NoSQL and SQL Data Modeling Bringing Together Data Semantics and Software eBook Ted Hills
Download As PDF : NoSQL and SQL Data Modeling Bringing Together Data Semantics and Software eBook Ted Hills 
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
the simple and familiar graphical notation of COMN with its three basic shapes and four line styles- how to think about objects, concepts, types, and classes in the real world, using the ordinary meanings of English words that aren't tangled with confused techno-speak
how to express logical data designs that are freer from implementation considerations than is possible in any other notation
how to understand key-value, document, columnar, and table-oriented database designs in logical and physical terms
how to use COMN to specify physical database implementations in any NoSQL or SQL database with the precision necessary for model-driven development
"I believe that this is a breakthrough modeling technique - and it is technique, not just notation. COMN provides notation to handle all of the constructs that E-R techniques don't do well, and it steps up to the problem of linking physical and conceptual models. . . . I'm convinced that COMN
is the future of data modeling."
Dave Wells, BI and Analytics Educator and Consultant, Infocentric
NoSQL and SQL Data Modeling Bringing Together Data Semantics and Software eBook Ted Hills
This would have been a 5 star review if two things would have been addressed, one of content and one of format.The content would have been greatly enhanced if the example of the coffee shop went further into the actual implementation - with a top to bottom example that included actual document construction and related detail.
The other issue is that the kindle version does not render some of the shapes. There were sections that would say something like 'the shape with the dashed line.' But the figure would be solid. I have the hard copy as well but people reading only the ki ndle version are going to be confused.
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NoSQL and SQL Data Modeling Bringing Together Data Semantics and Software eBook Ted Hills Reviews
I am less a data modeler and more of a programmer, so this was a very interesting way for me to become enlightened about the challenges that arise from not using a good data model and the opportunities to use a complete modeling language like COMN that does a much better job in our new world of big data. With the arrival of new unstructured data types, and more on the way, this book is a necessary reference for how to build big data solutions.
This was all new thinking for me and somewhat challenging, but I liked this book because I got the sense of strong intellect on the other side gently introducing me to some very sophisticated new concepts. It is clear that Hills is a top expert in this field and has a real passion for his topic. I also really liked the way the book uses real world examples to show the limitations of current entity relationship modeling paradigms.
A must read for anyone building big data solutions that they want to be robust, scalable and stand the test of time.
Disclosure Before this book was published, I met the author in person while attending his COMN course at a conference. I suggested to him that he should meet Steve Hoberman and see if Steve’s Technics Publications might publish it. It was neat to learn that Technics did so, and I was happy to see Ted’s note on that in his acknowledgements.
This is a very specialized, yet indeed groundbreaking book on data modeling, and I believe it will serve as a valuable conceptual reference to keep data modeling abreast of current technology.
NoSQL technologies continue to experience rapid increases in adoption, but their prescribed data structures, in order to scale along with these NoSQL distributed data systems, to unprecedented levels of data throughput, depart radically from classic physical implementations of entity-relational and dimension data models. As they continue to gain market adoption, undoubtedly there will be an increased need to establish common conceptual and logical data models, and then markedly different physical data models to represent the data physically in NoSQL technologies, in order to provide the benefits of a good data model shared understanding, standardization, extensibility to related data subject areas, load performance, query performance, and a straightforward interoperability with relational databases, which continue to be the bulwark back-end for transactional processing.
Unfortunately, but for very good reason, most or all traditional data modeling products cannot even express many prevalent NoSQL model patterns, such as indeterminate levels of nested sub-attributes, as well as situations where some records contain a different set of attributes than other records within a single table or file. The reason, of course, is that those NoSQL physically-instantiated model patterns themselves radically depart from the classic physical data model patterns in relational or dimensional, models. So, where does this leave the enterprise data architect who is supposed to establish a roadmap for enterprise data management? Where does that leave the typical data modeler – the vast majority of whom are familiar mostly with entity-relational modeling, but who is now supposed to design for interoperability between NoSQL and relational data? When this data modeler perceives that some of the NoSQL modeling notation looks more like UML (Unified Modeling Language), wherein objects, types and variables have a maddeningly divergent meaning than in entity-relationship data modeling, it only adds yet another, unfortunately long-standing area of confusion. Although it will surprise nobody to learn that early attempts by data modelers to establish common model patterns or design for logical interoperability between these disparate systems will not quickly bear fruit, the need for that interoperability and standardization will not go away simply because it is difficult.
The point where we acknowledge that (1) the gap between RDBMS and NoSQL design is not superficial, that (2) it goes far deeper than simply a feature gap in the data modeling tools -- but rather in the underlying terminology and symbols of data modeling, and that (3) we must continue to build models to reap maximize value from our data solutions – is the point at which we turn to Ted Hills and this ground-breaking book. We simply cannot build the understandable data models that lead to well-designed, highly interoperable data systems, without doing so.
Whether a reader is a relational data modeler, an object-oriented programmer, a UML-modeler, or a NoSQL Architect, Ted Hills guides each reader to a common set of concepts, and most specifically, the flexible and semantically robust Common Objective Modeling Notation (COMN) that Tedd Hills has invented.
This is the definitive book for anyone seeking a modeling technique that works with the complexities of big data. There are so many things in the NoSQL world that just don't fit into entity-relationship and star-schema models. The first challenge is modeling to understand and describe existing data instead of modeling to design databases. But that is the reality of big data -- it exists without models and usually with insufficient metadata. Next we are challenged by data constructs that don't fit neatly into entity-relationship structures including many-to-many relationships, multi-valued attributes, embedded arrays, associations implemented without foreign key relationships, and much more. Key-value stores, document stores, graph databases, etc. just aren't easily described with ER modeling. Ted Hills has developed an extension of object modeling that he calls Concept and Object Modeling Notation (COMN) that elegantly steps up to the needs of big data modeling. He presents the notation and the modeling technique in a way that is clear and easily understood for a variety of people with different backgrounds and data experiences.
Some thoughts from an earlier review and TDAN blog are included in the book description above. But I had the urge to say more. I had the opportunity to review the manuscript before publishing and to get to know Ted Hills. I learned from this book and I've been a data modeler for more than 30 years. Reading the book expanded my knowledge and getting to know Ted enriched my professional network. Good stuff all around!
This is a solid conceptual overview of data modeling in general with advice for those looking toward combining SQL and NoSQL. (I suppose the title of the book is pretty apt.)
This would have been a 5 star review if two things would have been addressed, one of content and one of format.
The content would have been greatly enhanced if the example of the coffee shop went further into the actual implementation - with a top to bottom example that included actual document construction and related detail.
The other issue is that the kindle version does not render some of the shapes. There were sections that would say something like 'the shape with the dashed line.' But the figure would be solid. I have the hard copy as well but people reading only the ki ndle version are going to be confused.
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