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Joe Celko's Data, Measurements and Standards in SQL
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"Unique? Without question. To my knowledge there is nothing out there quite like this. Further, based on his previous books, Joe is eminently qualified to put these "external world" ideas (standard codes used in industry) into the context of relational databases and SQL."--Rudy Limeback - An independent SQL Consultant "This book focuses on the problems of standardization and the related problems of measurements. It is clearly intended to encourage designers to at least be aware of the problems, before their database designs go live."--Computing Reviews
Product Description
Joe Celko has looked deep into the code of SQL programmers and found a consistent and troubling pattern - a frightening lack of consistency between their individual encoding schemes and those of the industries in which they operate. This translates into a series of incompatible databases, each one an island unto itself that is unable to share information with others in an age of internationalization and business interdependence. Such incompatibility severely hinders information flow and the quality of company data. "Data, Measurements and Standards in SQL" reveals the shift these programmers need to make to overcome this deadlock. By collecting and detailing the diverse standards of myriad industries, and then giving a declaration for the units that can be used in an SQL schema, Celko enables readers to write and implement portable data that can interface to any number of external application systems! This book doesn't limit itself to one subject, but serves as a detailed synopsis of measurement scales and data standards for all industries, thereby giving RDBMS programmers and designers the knowledge and know-how they need to communicate effectively across business boundaries. This title collects and details the diverse data standards of myriad industries under one cover, thereby creating a definitive, one-stop-shopping opportunity for database programmers. It enables readers to write and implement portable data that can interface to any number external application systems, allowing readers to cross business boundaries and move up the career ladder. It offers expert advice from one of the most-read SQL authors in the world who is well known for his ten years of service on the ANSI SQL standards committee and Readers Choice Award winning column in Intelligent Enterprise.
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3 reviews
3 of 3 people found the following review helpful
Comprehensive and user-friendly
28 Oct 2009
Format:Paperback
Part 1 covers the need, principles, and variety of measurement standards and Part 2 provides examples of actual standards across many industries such as language codes and phone numbers. This book is extremely informative and easy-to-read (I like Joe's writing style), and I found myself laughing out loud at several points in the book most notably around beer and Mad Magazine's metric system. As a data analyst and modeler, one of my tasks is to work with the business to understand and document existing domains as well as new and improved enterprise/industry domains. I will use this book as a reference in this endeavor.
Couldn't get past the author's condescending tone.
30 Mar 2012
Format:Paperback
The title review pretty much says it all for me, and the title of the book is a bit misleading as to the content you're actually getting. Not at all what I was hoping for.
Elusive title guarding valuable information
21 Mar 2011
Format:Paperback|Amazon Verified Purchase
The marketing speak in the description of this book is a bit confusing, and I worry that it leaves potential buyers unaware of what the book is really about. The book's title doesn't help much in this regard, either.
Database store data -- everyone knows that. There is some art in properly modeling and typing data so that it is represented consistently, flexibly, and efficiently in a database. This book endeavors to catalog different commonly used types of data, suggest an appropriate representation for that data, and describe the implementation of that representation as applied in a SQL database management server.
The first half of the book discusses different approaches that, in general, can help with the storage and representation of data. What are different approaches to help us handle data that's obvious bad or out of bounds? How can we best encode different data? What are good ways to represent values of vastly different scale? How can we efficiently validate certain types of data?
The advice presented in these first chapters makes it easy to extend the ideas of validation, storage, and efficient reference to any data type the user might encounter.
The balance of the book is divided into short chapters that examine different types of data. The book describes standards that influence the data stored; for example, for storing postal codes, the author examines Canadian, US, and UK schemes and discusses how they can be best represented and validated in a database. Clothing sizes are discussed by visiting the different dimensions and industry standards which govern the measurement and specification of these dimensions. All in all, more than 35 different types of data, ranging from spatial information to personal attributes, are examined.
The book is invaluable to database practitioners as they are often experts in the field of database work, but not experts in the domain modeled by the database. Most database engineers are not postal carriers or tailors, for example. The book facilitates the analysis and implementation of systems which involve domain- or industry-specific data, and I don't think there are many resources like it available.
Database store data -- everyone knows that. There is some art in properly modeling and typing data so that it is represented consistently, flexibly, and efficiently in a database. This book endeavors to catalog different commonly used types of data, suggest an appropriate representation for that data, and describe the implementation of that representation as applied in a SQL database management server.
The first half of the book discusses different approaches that, in general, can help with the storage and representation of data. What are different approaches to help us handle data that's obvious bad or out of bounds? How can we best encode different data? What are good ways to represent values of vastly different scale? How can we efficiently validate certain types of data?
The advice presented in these first chapters makes it easy to extend the ideas of validation, storage, and efficient reference to any data type the user might encounter.
The balance of the book is divided into short chapters that examine different types of data. The book describes standards that influence the data stored; for example, for storing postal codes, the author examines Canadian, US, and UK schemes and discusses how they can be best represented and validated in a database. Clothing sizes are discussed by visiting the different dimensions and industry standards which govern the measurement and specification of these dimensions. All in all, more than 35 different types of data, ranging from spatial information to personal attributes, are examined.
The book is invaluable to database practitioners as they are often experts in the field of database work, but not experts in the domain modeled by the database. Most database engineers are not postal carriers or tailors, for example. The book facilitates the analysis and implementation of systems which involve domain- or industry-specific data, and I don't think there are many resources like it available.
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