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 criteria, parameters and
factors that can be used to describe and measure the effectiveness of the IoT
adoption and implementation.
Five levels of maturity are defined: Advanced, Dynamic, Optimized, Primitive,
and Tentative (ADOPT). The definitions of these 5 levels are specified below:
Level Desc... (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)
I will present a tutorial on the service-oriented model-driven architecture
design for cloud solutions in the upcoming International Conference on Web
Services (ICWS 2009). Please join the session to explore the state-of-the-art
approach to effectively developing cloud services in a systematic fashion.
Contact Tony Shan (email@example.com) for more info.
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)
NoHadoop is not only Hadoop. Why?
According to the 2014 Big Data & Advanced Analytics Survey conducted by the
market research firm Evans Data, only 16% of over 400 developers surveyed
worldwide indicated that Hadoop batch processing was satisfactory in all use
cases. 71% of developers also expressed a need for real-time complex event
processing more than half the time in their applications, and 27% said they
use it all the time.
Hadoop has evolved from MapReduce and HDFS in the very beginning to a set of
technologies, including Hive, HBase, Sqoop, Flume, Pig, Mahout, etc. Though, ... (more)