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Unlike some other reproductions of classic texts (1) We have not
used OCR(Optical Character Recognition), as this leads to bad
quality books with introduced typos. (2) In books where there are
images such as portraits, maps, sketches etc We have endeavoured to
keep the quality of these images, so they represent accurately the
original artefact. Although occasionally there may be certain
imperfections with these old texts, we feel they deserve to be made
available for future generations to enjoy.
Unlike some other reproductions of classic texts (1) We have not
used OCR(Optical Character Recognition), as this leads to bad
quality books with introduced typos. (2) In books where there are
images such as portraits, maps, sketches etc We have endeavoured to
keep the quality of these images, so they represent accurately the
original artefact. Although occasionally there may be certain
imperfections with these old texts, we feel they deserve to be made
available for future generations to enjoy.
Unlike some other reproductions of classic texts (1) We have not
used OCR(Optical Character Recognition), as this leads to bad
quality books with introduced typos. (2) In books where there are
images such as portraits, maps, sketches etc We have endeavoured to
keep the quality of these images, so they represent accurately the
original artefact. Although occasionally there may be certain
imperfections with these old texts, we feel they deserve to be made
available for future generations to enjoy.
Data is an expensive and expansive asset. Information capture
has forced storage capacity from megabytes to terabytes, exabytes
and, pretty soon, zetabytes of data. So the need for accessible
storage space for this data is great. To make this huge amount of
data usable and relevant, it needs to be organized effectively.
Database Base Management Systems, such as Oracle, IBM s DB2, and
Microsoft SqlServer are used often, but these are being enhanced
continuously and auxiliary tools are being developed every week;
there needs to be a fundamental starting point for it all. That
stating point is Data Architecture, the blueprint for organizing
and structuring of information for services, service providers, and
the consumers of that data.
"Data Architecture: From Zen to Reality" explains the principles
underlying data architecture, how data evolves with organizations,
and the challenges organizations face in structuring and managing
their data. It also discusses proven methods and technologies to
solve the complex issues dealing with data. The book uses a
holistic approach to the field of data architecture by covering the
various applied areas of data, including data modelling and data
model management, data quality, data governance, enterprise
information management, database design, data warehousing, and
warehouse design. This book is a core resource for anyone
emplacing, customizing or aligning data management systems, taking
the Zen-like idea of data architecture to an attainable
reality.
Presents fundamental concepts of enterprise architecture with
definitions and real-world applications and scenariosTeaches data
managers and planners about the challenges of building a data
architecture roadmap, structuring the right team, and building a
long term set of solutions Includes the detail needed to illustrate
how the fundamental principles are used in current business
practice"
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