Dama dmbok pdf free download

Environmental Elements Knowledge Area Chapter Structure Knowledge Area Context Diagram Format Environmental Elements — Scope Detail Deleted Section 4. Data Management is an overarching term that describes the processes used to plan, specify, enable, create, acquire, maintain, use, archive, retrieve, control, and purge data. These processes overlap and interact within each data management knowledge area see section 4.

Whether known as Data Management, Data Resource Management, or Enterprise Information Management, organizations increasingly recognize that the data they possess is a valuable asset which must be managed properly to ensure success.

Businesses, governments, and other organizations are more effective when they leverage their data assets. Data Management is a maturing discipline. Data Management exists within a broader social context, and a broader landscape of technology adoption and use, community, and collaboration. Data Management concepts and supporting technology have evolved quickly over the last thirty years, and continue to evolve.

Creating a formal, certified, recognized, and respected data management discipline is not an easy task. The current environment can be a confusing combination of terms, methods, tools, opinion, and hype.

Executives, in particular, need to understand and assign value to data management activities, in order to fully support, fund, and staff the data management function. Moreover, standardization will also help us communicate with our teammates, managers, and executives, and ubiquitous use will elevate Data Management into a formal discipline around the world.

A Fra e ork hite paper as ritte a d floated to the data a age e t o u ity for o e t a d i put, and became the basis for the first publication. In order to ensure the work is an accurate reflection of the profession, it is essential to gain community consensus for the Framework that becomes the foundation of the document. The first edition was more concerned with outlining the functions of data management.

These ele e ts, along with the context diagram and activity groups, describe the data management processes and activities that are involved in a knowledge area. The entire body of knowledge about data management is quite large and constantly growing. It presents a standard industry view of data management knowledge areas, terminology, and common best practices, without going into implementation details.

Instead, it points readers to widely recognized publications, articles, and other resources for further reading on the HOW-TO methods and implementation details. DAMA also encourages communities of practice discussions on the topics presented. To build consensus for a generally applicable view of data management knowledge areas.

To provide standard definitions for commonly used data management knowledge areas, deliverables, roles, and other terminology, in conjunction with the DAMA Dictionary of Data Management, and thus, to move the Data Management Community towards standardization on concepts and activities.

To identify guiding principles for data management. To clarify the scope and boundaries of data management activities. To provide an overview of commonly accepted good practices, widely adopted techniques, and significant alternative approaches, without reference to specific technology vendors or their products.

To provide common organizational and cultural issues. To identify strategies for data management maturity analysis. To provide additional resources and reference material for further understanding of data management. Researchers in the field of data management. Professional CDMP data exams. Proposed Framework 4. This process was captured in 10 functions and associated activities. A knowledge area is a category of specialization.

It could be made up of one or more topics, which will be handled in separate sections. Each knowledge area has section topics that logically group activities. There is also an additional Data Management section containing topics that describe the knowledge requirements for data management professionals. The new Knowledge area is Data Integration and Interoperability. While we understand that governance covers pro esses , ot thi gs , the o o ter for Data Ma age e t Go er a e is Data Governance, and so we will use this term.

Context Diagrams Each knowledge area has a context diagram that outlines and frames the scope of that area. The diagram format is more tailored to describing the processes in terms of inputs documents and plans , outputs documents and products , business drivers goals, regulations, and standards , tools and techniques. Regulations and Industry Standards will be moved from Inputs into new categories.

Metrics will be enhanced. Primary Deliverables are renamed Deliverables, as they were not listed with any contrasting secondary deliverables. Finally, the level of detail on the diagrams will be kept to a very high level, consistent with an overview, and consistent across knowledge areas.

The text will provide more detail. If appropriate, a sub-topic section of a knowledge area may have its own context diagram for clarity. Activity Groups In the center of each context diagram, there is a box listing the processes for that knowledge area and topic. Planning activities may be performed on an iterative basis. Environmental Elements The seven Environmental Elements provide a logical and consistent way to describe each knowledge area.

You can choose to read online or you can use to download so it will be readily available to you anytime you need it. And all this available to you free with no restrictions such as cost and registration that other websites offer you. They recognize data has value and they want to leverage that value. As our ability and desire to create and exploit data has increased, so too has the need for reliable data management practices. An accessible, authoritative reference book written by leading thinkers in the field and extensively reviewed by DAMA members, DMBOK2 brings together materials that comprehensively describe the challenges of data management and how to meet them by:.

DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles:.