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Usage-Driven Database Design - From Logical Data Modeling through Physical Schema Definition (Paperback, 1st ed.)
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Usage-Driven Database Design - From Logical Data Modeling through Physical Schema Definition (Paperback, 1st ed.)
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Design great databases-from logical data modeling through physical
schema definition. You will learn a framework that finally cracks
the problem of merging data and process models into a meaningful
and unified design that accounts for how data is actually used in
production systems. Key to the framework is a method for taking the
logical data model that is a static look at the definition of the
data, and merging that static look with the process models
describing how the data will be used in actual practice once a
given system is implemented. The approach solves the disconnect
between the static definition of data in the logical data model and
the dynamic flow of the data in the logical process models. The
design framework in this book can be used to create operational
databases for transaction processing systems, or for data
warehouses in support of decision support systems. The information
manager can be a flat file, Oracle Database, IMS, NoSQL, Cassandra,
Hadoop, or any other DBMS. Usage-Driven Database Design emphasizes
practical aspects of design, and speaks to what works, what doesn't
work, and what to avoid at all costs. Included in the book are
lessons learned by the author over his 30+ years in the corporate
trenches. Everything in the book is grounded on good theory, yet
demonstrates a professional and pragmatic approach to design that
can come only from decades of experience. Presents an end-to-end
framework from logical data modeling through physical schema
definition. Includes lessons learned, techniques, and tricks that
can turn a database disaster into a success. Applies to all types
of database management systems, including NoSQL such as Cassandra
and Hadoop, and mainstream SQL databases such as Oracle and SQL
Server What You'll Learn Create logical data models that accurately
reflect the real world of the user Create usage scenarios
reflecting how applications will use a new database Merge static
data models with dynamic process models to create resilient yet
flexible database designs Support application requirements by
creating responsive database schemas in any database architecture
Cope with big data and unstructured data for transaction processing
and decision support systems Recognize when relational approaches
won't work, and when to turn toward NoSQL solutions such as
Cassandra or Hadoop Who This Book Is For System developers,
including business analysts, database designers, database
administrators, and application designers and developers who must
design or interact with database systems
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