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Key Technologies for Data Management 21st British National Conference on Databases, BNCOD 21, Edinburgh, UK, July 7-9, 2004, Proceedings (Lecture Notes in Computer Science) by

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  • 29 Currently reading

Published by Springer .
Written in English

Subjects:

  • Computing and Information Technology,
  • Database Management - General,
  • Computers,
  • Computers - General Information,
  • Computer Books: Database,
  • Database management,
  • Computer Science,
  • General,
  • Computers / Database Management / General,
  • Congresses

Book details:

Edition Notes

ContributionsHoward Williams (Editor), Lachlan MacKinnon (Editor)
The Physical Object
FormatPaperback
Number of Pages265
ID Numbers
Open LibraryOL9623531M
ISBN 103540223827
ISBN 109783540223825

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As data managers, your goals include understanding and improving the management of information and data as key enterprise assets. Understanding how to manipulate data structures represents the next plateau in the use of data management technologies. Data managers will be taking on expanded roles. Data management is the process of ingesting, storing, organizing and maintaining the data created and collected by an organization. Effective data management is a crucial piece of deploying the IT systems that run business applications and provide analytical information to help drive operational decision-making and strategic planning by corporate executives, business Author: Margaret Rouse. Article 5 data management best practices to help you do data right Follow these 5 data management best practices to make sure your business data gives you great results from analytics.; Article Data lineage: Making artificial intelligence smarter For AI to reach its full potential, the data feeding its algorithms and models needs to be well-understood.. Data .   Data on file servers grows very quickly unless you have a plan to manage and control it with the right tools. Symptoms include increased backup times, Backups that just won’t run, Backup timeframes over 24 hours, Backup costs, server performance, server crash, restoration timeframes and management costs, to eventually a complete lack of storage space.

  Data management systems provide the key to utilizing data in its many, various forms. Strategic implementation of data management technologies can help your company achieve: Improved organizational consistency; Increased productivity; Greater collaboration and communication; Faster, more knowledgeable business decisions.   Rob,Peter and Coronel Carlis: Database Systems: Design, implementation and management - 4 th ed. Cambridge, Course Technology, (p ,) Abraham and others: Database System Concepts.   Data management is the function of planning, controlling, and delivering data effectively in an organization. Data management includes the following functions: practicing the disciplines in the development, execution, and supervision of plans, programs, policies and practices that protect, control, deliver and enhance the quality and value of.   Similar to David’s other books on data management; Master Data Management shares a deep understanding of how critical business issues are addressed through the managed integration of emerging technologies. This book provides a full-scale exposition on the benefits and the challenges of master data integration; describes approaches to justify Reviews:

  Other smart technologies such as customer surveys, smart loyalty-program management and smart hotel management will play a bigger role in how hotels operate in and beyond. The key to smarter hotel operations is implementing the right technologies that meet guests’ expectations and hoteliers’ needs to get to know these travelers better.   Data Management implies the definition of policies, roles, processes and responsibilities throughout the company on the definition and management of data. An effective data governance model requires a complete structure that facilitates collaboration between technology and business.   As the Director of Product Management for all data management offerings at SAS, Ron Agresta works closely with customers, partners and industry analysts to help research and developments teams at SAS develop data quality, data governance, data integration, data virtualization, and big data software and holds a master’s degree from North . Subject (key words) Data management, data life cycle Description (abstract) Handbook on data management for researchers. Follows ten steps of the Data Life Cycle (propose, collect, assure, describe, submit, preserve, discover, integrate, analyse, publish). Provides information as well as practical tips and further resources. Informs.