Page 17 - Building Big Data Applications

Chapter 1 Big Data introduction 11

but around acquiring all the raw data and then using that for discovery and
finally reporting.
7. Artificial Intelligence is the new realm of intelligence that will be built for all en-
terprises. The intelligence is derived from both trained and untrained data sets.
The artificial intelligence algorithms will be implemented across the entire data
ecosystem, ranging from raw data to analytics databases. The algorithms can be
opensource or enterprise or vendor provided. The implementation includes con-
cepts including blockchain, robotic process automation, and lightweight data de-
livery systems.
8. Machine learning refers to an ecosystem of analytics and actions built on system
outcomes from machines. These machines work 24/7/365 and can process data in
continuum, which requires a series of algorithms, processes, code, analytics,
action-driven outcomes, and no human interference. Work taking place for more
than 25 years in this area has led to outcomes such as IBM Watson; TensorFlow,
an open source library for numeric computation; Bayesian networks; hidden
Markov model (HMM) algorithms; and Decision theory and Utility theory models
of Web 3.0 processing. This field is the advancement of artificial intelligence algo-
rithms and has more research and advancement published by Apache Software
Foundation, Google, IBM, and many universities.
9. Smart everything
a. Smart thermostatsdThe arrival of smart thermostats represents a very exciting
and powerful Internet of Things technology. For example, based on the choices
you make for controlling temperature, lighting, and timing inside your home,
you can use your smartphone or tablet to control these home environment
conditions from anywhere in the world. This capability has created much
excitement in the consumer market. Millions of homes now have these devices
installed. But what about the data part of this solution? To be able to do this
smart thermostat magic, the device needs to be permanently connected to the
Internet, not only to accommodate access, but more importantly to continu-
ously send information to the power company or device manufacturer or both.
Hence, the fear of the unknown: if anybody can get access to these devices and
obtain your credentials from the stream of data, imagine what can happen
next. Not only is identifying user preferences possible, someone hacking into
the smart thermostat can monitor your presence in the home, break in when
youarenot there or worse. Once someone has access to the network, theft of
data can occur that possibly leads to other kinds of damage. Is this solution
really that insecure? The answer is no. But ongoing work in the area of data
governance and data privacy attempts to address the gaps in security that can
cause concern. To help minimize these concerns, the underlying security of
the data needs to be well managed.
b. Smart carsdElectric automobiles manufactured by Tesla Motors and Nissan,
for example, are touted for being purely electrically driven thanks to the