A 3 day examination preparation course including live sitting of examinations for students who wish to attain the DAMA Certified Data Management Professional qualification (CDMP)
chris.bradley@dmadvisors.co.uk
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how data architecture is a key component of an overall enterprise architecture for enhanced business value and success.
LDM Slides: How Data Modeling Fits into an Overall Enterprise ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as it relates to data and its business impact across the organization.
Join this webinar for a discussion on how a data model can be combined with an overall enterprise architecture for enhanced business value and success.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Business Intelligence & Data Analytics– An Architected ApproachDATAVERSITY
Business intelligence (BI) and data analytics are increasing in popularity as more organizations are looking to become more data-driven. Many tools have powerful visualization techniques that can create dynamic displays of critical information. To ensure that the data displayed on these visualizations is accurate and timely, a strong Data Architecture is needed. Join this webinar to understand how to create a robust Data Architecture for BI and data analytics that takes both business and technology needs into consideration.
The document provides an introduction and background on Christopher Bradley, an expert in data governance. It then discusses data governance, defining it as the design and execution of standards and policies covering the design and operation of a management system to assure that data delivers value and is not a cost, as well as who can do what to the organization. The document lists Bradley's recent presentations and publications on topics related to data governance, data modeling, master data management and information management.
Data Architecture Best Practices for Advanced AnalyticsDATAVERSITY
Many organizations are immature when it comes to data and analytics use. The answer lies in delivering a greater level of insight from data, straight to the point of need.
There are so many Data Architecture best practices today, accumulated from years of practice. In this webinar, William will look at some Data Architecture best practices that he believes have emerged in the past two years and are not worked into many enterprise data programs yet. These are keepers and will be required to move towards, by one means or another, so it’s best to mindfully work them into the environment.
This document provides an overview of a data catalog called Amundsen that was created to improve the productivity of data users. Amundsen indexes data resources and powers search based on usage patterns to help users discover, understand, and analyze data. It aims to reduce the time data scientists spend on data discovery activities from one-third to increase their productivity. The tool provides search of metadata from various data sources and displays table details, column metadata stats, and people profiles to help users find and understand corporate data.
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how data architecture is a key component of an overall enterprise architecture for enhanced business value and success.
LDM Slides: How Data Modeling Fits into an Overall Enterprise ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as it relates to data and its business impact across the organization.
Join this webinar for a discussion on how a data model can be combined with an overall enterprise architecture for enhanced business value and success.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Business Intelligence & Data Analytics– An Architected ApproachDATAVERSITY
Business intelligence (BI) and data analytics are increasing in popularity as more organizations are looking to become more data-driven. Many tools have powerful visualization techniques that can create dynamic displays of critical information. To ensure that the data displayed on these visualizations is accurate and timely, a strong Data Architecture is needed. Join this webinar to understand how to create a robust Data Architecture for BI and data analytics that takes both business and technology needs into consideration.
The document provides an introduction and background on Christopher Bradley, an expert in data governance. It then discusses data governance, defining it as the design and execution of standards and policies covering the design and operation of a management system to assure that data delivers value and is not a cost, as well as who can do what to the organization. The document lists Bradley's recent presentations and publications on topics related to data governance, data modeling, master data management and information management.
Data Architecture Best Practices for Advanced AnalyticsDATAVERSITY
Many organizations are immature when it comes to data and analytics use. The answer lies in delivering a greater level of insight from data, straight to the point of need.
There are so many Data Architecture best practices today, accumulated from years of practice. In this webinar, William will look at some Data Architecture best practices that he believes have emerged in the past two years and are not worked into many enterprise data programs yet. These are keepers and will be required to move towards, by one means or another, so it’s best to mindfully work them into the environment.
This document provides an overview of a data catalog called Amundsen that was created to improve the productivity of data users. Amundsen indexes data resources and powers search based on usage patterns to help users discover, understand, and analyze data. It aims to reduce the time data scientists spend on data discovery activities from one-third to increase their productivity. The tool provides search of metadata from various data sources and displays table details, column metadata stats, and people profiles to help users find and understand corporate data.
This document discusses data governance and data architecture. It introduces data governance as the processes for managing data, including deciding data rights, making data decisions, and implementing those decisions. It describes how data architecture relates to data governance by providing patterns and structures for governing data. The document presents some common data architecture patterns, including a publish/subscribe pattern where a publisher pushes data to a hub and subscribers pull data from the hub. It also discusses how data architecture can support data governance goals through approaches like a subject area data model.
The first step towards understanding data assets’ impact on your organization is understanding what those assets mean for each other. Metadata – literally, data about data – is a practice area required by good systems development, and yet is also perhaps the most mislabeled and misunderstood Data Management practice. Understanding metadata and its associated technologies as more than just straightforward technological tools can provide powerful insight into the efficiency of organizational practices and enable you to combine practices into sophisticated techniques supporting larger and more complex business initiatives. Program learning objectives include:
- Understanding how to leverage metadata practices in support of business strategy
- Discuss foundational metadata concepts
- Guiding principles for and lessons previously learned from metadata and its practical uses applied strategy
Metadata strategies include:
- Metadata is a gerund so don’t try to treat it as a noun
- Metadata is the language of Data Governance
- Treat glossaries/repositories as capabilities, not technology
Webinar: Decoding the Mystery - How to Know if You Need a Data Catalog, a Dat...DATAVERSITY
This document discusses the importance of metadata and data governance. It describes how a data catalog can consolidate metadata from various sources like a business glossary, data dictionary, and data profiling. Automating data lineage is key to harvesting metadata at scale and establishing relationships between different metadata objects. When integrated in a data catalog, metadata provides a single source of truth about an organization's data that improves data literacy and trust.
Data Modeling, Data Governance, & Data QualityDATAVERSITY
Data Governance is often referred to as the people, processes, and policies around data and information, and these aspects are critical to the success of any data governance implementation. But just as critical is the technical infrastructure that supports the diverse data environments that run the business. Data models can be the critical link between business definitions and rules and the technical data systems that support them. Without the valuable metadata these models provide, data governance often lacks the “teeth” to be applied in operational and reporting systems.
Join Donna Burbank and her guest, Nigel Turner, as they discuss how data models & metadata-driven data governance can be applied in your organization in order to achieve improved data quality.
This document summarizes a research study that assessed the data management practices of 175 organizations between 2000-2006. The study had both descriptive and self-improvement goals, such as understanding the range of practices and determining areas for improvement. Researchers used a structured interview process to evaluate organizations across six data management processes based on a 5-level maturity model. The results provided insights into an organization's practices and a roadmap for enhancing data management.
Data governance Program PowerPoint Presentation Slides SlideTeam
The document discusses the need for data governance programs in companies. It outlines why companies suffer without effective data governance, such as applications being unable to communicate and inconsistencies in data leading to increased costs. The document then compares manual and automated approaches to data governance. It provides details on key aspects of building a data governance program, including establishing a framework, defining roles and responsibilities, and outlining a roadmap for improving data governance over time.
Data Governance Best Practices, Assessments, and RoadmapsDATAVERSITY
When starting or evaluating the present state of your Data Governance program, it is important to focus on best practices such that you don’t take a ready, fire, aim approach. Best practices need to be practical and doable to be selected for your organization, and the program must be at risk if the best practice is not achieved.
Join Bob Seiner for an important webinar focused on industry best practice around standing up formal Data Governance. Learn how to assess your organization against the practices and deliver an effective roadmap based on the results of conducting the assessment.
In this webinar, Bob will focus on:
- Criteria to select the appropriate best practices for your organization
- How to define the best practices for ultimate impact
- Assessing against selected best practices
- Focusing the recommendations on program success
- Delivering a roadmap for your Data Governance program
The document outlines several upcoming workshops hosted by CCG, an analytics consulting firm, including:
- An Analytics in a Day workshop focusing on Synapse on March 16th and April 20th.
- An Introduction to Machine Learning workshop on March 23rd.
- A Data Modernization workshop on March 30th.
- A Data Governance workshop with CCG and Profisee on May 4th focusing on leveraging MDM within data governance.
More details and registration information can be found on ccganalytics.com/events. The document encourages following CCG on LinkedIn for event updates.
The document discusses data governance and why it is an imperative activity. It provides a historical perspective on data governance, noting that as data became more complex and valuable, the need for formal governance increased. The document outlines some key concepts for a successful data governance program, including having clearly defined policies covering data assets and processes, and establishing a strong culture that values data. It argues that proper data governance is now critical to business success in the same way as other core functions like finance.
Data Architecture Strategies: Data Architecture for Digital TransformationDATAVERSITY
MDM, data quality, data architecture, and more. At the same time, combining these foundational data management approaches with other innovative techniques can help drive organizational change as well as technological transformation. This webinar will provide practical steps for creating a data foundation for effective digital transformation.
Five Things to Consider About Data Mesh and Data GovernanceDATAVERSITY
Data mesh was among the most discussed and controversial enterprise data management topics of 2021. One of the reasons people struggle with data mesh concepts is we still have a lot of open questions that we are not thinking about:
Are you thinking beyond analytics? Are you thinking about all possible stakeholders? Are you thinking about how to be agile? Are you thinking about standardization and policies? Are you thinking about organizational structures and roles?
Join data.world VP of Product Tim Gasper and Principal Scientist Juan Sequeda for an honest, no-bs discussion about data mesh and its role in data governance.
This document discusses data security management. It outlines key concepts and activities including understanding business and regulatory requirements, defining security policies, standards, controls and procedures, managing users, passwords and permissions. The goal is to protect information through proper authentication, authorization, access and auditing in alignment with privacy needs and regulations.
DAS Slides: Data Governance and Data Architecture – Alignment and SynergiesDATAVERSITY
Data Governance can have a varied definition, depending on the audience. To many, Data Governance consists of committee meetings and stewardship roles. To others, it focuses on technical Data Management and controls. Holistic Data Governance combines both of these aspects, and a robust Data Architecture and associated diagrams can be the “glue” that binds business and IT governance together. Join this webinar for practical tips and hands-on exercises for aligning Data Architecture and Data Governance for business and IT success.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace, from digital transformation to marketing, customer centricity, population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Improving Data Literacy Around Data ArchitectureDATAVERSITY
Data Literacy is an increasing concern, as organizations look to become more data-driven. As the rise of the citizen data scientist and self-service data analytics becomes increasingly common, the need for business users to understand core Data Management fundamentals is more important than ever. At the same time, technical roles need a strong foundation in Data Architecture principles and best practices. Join this webinar to understand the key components of Data Literacy, and practical ways to implement a Data Literacy program in your organization.
Creating a clearly articulated data strategy—a roadmap of technology-driven capability investments prioritized to deliver value—helps ensure from the get-go that you are focusing on the right things, so that your work with data has a business impact. In this presentation, the experts at Silicon Valley Data Science share their approach for crafting an actionable and flexible data strategy to maximize business value.
Who Should Own Data Governance – IT or Business?DATAVERSITY
The question is asked all the time: “What part of the organization should own your Data Governance program?” The typical answers are “the business” and “IT (information technology).” Another answer to that question is “Yes.” The program must be owned and reside somewhere in the organization. You may ask yourself if there is a correct answer to the question.
Join this new RWDG webinar with Bob Seiner where Bob will answer the question that is the title of this webinar. Determining ownership of Data Governance is a vital first step. Figuring out the appropriate part of the organization to manage the program is an important second step. This webinar will help you address these questions and more.
In this session Bob will share:
- What is meant by “the business” when it comes to owning Data Governance
- Why some people say that Data Governance in IT is destined to fail
- Examples of IT positioned Data Governance success
- Considerations for answering the question in your organization
- The final answer to the question of who should own Data Governance
Introduction to Data Analytics and VisualizationKaran Menon
The document provides information about Karan Menon and his background. It then outlines an agenda for a presentation on data analytics in business development. The agenda includes discussing what data analytics is, types of analytics, analytical tools like Tableau, Power BI and QlikView, and conclusions. Karan Menon has a PhD in information and knowledge management and researches topics related to business data analytics, industrial internet, and business models.
Data Catalog for Better Data Discovery and GovernanceDenodo
Watch full webinar here: https://buff.ly/2Vq9FR0
Data catalogs are en vogue answering critical data governance questions like “Where all does my data reside?” “What other entities are associated with my data?” “What are the definitions of the data fields?” and “Who accesses the data?” Data catalogs maintain the necessary business metadata to answer these questions and many more. But that’s not enough. For it to be useful, data catalogs need to deliver these answers to the business users right within the applications they use.
In this session, you will learn:
*How data catalogs enable enterprise-wide data governance regimes
*What key capability requirements should you expect in data catalogs
*How data virtualization combines dynamic data catalogs with delivery
Chief Data Officer: Evolution to the Chief Analytics Officer and Data ScienceCraig Milroy
The document discusses the evolution of the role of Chief Data Officer (CDO) to Chief Analytics Officer and the importance of data science. It notes that organizations are appointing CDOs to address data issues but these roles often lack formal guidance. The CDO role could evolve to focus more on analytics and data science. Data science involves using data to create actionable insights and predict the future rather than just analyzing the past. It requires multiple skills from domain expertise to technical skills to storytelling. Data scientists can provide a unique customer-centric view of data and opportunities for organizations.
Visualising Energistics WITSML XML Data Structures in Data Models. ECIM E&P conference, Haugesund Norway, September 2013.
chris.bradley@dmadvisors.co.uk
This document discusses data governance and data architecture. It introduces data governance as the processes for managing data, including deciding data rights, making data decisions, and implementing those decisions. It describes how data architecture relates to data governance by providing patterns and structures for governing data. The document presents some common data architecture patterns, including a publish/subscribe pattern where a publisher pushes data to a hub and subscribers pull data from the hub. It also discusses how data architecture can support data governance goals through approaches like a subject area data model.
The first step towards understanding data assets’ impact on your organization is understanding what those assets mean for each other. Metadata – literally, data about data – is a practice area required by good systems development, and yet is also perhaps the most mislabeled and misunderstood Data Management practice. Understanding metadata and its associated technologies as more than just straightforward technological tools can provide powerful insight into the efficiency of organizational practices and enable you to combine practices into sophisticated techniques supporting larger and more complex business initiatives. Program learning objectives include:
- Understanding how to leverage metadata practices in support of business strategy
- Discuss foundational metadata concepts
- Guiding principles for and lessons previously learned from metadata and its practical uses applied strategy
Metadata strategies include:
- Metadata is a gerund so don’t try to treat it as a noun
- Metadata is the language of Data Governance
- Treat glossaries/repositories as capabilities, not technology
Webinar: Decoding the Mystery - How to Know if You Need a Data Catalog, a Dat...DATAVERSITY
This document discusses the importance of metadata and data governance. It describes how a data catalog can consolidate metadata from various sources like a business glossary, data dictionary, and data profiling. Automating data lineage is key to harvesting metadata at scale and establishing relationships between different metadata objects. When integrated in a data catalog, metadata provides a single source of truth about an organization's data that improves data literacy and trust.
Data Modeling, Data Governance, & Data QualityDATAVERSITY
Data Governance is often referred to as the people, processes, and policies around data and information, and these aspects are critical to the success of any data governance implementation. But just as critical is the technical infrastructure that supports the diverse data environments that run the business. Data models can be the critical link between business definitions and rules and the technical data systems that support them. Without the valuable metadata these models provide, data governance often lacks the “teeth” to be applied in operational and reporting systems.
Join Donna Burbank and her guest, Nigel Turner, as they discuss how data models & metadata-driven data governance can be applied in your organization in order to achieve improved data quality.
This document summarizes a research study that assessed the data management practices of 175 organizations between 2000-2006. The study had both descriptive and self-improvement goals, such as understanding the range of practices and determining areas for improvement. Researchers used a structured interview process to evaluate organizations across six data management processes based on a 5-level maturity model. The results provided insights into an organization's practices and a roadmap for enhancing data management.
Data governance Program PowerPoint Presentation Slides SlideTeam
The document discusses the need for data governance programs in companies. It outlines why companies suffer without effective data governance, such as applications being unable to communicate and inconsistencies in data leading to increased costs. The document then compares manual and automated approaches to data governance. It provides details on key aspects of building a data governance program, including establishing a framework, defining roles and responsibilities, and outlining a roadmap for improving data governance over time.
Data Governance Best Practices, Assessments, and RoadmapsDATAVERSITY
When starting or evaluating the present state of your Data Governance program, it is important to focus on best practices such that you don’t take a ready, fire, aim approach. Best practices need to be practical and doable to be selected for your organization, and the program must be at risk if the best practice is not achieved.
Join Bob Seiner for an important webinar focused on industry best practice around standing up formal Data Governance. Learn how to assess your organization against the practices and deliver an effective roadmap based on the results of conducting the assessment.
In this webinar, Bob will focus on:
- Criteria to select the appropriate best practices for your organization
- How to define the best practices for ultimate impact
- Assessing against selected best practices
- Focusing the recommendations on program success
- Delivering a roadmap for your Data Governance program
The document outlines several upcoming workshops hosted by CCG, an analytics consulting firm, including:
- An Analytics in a Day workshop focusing on Synapse on March 16th and April 20th.
- An Introduction to Machine Learning workshop on March 23rd.
- A Data Modernization workshop on March 30th.
- A Data Governance workshop with CCG and Profisee on May 4th focusing on leveraging MDM within data governance.
More details and registration information can be found on ccganalytics.com/events. The document encourages following CCG on LinkedIn for event updates.
The document discusses data governance and why it is an imperative activity. It provides a historical perspective on data governance, noting that as data became more complex and valuable, the need for formal governance increased. The document outlines some key concepts for a successful data governance program, including having clearly defined policies covering data assets and processes, and establishing a strong culture that values data. It argues that proper data governance is now critical to business success in the same way as other core functions like finance.
Data Architecture Strategies: Data Architecture for Digital TransformationDATAVERSITY
MDM, data quality, data architecture, and more. At the same time, combining these foundational data management approaches with other innovative techniques can help drive organizational change as well as technological transformation. This webinar will provide practical steps for creating a data foundation for effective digital transformation.
Five Things to Consider About Data Mesh and Data GovernanceDATAVERSITY
Data mesh was among the most discussed and controversial enterprise data management topics of 2021. One of the reasons people struggle with data mesh concepts is we still have a lot of open questions that we are not thinking about:
Are you thinking beyond analytics? Are you thinking about all possible stakeholders? Are you thinking about how to be agile? Are you thinking about standardization and policies? Are you thinking about organizational structures and roles?
Join data.world VP of Product Tim Gasper and Principal Scientist Juan Sequeda for an honest, no-bs discussion about data mesh and its role in data governance.
This document discusses data security management. It outlines key concepts and activities including understanding business and regulatory requirements, defining security policies, standards, controls and procedures, managing users, passwords and permissions. The goal is to protect information through proper authentication, authorization, access and auditing in alignment with privacy needs and regulations.
DAS Slides: Data Governance and Data Architecture – Alignment and SynergiesDATAVERSITY
Data Governance can have a varied definition, depending on the audience. To many, Data Governance consists of committee meetings and stewardship roles. To others, it focuses on technical Data Management and controls. Holistic Data Governance combines both of these aspects, and a robust Data Architecture and associated diagrams can be the “glue” that binds business and IT governance together. Join this webinar for practical tips and hands-on exercises for aligning Data Architecture and Data Governance for business and IT success.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace, from digital transformation to marketing, customer centricity, population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Improving Data Literacy Around Data ArchitectureDATAVERSITY
Data Literacy is an increasing concern, as organizations look to become more data-driven. As the rise of the citizen data scientist and self-service data analytics becomes increasingly common, the need for business users to understand core Data Management fundamentals is more important than ever. At the same time, technical roles need a strong foundation in Data Architecture principles and best practices. Join this webinar to understand the key components of Data Literacy, and practical ways to implement a Data Literacy program in your organization.
Creating a clearly articulated data strategy—a roadmap of technology-driven capability investments prioritized to deliver value—helps ensure from the get-go that you are focusing on the right things, so that your work with data has a business impact. In this presentation, the experts at Silicon Valley Data Science share their approach for crafting an actionable and flexible data strategy to maximize business value.
Who Should Own Data Governance – IT or Business?DATAVERSITY
The question is asked all the time: “What part of the organization should own your Data Governance program?” The typical answers are “the business” and “IT (information technology).” Another answer to that question is “Yes.” The program must be owned and reside somewhere in the organization. You may ask yourself if there is a correct answer to the question.
Join this new RWDG webinar with Bob Seiner where Bob will answer the question that is the title of this webinar. Determining ownership of Data Governance is a vital first step. Figuring out the appropriate part of the organization to manage the program is an important second step. This webinar will help you address these questions and more.
In this session Bob will share:
- What is meant by “the business” when it comes to owning Data Governance
- Why some people say that Data Governance in IT is destined to fail
- Examples of IT positioned Data Governance success
- Considerations for answering the question in your organization
- The final answer to the question of who should own Data Governance
Introduction to Data Analytics and VisualizationKaran Menon
The document provides information about Karan Menon and his background. It then outlines an agenda for a presentation on data analytics in business development. The agenda includes discussing what data analytics is, types of analytics, analytical tools like Tableau, Power BI and QlikView, and conclusions. Karan Menon has a PhD in information and knowledge management and researches topics related to business data analytics, industrial internet, and business models.
Data Catalog for Better Data Discovery and GovernanceDenodo
Watch full webinar here: https://buff.ly/2Vq9FR0
Data catalogs are en vogue answering critical data governance questions like “Where all does my data reside?” “What other entities are associated with my data?” “What are the definitions of the data fields?” and “Who accesses the data?” Data catalogs maintain the necessary business metadata to answer these questions and many more. But that’s not enough. For it to be useful, data catalogs need to deliver these answers to the business users right within the applications they use.
In this session, you will learn:
*How data catalogs enable enterprise-wide data governance regimes
*What key capability requirements should you expect in data catalogs
*How data virtualization combines dynamic data catalogs with delivery
Chief Data Officer: Evolution to the Chief Analytics Officer and Data ScienceCraig Milroy
The document discusses the evolution of the role of Chief Data Officer (CDO) to Chief Analytics Officer and the importance of data science. It notes that organizations are appointing CDOs to address data issues but these roles often lack formal guidance. The CDO role could evolve to focus more on analytics and data science. Data science involves using data to create actionable insights and predict the future rather than just analyzing the past. It requires multiple skills from domain expertise to technical skills to storytelling. Data scientists can provide a unique customer-centric view of data and opportunities for organizations.
Visualising Energistics WITSML XML Data Structures in Data Models. ECIM E&P conference, Haugesund Norway, September 2013.
chris.bradley@dmadvisors.co.uk
Dubai training classes covering:
An Introduction to Information Management,
Data Quality Management,
Master & Reference Data Management, and
Data Governance.
Based on DAMA DMBoK 2.0, 36 years practical experience and taught by author, award winner CDMP Fellow.
CDMP Overview Professional Information Management CertificationChristopher Bradley
Overview of the DAMA Certified Data Management Professional (CDMP) examination.
Session presented at DAMA Australia November 2013
chris.bradley@dmadvisors.co.uk
The document discusses the emergence and future of the Chief Data Officer (CDO) role. It outlines how data strategies have evolved from governance to monetization as data has increased in volume and importance. The CDO role emerged to oversee organizations' data as a strategic asset. Successful CDOs demonstrate six personas: Evangelist, Educator, Protector, Quant, Architect, and Politician. These personas focus on strategy, education, governance, analytics, architecture, and stakeholder management. The document concludes that for CDOs to be effective, they must find the right person, demonstrate quick wins, avoid distractions, build a team, secure funding, and ease disruptions caused by changes in how the
This document discusses BP's data modelling challenges and solutions. BP has over 100,000 employees operating in over 100 countries with 250 data centers and over 7,000 applications. Their challenges included decentralized management of data modelling, lack of standards and governance, and models getting lost after projects. Their solution included a self-service DMaaS portal for ER/Studio licensing and model publishing. It provides automated reporting, judicious use of macros, and a community of interest. Next steps include promoting data modelling to SAP architects and expanding training, certification and the online community.
Information Management Fundamentals DAMA DMBoK training course synopsisChristopher Bradley
The fundamentals of Information Management covering the Information Functions and disciplines as outlined in the DAMA DMBoK . This course provides an overview of all of the Information Management disciplines and is also a useful start point for candidates preparing to take DAMA CDMP professional certification.
Taught by CDMP(Master) examiner and author of components of the DMBoK 2.0
chris.bradley@dmadvisors.co.uk
A conceptual data model (CDM) uses simple graphical images to describe core concepts and principles of an organization at a high level. A CDM facilitates communication between businesspeople and IT and integration between systems. It needs to capture enough rules and definitions to create database systems while remaining intuitive. Conceptual data models apply to both transactional and dimensional/analytics modeling. While different notations can be used, the most important thing is that a CDM effectively conveys an organization's key concepts.
Information Management training developed by Chris Bradley.
Education options include an overview of Information Management, DMBoK Overview, Data Governance, Master & Reference Data Management, Data Quality, Data Modelling, Data Integration, Data Management Fundamentals and DAMA CDMP certification.
chris.bradley@dmadvisors.co.uk
The document discusses an enterprise information management (EIM) framework and big data readiness assessment. It provides an overview of key components of an EIM framework, including data governance, data integration, data lifecycle management, and maturity assessments of EIM disciplines and enablers. It then describes a big data readiness assessment that helps organizations address questions around their need for and ability to exploit big data by determining which foundational EIM capabilities must be established and what aspects need improvement before embarking on a big data initiative.
The Chief Data Office at the Department of Commerce aims to empower people and businesses through open data and transparency. The CDO identifies how data can be harnessed and transformed to create business opportunities and competitive advantages. At the Department of Commerce, the CDO's mission is to fundamentally change how people and businesses interact with the various bureaus that manage important data through the delivery of data products and services, consulting, training, partnerships, and procurement of data infrastructure.
The document provides an introduction to Christopher Bradley and his experience in information management, along with a list of his recent presentations and publications. It then outlines that the remainder of the document will discuss approaches to selecting data modelling tools, an evaluation method, vendors and products, and provide a summary.
Joe Caserta was a featured speaker, along with MIT Sloan School faculty and other industry thought-leaders. His session 'You're the New CDO, Now What?' discussed how new CDOs can accomplish their strategic objectives and overcome tactical challenges in this emerging executive leadership role.
In its tenth year, the MIT CDOIQ Symposium 2016 continues to explore the developing role of the Chief Data Officer.
For more information, visit http://casertaconcepts.com/
Information Management Training & Certification from Data Management Advisors.
info@dmadvisors.co.uk
Courses available include:
Information Management Fundamentals,
Data Governance,
Data Quality Management,
Master & Reference Data,
Data Modelling,
Data Warehouse & Business Intelligence,
Metadata Management,
Data Security & Risk,
Data Integration & Interoperability,
DAMA CDMP Certification,
Business Process Discovery
Data Modelling 101 half day workshop presented by Chris Bradley at the Enterprise Data and Business Intelligence conference London on November 3rd 2014.
Chris Bradley is a leading independent information strategist.
Contact chris.bradley@dmadvisors.co.uk
DAMA BCS Chris Bradley Information is at the Heart of ALL architectures 18_06...Christopher Bradley
Information is at the heart of ALL architectures and the business.
Presentation by Chris Bradley to BCS Data Management Specialist Group (DMSG) and DAMA at the event "Information the vital organisation enabler" June 2015
Master Data Management (MDM) is a systematic approach to cleaning up customer data so businesses can manage it efficiently and grow effectively. MDM helps businesses achieve a single version of truth about customers. It deals with strategies, architectures, and technologies for managing customer data, known as Customer Data Integration (CDI). Implementing MDM requires gaining commitment from senior management, understanding business drivers and resource requirements, and providing estimates of benefits like reduced costs and increased sales. A pilot project should be proposed before a full implementation to demonstrate value and gather feedback.
The what, why, and how of master data managementMohammad Yousri
This presentation explains what MDM is, why it is important, and how to manage it, while identifying some of the key MDM patterns and best practices that are emerging. This presentation is a high-level treatment of the problem space.
The presentation is summarizing the article of Microsoft in a simple way.
https://msdn.microsoft.com/en-us/library/bb190163.aspx
This is a 3 day advanced course for students with existing data modelling experience to enable them to build quality data models that meet business needs. The course will enable students to:
* Understand and practice different requirements gathering approaches.
* Recognise the relationship between process and data models and practice capturing requirements for both.
* Learn how and when to exploit standard constructs and reference models.
*Understand further dimensional modelling approaches and normalisation techniques.
* Apply advanced patterns including "Bill of Materials" and "Party, Role, Relationship, Role-Relationship"
* Understand and practice the human centric design skills required for effective conceptual model development
* Recognise the different ways of developing models to represent ranges of hierarchies
This is a 3 day introductory course introducing students to data modelling, its purpose, the different types of models and how to construct and read a data model. Students attending this course will be able to:
Explain the fundamental data modelling building blocks. Understand the differences between relational and dimensional models.
Describe the purpose of Enterprise, conceptual, logical, and physical data models
Create a conceptual data model and a logical data model.
Understand different approaches for fact finding.
Apply normalisation techniques.
Unichrone imparts Operational Excellence Training Course for the middle and senior management audience. The course is for 4 days and helps the participants to understand with thorough information on Operational Excellence subject.
This 3-day workshop aims to teach practitioners data analysis and interpretation skills. The objectives are to impart an understanding of data-oriented thinking, equip attendees with statistical tools to identify, analyze and interpret data to enhance performance, and inculcate a data-centric culture. Attendees will learn how to convert data into information, use data to achieve breakthroughs and influence stakeholders. The workshop will include exercises and case studies led by a world-class faculty with decades of experience across industries. It is intended for individuals and teams from all levels and departments.
This document summarizes a business analytics certificate program offered jointly by Dun & Bradstreet and EduPristine. The 10-day program provides 50 hours of classroom training using R Tool and Excel, focusing on topics like statistics, linear regression, logistic regression, decision trees, and time series modeling. It is intended to equip professionals with essential analytics tools and skills. Participants will receive certification upon completing the course and can choose packages that include additional case studies, data visualization training, and Tableau certification. EduPristine is an education company that provides various professional training programs.
Here's an opportunity to view the kinds of knowledge and skills I bring to an organization ro engagement. I look forward to hearing from professionals who see the value in my assistance.
I apologize, upon further review I do not feel comfortable providing a summary of a document that contains personal information or discusses legal compliance.
Maximising and monitoring project management competenceILX Group
Introduce the ILX 3CAT – combined competence and capability assessment tool
Review the APM Competence Framework (2015) and to show how the 3CAT can help you to develop the competence of your teams by baselining capability
Review the impact of competence assessment on personal and organisational capability
Review of the ILX 3CAT tool.
Maximising and monitoring project management competenceILX Group
Introduce the ILX 3CAT – combined competence and capability assessment tool
Review the APM Competence Framework (2015) and to show how the 3CAT can help you to develop the competence of your teams by baselining capability
Review the impact of competence assessment on personal and organisational capability
Review of the ILX 3CAT tool.
Data Governance and MDM | Profisse, Microsoft, and CCGCCG
CCG will introduce a methodology and framework for DG that allows organizations to assess DG faster, deriving actionable insights that can be quickly implemented with minimal disruption. CCG will also review how Microsoft Azure Solutions can be leveraged to build a strong foundation for governed data insights. In addition, Profisee will introduce a popular component of data governance, MDM.
This document provides an overview of a 3-day "Business Analytics" workshop for practitioners. The workshop aims to impart an understanding of data-oriented thinking, equip participants with statistical tools to identify, analyze and interpret data for improved performance, and foster a data-centric culture. The workshop will cover topics like identifying opportunities from data, basic statistics, analytical tools, statistical tests, regression, forecasting techniques and more. It will include practical exercises and cases. The target audience are individuals and teams from across organizations and industry domains. The workshop will be led by an experienced principal coach with expertise in areas like Lean Six Sigma, customer service, and analytics.
Virtual Governance in a Time of Crisis WorkshopCCG
The CCGDG framework is focused on the following 5 key competencies. These 5 competencies were identified as areas within DG that have the biggest ROI for you, our customer. The pandemic has uncovered many challenges related to governance, therefore the backbone of this model is the emphasis on risk mitigation.
1. Program Management
2. Data Quality
3. Data Architecture
4. Metadata Management
5. Privacy
How Talent Analytics Can Help You Maximize Your HR StrategyGlassdoor
For most organizations, the promise of Big Data remains unfulfilled. The vast majority of organizations are stuck in a reporting cycle, churning out lots of metrics, but few insights or solutions. The ability to measure, analyze, and optimize talent practices is now critical to business success.
Many HR organizations have recognized this need and are starting to invest more strategically in measurement and analytics. With a plethora of data, recruiting is an area ripe to take advantage of analytics. With the right tools and capabilities, this data can be turned into competitive advantage.
Check out our webinar feat. Karen O'Leonard, VP of Benchmarking & Analytics Research of Bersin by Deloitte and Wiliam Blackstorm, Sr. Manager Sourcing & Market Intelligence & Director of Global Talent Analytics, Research Division of Cisco to learn:
-Where to start when analyzing recruitment data
-How to build an effective talent analytics capability
-How one organization, Cisco, is using analytics to develop a more effective recruitment strategy
Data Governance with Profisee, Microsoft & CCG CCG
1. The workshop agenda covers data governance fundamentals, assessing an organization's data governance maturity using the CCGDG framework, and prioritizing a roadmap for improvement.
2. The Profisee presentation promotes their master data management solution for enabling digital transformation by providing a single view of critical data across systems.
3. Profisee's solution focuses on five key areas: stewardship, matching configuration, adjusting the configuration, operational matching, and workflow management to ensure data quality.
Business Continuity & Disaster Recovery Planning 02 - 04 December 2013 Kuala ...360 BSI
Disasters could cripple your organization, suspending mission-critical processes and disrupting service to your customers. These disasters could be man-made or natural in nature.
The Business Continuity Plan addresses an organization’s ability to continue functioning when normal operations are disrupted. A Disaster Recovery Plan is used to define the resources, action, tasks, and data required to manage the business recovery process in the event of a disaster.
In this workshop you learn to identify vulnerabilities and implement appropriate countermeasures to prevent and mitigate threats to your mission-critical processes. You will learn techniques for creating a business continuity plan (BCP) and the methodology for building an infrastructure that supports its effective implementation.
Benefits of Attending:
Using a carefully selected case study, course participants will:
- Create, document and test continuity arrangements for an organization
- Perform a risk assessment and Business Impact Assessment (BIA) to identify vulnerabilities
- Select and deploy an alternate site for continuity of mission-critical activities
- Identify appropriate strategies to recover the infrastructure and processes
- Organize and manage recovery teams
- Test and maintain an effective recovery plan in a rapidly changing technology environment
Exclusive:
- Bring your BCP/DRP for private consultation review
- BCP/DRP Step-by-step Guide
- BCP/DRP templates and worksheets to aid you in applying and putting into practice what you have learned from this workshop
- FREE CD containing course material, case studies, and other related items of the training workshop
Who should attend:
- Vice Presidents, Directors, General Managers
- Chief Information Officers
- Chief Security Officers
- Chief Information Security Officers
- Chief Technology Officers
- Heads of Departments in Information Security Management
Contact Kris at kris@360bsi.com to register.
Communicating the ROI of UX from The Enterprise to The Streets (JD Buckley at...Rosenfeld Media
JD Buckley: "Communicating the ROI of UX from The Enterprise to The Streets"
Enterprise UX 2018 • June 14-15, 2018 • San Francisco, CA, USA
http://enterpriseux.net
Big Data, why the Big fuss.
Volume, Variety, Velocity ... we know the 3 V's of Big Data. But Big Data if it yields little Information is useless, so focus on the 4th V = Value.
If you haven't sorted quality & data governance for your "little data" then seriously consider if you want to venture into the world of Big Data
Sixth Dimension Learning (SDL) delivers career-focused education and training that gives you the edge to succeed in a competitive world. The trainers and supporting staff at SDL are highly qualified professionals with vast industry experience. SDL was created with the purpose of reducing the gap between education and industry. The mission of SDL is to educate individuals so that they excel in their respective professions.
This document contains the resume of Manoj S. Karde which provides details of his educational qualifications, professional experience, skills and selected projects. Some key highlights include:
- Manoj has over 23 years of experience including 13 years of SAP MM experience.
- He currently works as an SAP MM Lead at Capgemini and has experience working with various clients on SAP support and implementation projects.
- Manoj's educational qualifications include a Diploma in Production Engineering, Graduation in Industrial Engineering, and certifications in SAP MM and Materials Management.
Dont let governance risk and compliance be a roll of the device | Modern Wor...Nikki Chapple
This document summarizes information about improving governance, risk, and compliance (GRC) maturity. It discusses establishing a GRC framework and assessing the current maturity level, which can range from not started to optimal. It then provides examples of actions organizations can take to improve their GRC maturity for both general GRC posture and specific to Microsoft 365. These include defining roles and processes, applying security defaults, implementing data protection and retention, and extending capabilities with additional licensing. The key steps are to start by prioritizing areas and establishing accountability, then continuously improving through a strategic risk-based approach.
Paper which discusses the notion that Data is NOT the "new Oil". We hear copious amounts said that Data is an asset, it's got to be managed, few people in the business understand it & so on. The phrase "Data is the new Oil" gets used many times, yet is rarely (if ever) justified. This paper is aimed to raise the level of debate from a subliminal nod to a conscious examination of the characteristics of different "assets" (particularly Oil) and to compare them with those of the 'Data asset".
Written by Christopher Bradley, CDMP Fellow, VP Professional Development DAMA International & 38 years Information Management experience, much of it in the Oil & Gas industry.
Information Management Training Courses & Certification approved by DAMA & based upon practical real world application of the DMBoK.
Includes Data Strategy, Data Governance, Master Data Management, Data Quality, Data Integration, Data Modelling & Process Modelling.
A Data Management Advisors discussion paper comparing the characteristics of different types of "assets" and asking the question "Is the data asset REALLY different"?
Peter Aiken introduces the concept of information management and argues that information is a valuable corporate asset that needs to be managed rigorously. The document discusses how the rise of unstructured data poses new challenges for information management. It outlines the dangers of poor information management, such as regulatory fines, damage to brand and reputation, and inability to access the right information to make good decisions. The document argues that smart organizations will implement information governance to exploit their information assets and gain competitive advantages.
Big Data projects require diverse skills and expertise, not a single person. Harnessing large and complex datasets can provide significant benefits for organizations, such as better decision making and new revenue opportunities, but also challenges. Successful Big Data initiatives require the right technology, skilled staff, and effective presentation of insights to decision makers. While technology enables exploitation of Big Data, information management practices and a mix of technical and analytical skills are needed to realize its full potential.
Information is at the heart of all architecture disciplinesChristopher Bradley
Information is at the Heart of ALL the business & all architectures.
A white paper by Chris Bradley outlining why Information is the "blood" of an organisation.
How to identify the correct Master Data subject areas & tooling for your MDM...Christopher Bradley
1. What are the different Master Data Management (MDM) architectures?
2. How can you identify the correct Master Data subject areas & tooling for your MDM initiative?
3. A reference architecture for MDM.
4. Selection criteria for MDM tooling.
chris.bradley@dmadvisors.co.uk
Data Management Capabilities for the Oil & Gas Industry 17-19 March, DubaiChristopher Bradley
The document summarizes an upcoming workshop on data management capabilities for the oil and gas industry. The 3-day workshop in Dubai will bring together senior professionals to share experiences with major data management concepts. Participants will analyze capabilities of concepts like master data management, big data, ERP systems, and GIS. The goal is to develop a comprehensive solution architecture model that classifies these concepts to help organizations evaluate market solutions and needs. Sessions will cover data storage, integration, and management services applications in oil and gas. Attendees include CEOs, data managers, architects, and other technical roles.
DMBOK 2.0 and other frameworks including TOGAF & COBIT - keynote from DAMA Au...Christopher Bradley
This document provides biographical information about Christopher Bradley, an expert in information management. It outlines his 36 years of experience in the field working with major organizations. He is the president of DAMA UK and author of sections of the DAMA DMBoK 2. It also lists his recent presentations and publications, which cover topics such as data governance, master data management, and information strategy. The document promotes training courses he provides on information management fundamentals and data modeling.
Information is at the heart of all architecture disciplines & why Conceptual ...Christopher Bradley
Information is at the heart of all of the architecture disciplines such as Business Architecture, Applications Architecture and Conceptual Data Modelling helps this.
Also, data modelling which helps inform this has been wrongly taught as being just for Database design in many Universities.
chris.bradley@dmadvisors.co.uk
This document discusses the importance and evolution of data modeling. It argues that data modeling is critical to all architecture disciplines, not just database development, as the data model provides common definitions and vocabulary. The document reviews the history of data management from the 1950s to today, noting how data modeling was originally used primarily for database development but now has broader applications. It discusses different types of data models for different purposes, and walks through traditional "top-down" and "bottom-up" approaches to using data models for database development. The overall message is that data modeling remains important but its uses and best practices have expanded beyond its original scope.
Introduction to Data Governance
Seminar hosted by Embarcadero technologies, where Christopher Bradley presented a session on Data Governance.
Drivers for Data Governance & Benefits
Data Governance Framework
Organization & Structures
Roles & responsibilities
Policies & Processes
Programme & Implementation
Reporting & Assurance
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Aggregage
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...Social Samosa
The Modern Marketing Reckoner (MMR) is a comprehensive resource packed with POVs from 60+ industry leaders on how AI is transforming the 4 key pillars of marketing – product, place, price and promotions.
Open Source Contributions to Postgres: The Basics POSETTE 2024ElizabethGarrettChri
Postgres is the most advanced open-source database in the world and it's supported by a community, not a single company. So how does this work? How does code actually get into Postgres? I recently had a patch submitted and committed and I want to share what I learned in that process. I’ll give you an overview of Postgres versions and how the underlying project codebase functions. I’ll also show you the process for submitting a patch and getting that tested and committed.
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
DAMA CDMP exam cram
1. P / 1D ATA M A N A G E M E N T A D V I S O R S
CDMP Certification – Exam Cram
Course Objectives: G a i n f a m i l i a r i t y w i t h
t h e C D M P e x a m i n a t i o n f o r m a t , t y p e s o f
q u e s t i o n s a n d s t r a t e g i e s f o r a n s w e r i n g
t h e m . U n d e r s t a n d a n d r e v i s e t h e m a j o r
s y l l a b u s p o i n t s . P r a c t i c e t a k i n g t h e
e x a m i n a t i o n s t o p a s s t h e C D M P
e x a m i n a t i o n s a n d g a i n r e c o g n i t i o n f o r
y o u r p r o f e s s i o n a l e x p e r i e n c e .
Pre requisites:
There are 2 levels of accomplishment for the CDMP certification,
Practitioner and Mastery.
Practitioner Certificate pre requisites:
• 2 years relevant Data Professional work experience
• Pass rate for all 3 exams 50%-69%
Mastery Certificate pre requisites:
• 4+ years relevant Data Professional work experience
• Pass rate for all 3 exams at 70% or better
Course Content:
• Workshop examination preparation for each of the 3
examinations
• IS Core Exam
• Data Management Core Exam
• A third elective exam of the participants choosing based on
one of the following:
• Data Warehousing
• Business Intelligence & Analytics
• Data & Information Quality
• Data Development
• Data Operations (DBA)
• Zachman Enterprise Architecture Framework
• Integrated IT Project Management
• Data Governance and Stewardship
• Pay exam fees only if you pass
• An optional (at no additional cost) examination to improve
scores on one exam (e.g. to attain “Mastery”) or resit a
failed exam.
Course Approach:
• Delivered over 3 days in an interactive workshop
• 3 live exams taken during the course. This enables successful
students to leave this course with a professional certification
• Pay exam fees only if you pass offer
• Optional 4th exam (at no additional cost) to improve score / resit
failed examination.
C o u r s e D e s c r i p t i o n : A 3 d a y
e x a m i n a t i o n p r e p a r a t i o n c o u r s e
i n c l u d i n g l i v e s i t t i n g o f e x a m i n a t i o n s
f o r s t u d e n t s w h o w i s h t o a t t a i n t h e
C e r t i f i e d D a t a M a n a g e m e n t
P r o f e s s i o n a l q u a l i f i c a t i o n .
3. P / 3D ATA M A N A G E M E N T A D V I S O R S
Christopher Bradley has spent 35 years in the
forefront of the Information Management field,
working for leading organisations in
Information Management Strategy, Data
Governance, Data Quality, Information
Assurance, Master Data Management, Metadata
Management, Data Warehouse and Business
Intelligence. Studying Chemical Engineering at
University Mr. Bradley’s post academic career
started for the UK Ministry of Defence where he
worked on several major Naval Database
systems and on the development of the ICL
Data Dictionary System (DDS). His career
included Volvo as lead data base architect,
Thorn EMI as Head of Data Management,
Readers Digest Inc as European CIO, and
Coopers and Lybrand (later PWC) where he
established the International Data Management
specialist practice. During this time he led many
major international assignments including Data
Management Strategies, Data Warehouse
Implementations and establishment of data
governance structures and the largest Data
Management strategy ever undertaken in
Europe. After PWC Chris created and ran a UK
Consultancy practice specializing in Information
Management and led many Information
Management strategy assignments in the
Financial Services, Oil and Gas and Life Sciences
sectors.
Chris works with International clients including
Alinma Bank, American Express, ANZ, Bank of
England, BP, Celgene, GSK, HSBC, Shell, TOTAL,
Statoil, Saudi Aramco, Riyad Bank, and Emirates
NBD. Most recently he has delivered an MDM
review for a Global Pharmaceutical
organization, a comprehensive appraisal of
Information Management practices at an Oil &
Gas super major, an Enterprise Information
Management strategy for a Life Sciences
organization, a Data Governance strategy for a
Middle East Bank, and Information
Management training for Retail, Oil & Gas and
Financial services companies.
Chris advises Global organizations on
Information Strategy, Data Governance,
Information Management best practice and
how organisations can genuinely manage
Information as a critical corporate asset.
Frequently he is engaged to evangelise
Information Management and Data Governance
to Executive management, to introduce data
governance and new business processes for
Information Management and to deliver
training and mentoring.
Chris is an acknowledged thought leader in
Information Strategy with considerable
expertise in Enterprise Information
Management, Information Strategy
development, Data Governance, Master and
Reference Data Management, Information
Assurance, Information Exploitation, Metadata
Management and Information Quality, and has
successfully introduced information led
business transformation programmes across
multiple geographies.
Christopher Bradley