Big Data and the Internet of Things Enterprise Information Architect
Enterprise Information Architecture for a New Age: Big Data and The Internet of Things, provides guidance in designing an information architecture to accommodate increasingly large amounts of data, massively large amounts of data, not only from traditiona
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Contents at a Glance About the Authors��������������������������������������������������������������������������� xiii Acknowledgments��������������������������������������������������������������������������� xv Introduction����������������������������������������������������������������������������������� xvii ■Chapter ■ 1: Big Data Solutions and the Internet of Things�������������� 1 ■Chapter ■ 2: Evaluating the Art of the Possible������������������������������� 29 ■Chapter ■ 3: Understanding the Business��������������������������������������� 49 ■■Chapter 4: Business Information Mapping for Big Data and Internet of Things������������������������������������������������������������������������� 79 ■Chapter ■ 5: Understanding Organizational Skills��������������������������� 99 ■■Chapter 6: Designing the Future State Information Architecture������������������������������������������������������������ 115 ■Chapter ■ 7: Defining an Initial Plan and Roadmap����������������������� 139 ■Chapter ■ 8: Implementing the Plan���������������������������������������������� 165 ■Appendix ■ A: References�������������������������������������������������������������� 181 ■Appendix ■ B: Internet of Things Standards���������������������������������� 185 Index���������������������������������������������������������������������������������������������� 191
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Introduction The genesis of this book began in 2012. Hadoop was being explored in mainstream organizations, and we believed that information architecture was about to be transformed. For many years, business intelligence and analytics solutions had centered on the enterprise data warehouse and data marts, and on the best practices for defining, populating, and analyzing the data in them. Optimal relational database design for structured data and managing the database had become the focus of many of these efforts. However, we saw that focus was changing. For the first time, streaming data sources were seen as potentially important in solving business problems. Attempts were made to explore such data experimentally in hope of finding hidden value. Unfortunately, many efforts were going nowhere. The authors were acutely aware of this as we were called into many organizations to provide advice. We did find some organizations that were successful in analyzing the new data sources. When we took a step back, we saw a common pattern emerging that was leading to their success. Prior to starting Big Data initiatives, the organizations’ stakeholders had developed theories about how the new data would improve business decisions. When building prototypes, they were able to prove or disprove these theories quickly. This successful approach was not completely new. In fact, many used the same strategy when developing successful data warehouses, business intelligence, and advanced analytics solutions that became critical to running their businesses. We describe this phased approach as a methodology for success in this book. We walk through the phases of the methodology in eac
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