IDG Enterprise's 2015 Big Data and Analytics survey shows that the number of
organizations with deployed/implemented data-driven projects has increased by
125% over the past year. The momentum continues to build.
Big Data as a concept is characterized by 3Vs: Volume, Velocity, and Variety.
Big Data implies a huge amount of data. Due to the sheer size, Big Data tends
to be clumsy. The dominating implementation solution is Hadoop, which is
batch based. Not just a handful of companies in the market merely collect
lots of data with noise blindly, but they don't know how to cleanse it, let
alone how to transform, store and consume it effectively. They simply set up
a HDFS cluster to dump the data gathered and then label it as their "Big
Data" solution. Unfortunately, the consequence of what they did actually
marks the death of Big Data.
Collecting a lot of data is litera... (more)
Due to the unprecedented volume, variety, and velocity of Big Data, it is
neither trivial nor straightforward to find a clear path to jumpstart the Big
Data journey. This space is overwhelmingly crowded with so many immature
options and evolving solutions. To some extent it is somewhat confusing and
daunting. Where can you find an entry point? What is the most effective way
to get on board? Which aspects should you be mindful of? How can you not miss
the paramount things?
Why do you need to begin with the basics?
Here are five areas of consideration for Big Data on-ramp: Structur... (more)
In a recent panel session I chaired, a question was raised from audience in
the Q&A part about how to relate Big Data and Big Service. There are
basically two aspects in this: Big Data as a Service, and Big Data for Big
Big Data as a Service: BDaaS is to a large extent Big Data cloudification. We
build Big Data as a capability to collect, transform, import, store, process,
query, analyze, explore, predict, export, search,visualize,
and display a large amount of data. Then we expose this capability as a
service in a SaaS fashion, so users can leverage it to quickly solve... (more)
Big Data is a loose term for the collection, storage, processing, and
sophisticated analysis of massive amounts of data, far larger and from many
more kinds of sources than ever before. The definition of Big Data can be
traced back to the 3Vs model defined by Doug Laney in 2001: Volume, Velocity,
and Variety. The fourth V was later added in different fashions, such as
“Value” or “Veracity”.
Interestingly the conceptualization of Big Data in the beginning of this
century seems to gain wider use now after nearly 14 years. This sounds a
little strange as the present dynamic world ha... (more)
Internet of Things (IoT) is booming. The “Software for the Internet of
Things (IoT) Developer Survey” report, published by Embarcadero
Technologies last month, shows that 77% of development teams will have IoT
solutions in active development in 2015 with almost half (49%) of IoT
developers anticipating their solutions will generate business impacts by the
end of this year.
IoT Maturity Model (IoTMM) is a qualitative method to gauge the growth and
increasing impact of IoT capabilities in an IT environment from both business
and technology perspectives. It comprises a set of crite... (more)