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Books > Computing & IT > General theory of computing
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Meeting the Challenges of Data Quality Management (Paperback)
Loot Price: R1,265
Discovery Miles 12 650
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Meeting the Challenges of Data Quality Management (Paperback)
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Meeting the Challenges of Data Quality Management outlines the
foundational concepts of data quality management and its
challenges. The book enables data management professionals to help
their organizations get more value from data by addressing the five
challenges of data quality management: the meaning challenge
(recognizing how data represents reality), the process/quality
challenge (creating high-quality data by design), the people
challenge (building data literacy), the technical challenge
(enabling organizational data to be accessed and used, as well as
protected), and the accountability challenge (ensuring
organizational leadership treats data as an asset). Organizations
that fail to meet these challenges get less value from their data
than organizations that address them directly. The book describes
core data quality management capabilities and introduces new and
experienced DQ practitioners to practical techniques for getting
value from activities such as data profiling, DQ monitoring and DQ
reporting. It extends these ideas to the management of data quality
within big data environments. This book will appeal to data quality
and data management professionals, especially those involved with
data governance, across a wide range of industries, as well as
academic and government organizations. Readership extends to people
higher up the organizational ladder (chief data officers, data
strategists, analytics leaders) and in different parts of the
organization (finance professionals, operations managers, IT
leaders) who want to leverage their data and their organizational
capabilities (people, processes, technology) to drive value and
gain competitive advantage. This will be a key reference for
graduate students in computer science programs which normally have
a limited focus on the data itself and where data quality
management is an often-overlooked aspect of data management
courses.
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