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How DAMA-DMBOK Can Help You Achieve Excellence in Data Management (2nd Edition)


DAMA-DMBOK: Data Management Body of Knowledge (2nd Edition)




Data is an essential asset for any organization that wants to succeed in the digital age. Data can provide insights, enable innovation, improve decision-making, and create value. However, data also comes with challenges, such as complexity, quality, security, integration, governance, and ethics. How can organizations manage their data effectively and efficiently?




DAMA-DMBOK: Data Management Body Of Knowledge (2nd Edition).mobi



One of the best guides for data management is the DAMA-DMBOK: Data Management Body of Knowledge (2nd Edition), published by DAMA International in 2017. This book presents a comprehensive view of the concepts and practices of data management, based on the experience and expertise of leading practitioners in the field. In this article, we will introduce what DAMA-DMBOK is, how to apply it in practice, and how to learn more about it.


What is DAMA-DMBOK?




DAMA-DMBOK is an acronym for Data Management Association - Data Management Body of Knowledge. It is a reference book that describes the best practices for data management across 11 functional areas, such as data governance, data architecture, data quality, data security, data integration, metadata management, and more. It also provides a common vocabulary, a functional framework, a maturity model, and a set of guiding principles for data management.


The purpose and scope of DAMA-DMBOK




The purpose of DAMA-DMBOK is to help data management professionals and their organizations to address their data management needs and challenges. It is not a prescriptive methodology or a one-size-fits-all solution. Rather, it is a flexible and adaptable guide that can be tailored to different contexts, domains, industries, and technologies.


The scope of DAMA-DMBOK covers the entire lifecycle of data, from creation to disposal. It also covers all types of data, such as structured, unstructured, semi-structured, big data, master data, reference data, etc. It applies to both internal and external data sources and stakeholders. It supports both operational and analytical data use cases.


The structure and content of DAMA-DMBOK




The structure of DAMA-DMBOK consists of 12 chapters. The first chapter introduces the data management overview and context. The next 11 chapters cover each of the 11 functional areas of data management in detail. Each chapter follows a similar format: definition, objectives, scope, activities, roles, deliverables, metrics, best practices, challenges, trends, and references.


The content of DAMA-DMBOK is based on the collective wisdom and experience of hundreds of contributors from various backgrounds and regions. It is also extensively reviewed by thousands of members from the DAMA International community. It reflects the current state-of-the-art knowledge and practices of data management.


The benefits and challenges of using DAMA-DMBOK




Some of the benefits of using DAMA-DMBOK are:



  • It provides a comprehensive and consistent view of data management.



  • It helps to align data management with business goals and strategies.



  • It helps to improve data quality, reliability, usability, and value.



  • It helps to reduce data risks, costs, and complexity.



  • It helps to enhance data collaboration, communication, and integration.



  • It helps to foster a data-driven culture and mindset.



Some of the challenges of using DAMA-DMBOK are:



  • It requires a significant investment of time, resources, and commitment.



  • It requires a high level of data management skills and expertise.



  • It requires a strong data governance and leadership support.



  • It requires a continuous improvement and adaptation process.



  • It may encounter resistance or misunderstanding from some stakeholders.



How to apply DAMA-DMBOK in practice?




DAMA-DMBOK is not a step-by-step instruction manual or a cookbook. It is a reference guide that can be used in different ways depending on the needs and objectives of each organization. However, there are some common elements that can help to apply DAMA-DMBOK in practice, such as the data management principles, functions, roles, processes, deliverables, and metrics.


The data management principles and functions




DAMA-DMBOK defines 10 guiding principles for data management. These are:



  • 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.



DAMA-DMBOK also defines 11 functional areas for data management. These are:



  • Data Governance: The exercise of authority, control, and shared decision making over the management of data assets.



  • Data Architecture: The design of data structures, models, standards, policies, rules, and processes that govern the creation, storage, access, integration, and usage of data.



  • Data Modeling and Design: The analysis, representation, and specification of the structure, meaning, relationships, and constraints of data within a given domain or context.



  • Data Storage and Operations: The implementation, maintenance, backup, recovery, performance tuning, security, and administration of physical data assets.



  • Data Security: The protection of data assets from unauthorized access, use, disclosure, modification, or destruction.



  • Data Integration and Interoperability: The acquisition, extraction, transformation, movement, delivery, replication, federation, virtualization, and harmonization of data from various sources and formats across systems and boundaries.



  • Document and Content Management: The capture, storage, retrieval, distribution, preservation, and disposition of unstructured or semi-structured digital information objects such as documents, images, videos, audio files, web pages, etc.



  • Reference and Master Data: The identification, definition, maintenance, and governance of authoritative and reusable data values that represent the core entities of an organization such as customers, products, suppliers, employees, locations, etc.



  • Data Warehousing and Business Intelligence: The collection, integration, analysis, and presentation of historical or current data to support business decision making and performance measurement through various techniques such as reporting, dashboards, scorecards, data mining, predictive analytics, etc.



  • Metadata Management: The definition, control, maintenance, and usage of the information that describes the characteristics, structure, meaning, quality, lineage, relationships, and usage of data assets.



  • Data Quality Management: The planning, implementation, monitoring, measurement, evaluation, and improvement of the accuracy, completeness, consistency, timeliness, validity, and fitness for purpose of data assets.



The data management roles and responsibilities




DAMA-DMBOK identifies several roles that are pertinent to data management. These are not positions, but rather functions that can be performed by different people depending on the size and structure of the organization. Some of these roles are:



  • Data management leader. This is a senior-level role that provides strategic direction, oversight, and coordination for data management activities across the organization. This role is responsible for establishing and enforcing data management policies, standards, and best practices. This role also communicates the value and benefits of data management to stakeholders and sponsors.



  • Data steward. This is a business-oriented role that defines, monitors, and maintains the quality, integrity, and usability of data assets within a specific domain or context. This role is responsible for understanding the business requirements and rules for data, as well as ensuring compliance with data governance policies and regulations. This role also collaborates with data producers and consumers to resolve data issues and improve data processes.



  • Data architect. This is a technical role that designs, develops, and maintains the logical and physical data models, structures, standards, and schemas that support the data needs of the organization. This role is responsible for ensuring alignment between the data architecture and the business architecture, as well as ensuring integration and interoperability among data sources and systems.



  • Data engineer. This is a technical role that implements, operates, and supports the data storage, processing, and movement solutions that enable data access and usage across the organization. This role is responsible for ensuring performance, availability, scalability, security, and reliability of data platforms and pipelines.



  • Data analyst. This is a business-oriented role that explores, analyzes, interprets, and presents data to support business decision-making and performance measurement. This role is responsible for understanding the business questions and objectives, as well as selecting, transforming, and visualizing the relevant data sources and methods.



  • Data scientist. This is a technical role that applies advanced statistical, mathematical, and computational techniques to discover patterns, trends, anomalies, and insights from large and complex data sets. This role is responsible for developing, testing, and deploying data-driven models, algorithms, and applications that provide predictive or prescriptive solutions to business problems.



The data management processes and deliverables




DAMA-DMBOK defines a set of processes and deliverables for each of the 11 functional areas of data management. These processes and deliverables describe the activities and outputs that are involved in planning, executing, monitoring, and controlling data management projects and operations. Some examples of these processes and deliverables are:



Functional Area


Process


Deliverable


Data Governance


Establish data governance framework


Data governance charter


Data Architecture


Design data architecture


Data architecture blueprint


Data Modeling and Design


Create data models


Data model diagrams and specifications


Data Storage and Operations


Implement data storage solutions


Data storage schemas and scripts


Data Security


Define data security policies and rules


Data security policy document


Data Integration and Interoperability


Develop data integration solutions


Data integration workflows and mappings


Document and Content Management


Manage document lifecycle


Document metadata and classification scheme


Reference and Master DataMaintain reference and master data valuesReference and master data catalogData Warehousing and Business IntelligenceAnalyze data for business insightsData analysis reports and dashboardsMetadata ManagementCapture and store metadataMetadata repository and dictionaryData Quality ManagementAssess and improve data qualityData quality assessment report and improvement plan


The data management metrics and maturity assessment




DAMA-DMBOK defines a set of metrics and maturity assessment for data management. These are tools that help to measure and evaluate the performance, progress, and value of data management activities and outcomes. Some examples of these metrics and maturity assessment are:



  • Data management key performance indicators (KPIs). These are quantifiable measures that indicate how well data management objectives are being achieved. They can be used to monitor and report on data management activities, such as data quality improvement, data integration efficiency, data security compliance, etc.



  • Data management balanced scorecard (BSC). This is a strategic management tool that aligns data management goals with business goals and provides a holistic view of data management performance across four perspectives: financial, customer, internal process, and learning and growth.



  • Data management return on investment (ROI). This is a financial measure that evaluates the benefits and costs of data management initiatives. It can be used to justify and prioritize data management investments, as well as to demonstrate the value and impact of data management to stakeholders.



  • Data management maturity model (DMMM). This is a framework that assesses the current state and desired state of data management capabilities across the 11 functional areas. It can be used to identify gaps and opportunities for improvement, as well as to define roadmaps and action plans for data management advancement.



How to learn more about DAMA-DMBOK?




DAMA-DMBOK is a valuable resource for data management professionals and organizations, but it is not the only one. There are many other ways to learn more about DAMA-DMBOK and data management in general, such as:


The DAMA International organization and community




DAMA International is a global not-for-profit organization that aims to advance the concepts and practices of data management and support data management professionals and their organizations. DAMA International has various branches and chapters around the world that offer local events, networking, and learning opportunities. DAMA International also organizes annual conferences, webinars, publications, and awards to showcase and share the latest developments and best practices in data management.


The DAMA certification and training programs




DAMA International offers a professional certification program for data management professionals called the Certified Data Management Professional (CDMP). This program is based on the DAMA-DMBOK and provides an objective and vendor-independent assessment of data management knowledge, skills, and experience. The CDMP certification has three levels: Associate, Practitioner, and Master. Each level requires passing one or more exams that cover different data management topics and domains.


The DAMA publications and resources




DAMA International publishes and provides various publications and resources for data management professionals and organizations. These publications and resources include books, articles, white papers, case studies, webinars, podcasts, newsletters, blogs, and more. They cover a wide range of data management topics and domains, such as data governance, data quality, data modeling, data security, data analytics, and more. They are updated regularly to reflect the latest trends and best practices in data management.


Some of the most notable publications and resources from DAMA International are:



  • The DAMA Guide to the Data Management Body of Knowledge (DAMA-DMBOK). This is the reference book that describes the best practices for data management across 11 functional areas. It is the basis for the CDMP certification program and the DMMM framework.



  • The DAMA Dictionary of Data Management Terms. This is a glossary that defines over 2000 terms related to data management. It provides a common vocabulary and a standard terminology for data management professionals.



  • The DAMA Data Management Body of Knowledge Case Studies. These are real-world examples of how organizations have applied the DAMA-DMBOK principles and practices to address their data management challenges and achieve their business goals.



Conclusion




DAMA-DMBOK is a comprehensive and authoritative guide for data management professionals and organizations. It provides a common framework, a common vocabulary, and a common set of best practices for data management across 11 functional areas. It also provides a flexible and adaptable approach that can be tailored to different contexts, domains, industries, and technologies.


DAMA-DMBOK can help data management professionals and organizations to address their data management needs and challenges, as well as to align their data management activities with their business goals and strategies. It can also help them to improve their data quality, reliability, usability, and value, as well as to reduce their data risks, costs, and complexity.


DAMA-DMBOK is not the only resource for data management professionals and organizations. There are many other ways to learn more about DAMA-DMBOK and data management in general, such as joining the DAMA International organization and community, enrolling in the DAMA certification and training programs, and accessing the DAMA publications and resources.


FAQs




Here are some frequently asked questions about DAMA-DMBOK and data management.



  • What is the difference between DAMA-DMBOK and DAMA-DMBOK2?



DAMA-DMBOK is the first edition of the Data Management Body of Knowledge, published by DAMA International in 2009. DAMA-DMBOK2 is the second edition of the Data Management Body of Knowledge, published by DAMA International in 2017. DAMA-DMBOK2 updates and expands the content of DAMA-DMBOK to reflect the latest developments and best practices in data management.


  • How can I get a copy of DAMA-DMBOK or DAMA-DMBOK2?



You can purchase a hard copy or a digital copy of DAMA-DMBOK or DAMA-DMBOK2 from various online platforms, such as Amazon, Barnes & Noble, or Technics Publications. You can also access a free preview of DAMA-DMBOK2 from the DAMA International website.


  • How can I prepare for the CDMP exams?



The CDMP exams are based on the content of DAMA-DMBOK and DAMA-DMBOK2. You can prepare for the CDMP exams by studying these books and by taking practice tests and mock exams. You can also enroll in training courses or workshops offered by DAMA International or its partners.


  • How can I join DAMA International or a local chapter?



You can join DAMA International or a local chapter by visiting the DAMA International website and filling out an online application form. You will need to pay an annual membership fee and agree to abide by the DAMA International code of ethics. You will then receive a confirmation email and a membership number.


  • How can I contribute to DAMA International or DAMA-DMBOK?



You can contribute to DAMA International or DAMA-DMBOK by volunteering your time, skills, and expertise to various activities and initiatives. For example, you can participate in events, webinars, publications, committees, working groups, or projects. You can also provide feedback, suggestions, or comments to improve the quality and relevance of DAMA International or DAMA-DMBOK.


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