How do we design for data when traditional design techniques cannot extend to new database technologies? In this era of big data and the Internet of Things, it is essential that we have the tools we need to understand the data coming to us faster than ever before, and to design databases and data processing systems that can adapt easily to ever-changing data schemas and ever-changing business requirements. There must be no intellectual disconnect between data and the software that manages it. It must be possible to extract meaning and knowledge from data to drive artificial intelligence applications. Novel NoSQL data organization techniques must be used side-by-side with traditional SQL databases. Are existing data modeling techniques ready for all of this? The Concept and Object Modeling Notation (COMN) is able to cover the full spectrum of analysis and design. A single COMN model can represent the objects and concepts in the problem space, logical data design, and concrete NoSQL and SQL document, key-value, columnar, and relational database implementations. COMN models enable an unprecedented level of traceability of requirements to implementation. COMN models can also represent the static structure of software and the predicates that represent the patterns of meaning in databases. This book will teach you:
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Ted Hills has been active in the Information Technology industry since 1975. Starting with microprocessor design and bare metal programming, Ted moved gradually up through device drivers and operating systems to communications software, applications, and finally information architecture. Experience applying his top-to-bottom understanding of data, software, and computer architecture for many companies, including AT&T Bell Laboratories, Dow Jones, Bloomberg, Merrill Lynch, and Bank of America, has given Ted a deep understanding of the needs of modern business and of how to apply theory to practice. At LexisNexis, Ted co-leads the work of establishing enterprise data architecture standards and governance processes, working with data models and business and data definitions for both structured and unstructured data. Ted has always been an active researcher, with interests in software and data integration, data modeling notations, and improving the expressivity of languages while keeping them type-safe.
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