LEADER 00000uam a2200409 a 4500
006 m u
007 cr cn
008 170801s2017 xx o eng
024 8 9781787120730
041 0 eng
100 1 Minteer, Andrew,|eauthor.
245 10 Analytics for the Internet of Things (IoT)|h[electronic
resource] /|cMinteer, Andrew.
250 1st edition
264 1 |bPackt Publishing,|c2017.
300 378 p.
338 online resource|bcr|2rdacarrier
347 text file
520 Break through the hype and learn how to extract actionable
intelligence from the flood of IoT data About This Book
Make better business decisions and acquire greater control
of your IoT infrastructure Learn techniques to solve
unique problems associated with IoT and examine and
analyze data from your IoT devices Uncover the business
potential generated by data from IoT devices and bring
down business costs Who This Book Is For This book targets
developers, IoT professionals, and those in the field of
data science who are trying to solve business problems
through IoT devices and would like to analyze IoT data.
IoT enthusiasts, managers, and entrepreneurs who would
like to make the most of IoT will find this equally
useful. A prior knowledge of IoT would be helpful but is
not necessary. Some prior programming experience would be
useful What You Will Learn Overcome the challenges IoT
data brings to analytics Understand the variety of
transmission protocols for IoT along with their strengths
and weaknesses Learn how data flows from the IoT device to
the final data set Develop techniques to wring value from
IoT data Apply geospatial analytics to IoT data Use
machine learning as a predictive method on IoT data
Implement best strategies to get the most from IoT
analytics Master the economics of IoT analytics in order
to optimize business value In Detail We start with the
perplexing task of extracting value from huge amounts of
barely intelligible data. The data takes a convoluted
route just to be on the servers for analysis, but insights
can emerge through visualization and statistical modeling
techniques. You will learn to extract value from IoT big
data using multiple analytic techniques. Next we review
how IoT devices generate data and how the information
travels over networks. You’ll get to know strategies to
collect and store the data to optimize the potential for
analytics, and strategies to handle data quality concerns.
Cloud resources are a great match for IoT analytics, so
Amazon Web Services, Microsoft Azure, and PTC ThingWorx
are reviewed in detail next. Geospatial analytics is then
introduced as a way to leverage location information.
Combining IoT data with environmental data is also
discussed as a way to enhance predictive capability. We’ll
also review the economics of IoT analytics and you’ll
discover ways to optimize business value. By the end of
the book, you’ll know how to handle scale for both data
storage and analytics, how Apache...
533 Electronic reproduction.|bBoston, MA :|cSafari,|nAvailable
via World Wide Web.
538 Mode of access: World Wide Web.
542 |fCopyright © Packt Publishing
550 Made available through: Safari, an O’Reilly Media Company.
655 7 Electronic books.|2local
710 2 Safari, an O’Reilly Media Company.
830 0 Safari Books Online
856 40 |uhttps://ezp.lib.unimelb.edu.au/login?url=https://
&orpq&email=^u|zConnect to ebook (University of Melbourne
990 Safari Books Online
990 Batch Ebook load (bud2) - do not edit, delete or attach
| UniM INTERNET resource
|| AVAILABLE |