one
transactional relationship. For example, the quantifiable value of a dollar
is considered to be finite – it can only be used to buy one item or service
at a time, or a person can ... (more)
The Big Data Intellectual Capital Rubik's Cube
This is another topic that has taken me a long time to write, but several
conversations with Peter Burris(@plburris) from Wikibon finally helped me to
pull this together. Thanks Peter!
I’ve struggled to understand and define the Intellectual Capital (IC)
components – or dimensions – of the new, Big Data organization; that is,
what are the new Big Data assets that an organization needs to collect,
enrich and apply to drive business differentiation and competitive advantage?
These assets form the basis of the modern “collaborative valu... (more)
The Quantified Economy and the Future of IoT Data
The Quantified Economy represents the total global addressable market (TAM)
for IoT that, according to a recent IDC report, will grow to an unprecedented
$1.3 trillion by 2019. With this the third wave of the Internet-global
proliferation of connected devices, appliances and sensors is poised to take
off in 2016.
In his session at @ThingsExpo, David McLauchlan, CEO and co-founder of Buddy
Platform, will discuss how the ability to access and analyze the massive
volume of streaming data from millions of connected devices in real ti... (more)
I’ve heard several clients complain about the curse of “orphaned
analytics”; which are one-off analytics developed to address a specific
business need but never “operationalized” or packaged for re-use across
the organization. Unfortunately, many analytic organizations lack a framework
for ensuring that the analytics are not being developed in a void.
Organizations lack an overarching model to ensure that the resulting
analytics and associated organizational intellectual capital can be captured
and re-used across multiple use cases.
Without this over-arching analytics framework... (more)