swiss-city.info: DAMA-DMBOK: Data Management Body of Knowledge (2nd Edition) a Kindle? Get your Kindle here, or download a FREE Kindle Reading App. The equivalent of the PMBOK or the BABOK, the DAMA-DMBOK provides information on: . Get your Kindle here, or download a FREE Kindle Reading App. Jul 7, DAMA International Guide to Data Management Body of Knowledge (DAMA DMBOK ®); DAMA International Dictionary of Data Management.
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Mar 17, Grammar, obvious errors, enhanced, questions re. ”methods”, roles, regulations, owners, diagrams and expanded some content outline. DAMA International xvii DAMA-DMBOK Guide Thank you to all the present and and began with a white paper framework published as a free download on our DAMA website. eBook available only in electronic form from www. May 26, Download Read DAMA-DMBOK: Data Management Body of Knowledge (2nd Edition) | Ebook PDF Free Download Here.
DAMA International is dedicated to advancing the concepts and practices of information and data management and supporting DAMA members and their organizations to address their information and data management needs. To fulfill this mission, DAMA-I sponsors and facilitates the development of bodies of knowledge through its community of experts as well as developing certification and training programs. DAMA DMBOK defines a standard industry view of data management functions, terminology and best practices, without detailing specific methods and techniques. Over terms defining a common data management vocabulary for IT professionals, data stewards and business leaders. Over 40 topics including finance and accounting, knowledge management, architecture, data modeling, XML, and analytics. The Dictionary is available as individual editions: CD or hardcopy can also be purchased through Amazon.
Show details Buy the selected items together This item: Data Governance: Customers who viewed this item also viewed Page 1 of 1 Start over Page 1 of 1 This shopping feature will continue to load items. In order to navigate out of this carousel please use your heading shortcut key to navigate to the next or previous heading. Seiner 4. The primary purpose of DAMA International is to promote the understanding, development, and practice of managing data and information to support business strategies.
DAMA International has chapters throughout the world. DAMA members network with other professionals to share ideas, trends, problems, and solutions.
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Would you like to tell us about a lower price? If you are a seller for this product, would you like to suggest updates through seller support? It provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure. To build consensus for a generally applicable view of data management functions. To provide standard definitions for commonly used data management functions, deliverables, roles, and other terminology.
To document guiding principles for data management. To present a vendor-neutral overview to commonly accepted good practices, widely adopted methods and techniques, and significant alternative approaches.
To clarify the scope and boundaries of data management. To act as a reference which guides readers to additional resources for further understanding.
DMBOK and other frameworks including TOGAF & COBIT - keynote from…
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Data Management Body of Knowledge 2nd Edition. John Ladley. Sunil Soares. Management Information Systems for the Information Age. Maeve Haag Stephen;. Navigating the Labyrinth: An Executive Guide to Data Management. Non-Invasive Data Governance. About the Author DAMA International is a not-for-profit, vendor-independent association of technical and business professionals dedicated to advancing the concepts and practices for data resource management and enterprise information.
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Perfect Paperback Verified Purchase. For decades, having a comprehensive and integrated approach for data management was the holy grail for IT professionals. Things that I hope the next editions of this wonderful guide to focus on are: How to incrementally implement MDM to align with business priorities. Provision of Business Intelligence BI to the enterprise and the manner in which data consumed by BI solutions and the resulting reports are managed.
Particularly important if the data is replicated into a Data Warehouse. Provision of metadata repositories and the means of providing business user access and glossaries from these.
The development, use and exploitation of data models, ranging from Enterprise, through Conceptual to Logical, Physical and Dimensional. Maturity assessment to consider the way in which models are utilized in the enterprise and their integration in the Software Development Life Cycle SDLC. Data Architecture Management: Approaches, plans, considerations and guidelines for provision of Data Integration and access.
Data Lifecycle Management: Proactive planning for the management of Data across its entire lifecycle from inception through, acquisition, provisioning, exploitation eventually to destruction. This IM discipline and its maturity assessment determine how well this is planned for and accomplished. Identification of threats and the adoption of defences to prevent unauthorized access, use or loss of data and particularly abuse of personal data.
Regulatory Compliance: The polices and assurance processes that the enterprise is required to meet. Adapting to the changing legal and regulatory requirements related to information and data. Data Risk Management: Identification of risks not just security to data and its use, together with risk mitigation, controls and reporting.
Examination of the categories of tools supporting the IM disciplines. How to select the appropriate toolset. Discussion of an example policy for use of specific technology to ensure consistency and interoperability across the enterprise.
A new discipline introduced into DMBoK 2. The applicability of the different approaches, issues and implications of each will be discussed together with an outline of the technologies that support these styles of integration. What is the relationship between a data model and other types of models?
Modeling basics, major constructs, identifying entities, model levels and linkage between them. When is it appropriate, what are the limitations. When this works, where is it appropriate.
DAMA-DMBOK (2nd Edition): Data Management Body of Knowledge
Is this always the best approach for requirements? How to select the fact fining approach and when the are and are not appropriate. Why mastering this construct can provide phenomenal flexibility. Different approaches for modelling hierarchies.
Progressing beyond 3NF. Case studies on other uses. A 1 day foundation class in Data Modelling to give practitioners an overview of Data Modelling, one of the most crucial of the Information Management disciplines. Data Modeling Foundation 1 day: What is Data Modelling, Why is Important, What areas are impacted and influenced by Data models, what are the benefits and uses of data models. What are the different types and why and when are they appropriate. The major constructs in data models.
The class covering the need for Data Governance, its outcome, typical organization structures for Data Governance, the roles responsibilities and activities involved in establishing successful Data Governance, and metrics for measuring progress of a Data Governance initiative.
The 2 day class explores a Framework for and how to get started with Data Governance. Now its started; how do you sustain Data Governance. A 1 day foundation class or 2 day practitioner class covering the different MDM architectures, genres, applications and activities involved in running a successful Master Data Management initiative.
These vary from a full central hub, through hybrid to virtualised with many flavours and variants along the way. The issues and implications associated with the different approaches and why getting this right impacts future MDM success.
A 1 day foundation class or 2 day practitioner class covering the principles, processes and activities involved in creating a Data Quality function.
How could these have been avoided? New for DMBoK 2. A 1 day foundation class or 2 day practitioner class covering the considerations for Data Integration, the different architectures available and their applicability. Discuss the technologies, and activities involved in Data Integration and migration. The 2 day class also explores use cases of the differing Data Integration architectures.
The workshops introduce the Information Management topic, its drivers, benefits and actions organizations should take to ensure Information is managed as a key asset. 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: Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas.
Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics. Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals.
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: Data is an asset with unique properties The value of data can be and should be expressed in economic terms Managing data means managing the quality of data It takes metadata to manage data It takes planning to manage data Data management is cross-functional and requires a range of skills and expertise Data management requires an enterprise perspective Data management must account for a range of perspectives Data management is data lifecycle management Different types of data have different lifecycle requirements Managing data includes managing risks associated with data Data management requirements must drive information technology decisions Effective data management requires leadership commitment Chapters include: It will also enable organizational leaders to recognize the value and contributions of data management activities.
Read more Read less. Frequently bought together. Total price: Add all three to Cart Add all three to List. Buy the selected items together This item: Data Governance: Customers who bought this item also bought. Page 1 of 1 Start over Page 1 of 1. John Ladley. Sunil Soares.
Non-Invasive Data Governance. Data Stewardship: Navigating the Labyrinth: An Executive Guide to Data Management. About the Author DAMA International is a not-for-profit, vendor-independent association of technical and business professionals dedicated to advancing concepts and practices related to managing data and information in support of business strategy.
Read more. Product details Paperback: Technics Publications; Second edition July 1, Language: English ISBN Tell the Publisher! I'd like to read this book on Kindle Don't have a Kindle? Share your thoughts with other customers. Write a customer review. Top Reviews Most recent Top Reviews.
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