English
资源说明：W.H. INMON
DANIEL LINSTEDT
Corporate data – the vista of information across the entire corporation.
There are many different types of data found in the
corporation. The book lays out one perspective of data and describes
– at a very high level – how that data is used (and is not
used) in the decision-making process of the corporation.
Big Data – what is it and how can it enhance decision making
in the corporation. There are different definitions of Big Data.
This book takes a very pragmatic view of Big Data then discusses
some salient characteristics of it. The most salient characteristic
– one not discussed by the vendors – is that of the
difference of repetitive and non-repetitive Big Data. Profound
differences between repetitive and non-repetitive Big Data is
herein called the “great divide.” This book is worth buying for
no other reason than simply to understand this “great divide”
and its implications to the decision-making ability of the corporation.
Data warehouse – the need for corporate integrity of data.
One day, corporations awoke to the fact having data was not
the same thing as having believable data. They awoke to discover
the meaning of “data integrity.” That was the day the enterprise
data warehouse (EDW) was born. With an EDW, corporations
had the bedrock data on which to make important
PREFACE xix
and trustworthy decisions. Prior to the EDW, corporations had
plenty of data, but the data was not believable.
Data vault – the need for managing the change of data over
time. Data warehouses evolved over time. The ultimate in the
evolution of data warehousing was the discipline and structure
known as the “data vault.” There were and are many reasons to
have the data vault as the backbone of the systems that require
integrity.
Operational systems – the need to run the corporation’s dayto-
day business. For all the needs of managing very large data
volumes and for data integrity requirements, there is (and will
continue to be) a need to have systems that run and enhance
the day-to-day operations of the organization.
Architecture – how the different types of data and the different
needs for data are fitted together, in a holistic and a cohesive
way. It is one thing to recognize the different needs of perspectives
of data in the corporation. It is another thing to envision
how the different types of data fit together in a cohesive, holistic
manner.
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