文件名称：Analytics for the Internet of Things 2017.7
文件大小：19.04MB
文件格式：PDF
更新时间：2020-09-06 03:41:23
物联网 数据分析 Analytics 人工智能
Intelligent Analytics for your Intelligent devices 针对智能设备的数据智能分析 Book Description 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 Spark can be leveraged to handle scalability, and how R and Python can be used for analytic modeling. Style and approach This book follows a step-by-step, practical approach to combine the power of analytics and IoT and help you get results quickly Contents Chapter 1. Questions Chapter 2. Defining Iot Analytics And Challenges Chapter 3. Iot Devices And Networking Protocols Chapter 4. Iot Analytics For The Cloud Chapter 5. Creating An Aws Cloud Analytics Environment Chapter 6. Collecting All That Data – Strategies And Techniques Chapter 7. Getting To Know Your Data – Exploring Iot Data Chapter 8. Decorating Your Data – Adding External Datasets To Innovate Chapter 9. Communicating With Others – Visualization And Dashboarding Chapter 10. Applying Geospatial Analytics To Iot Data Chapter 11. Data Science For Iot Analytics Chapter 12. Strategies To Organize Data For Analytics Chapter 13. The Economics Of Iot Analytics Chapter 14. Bringing It All Together