The official definition provided by DAMA International, the professional organization for those in the data management profession, is: Data Resource Management is the development and execution of architectures, policies, practices and procedures that properly manage the full data lifecycle needs of an enterprise. This definition is fairly broad and encompasses a number of professions which may not have direct technical contact with lower-level aspects of data management, such as relational database management. Alternatively, the definition provided in the DAMA Data Management Body of Knowledge (DAMA-DMBOK) is: Data management is the development, execution and supervision of plans, policies, programs and practices that control, protect, deliver and enhance the value of data and information assets.
This book is your ultimate resource for Data Management. Here you will find the most up-to-date information, analysis, background and everything you need to know.
In easy to read chapters, with extensive references and links to get you to know all there is to know about Data Management right away, covering: Data management, Abstraction (computer science), ADO.NET, ADO.NET data provider, WCF Data Services, Age-Based Content Rating System, Data archaeology, Archive site, Association rule learning, Atomicity (database systems), Australian National Data Service, Automated Tiered Storage, Automatic data processing, Automatic data processing equipment, BBC Archives, Bitmap index, British Oceanographic Data Centre, Business intelligence, Business Intelligence Project Planning, Change data capture, Chunked transfer encoding, Cleansing and Conforming Data, Client-side persistent data, Clone (database), Cloud Data Management Interface, Cognos Reportnet, Commit (data management), Commitment ordering, The History of Commitment Ordering, Comparison of ADO and ADO.NET, Comparison of OLAP Servers, Comparison of structured storage software, Computer-aided software engineering, Concurrency control, Conference on Innovative Data Systems Research, Consumer Relationship System, Content Engineering, Content format, Content inventory, Content management, Content Migration, Content re-appropriation, Content repository, Control break, Control flow diagram, Copyright, Core Data, Core data integration, Customer data management, DAMA, Dashboard (business), Data, Data access, Data aggregator, Data architect, Data architecture, Data auditing, Data bank, Data binding, Data center, Data classification (data management), Data conditioning, Data custodian, Data deduplication, Data dictionary, Data exchange, Data extraction, Data field, Data flow diagram, Data governance, Data independence, Data integration, Data library, Data maintenance, Data management plan, Data mapping, Data migration, Data processing system, Data profiling, Data proliferation, Data recovery, Data Reference Model, Data retention software, Data room, Data security, Data set (IBM mainframe), Data steward, Data storage device, Data Stream Management System, Data Transformation Services, Data Validation and Reconciliation, Data verification, Data virtualization, Data visualization, Data warehouse, Database administration and automation, Database administrator, Database engine, Database schema, Database server, Database transaction, Database-centric architecture, Disaster recovery, Distributed concurrency control, Distributed data store, Distributed database, Distributed file system, Distributed transaction, DMAPI, Document capture software, Document-oriented database, Durability (database systems), Dynamic Knowledge Repository, Dynomite, Edge data integration...and much more
This book explains in-depth the real drivers and workings of Data Management. It reduces the risk of your technology, time and resources investment decisions by enabling you to compare your understanding of Data Management with the objectivity of experienced professionals.
