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Reference matter data management: Two categories of structured data : Master data: is data associated with core business entities such as customer, product, asset, etc. Transaction data: is the recording of business transactions such as orders in manufacturing, loan and credit card payments in banking, and product sales in retail. Reference data: is any kind of data that is used solely to categorize other data found in a database, or solely for relating data in a database to information beyond the boundaries of the enterprise .
Reference master data management
Reference master data management
Dr. Hamdan Al-Sabri
Master Data Management (MDM) can provide significant value to the organization in creating consistent key data assets such as Customer, Product, Supplier, Patient, and the list goes on. But getting MDM “right” requires a strategic mix of Data Architecture, business process, and Data Governance. Join this webinar to learn how to find the “sweet spot” between technology, design, process, and people for your MDM initiative.
Master Data Management - Aligning Data, Process, and Governance
Master Data Management - Aligning Data, Process, and Governance
DATAVERSITY
MDM Strategy & Roadmap
MDM Strategy & Roadmap
victorlbrown
Mdm: why, when, how
Mdm: why, when, how
Jean-Michel Franco
Despite its immaterial nature, data has a tendency to pile up as time goes on, and can quickly be rendered unusable or obsolete without careful maintenance and streamlining of processes for its management. This presentation will provide you with an understanding of reference and Master Data Management (MDM), one such method for keeping mass amounts of business data organized and functional towards achieving business goals. MDM’s guiding principles include the establishment and implementation of authoritative data sources and effective means of delivering data to various business processes, as well as increases to the quality of information used in organizational analytical functions (such as BI). To that end, attendees of this webinar will learn how to: Structure their Data Management processes around these principles Incorporate Data Quality engineering into the planning of reference and MDM Understand why MDM is so critical to their organization’s overall data strategy Discuss foundational MDM concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
The Importance of Master Data Management
The Importance of Master Data Management
DATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Master Data Management – Aligning Data, Process, and Governance
Master Data Management – Aligning Data, Process, and Governance
DATAVERSITY
In MDM (Master Data Management) area, there are evolution of maturity. This slide explain briefly characteristics of each level.
5 Level of MDM Maturity
5 Level of MDM Maturity
PanaEk Warawit
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
How to identify the correct Master Data subject areas & tooling for your MDM...
How to identify the correct Master Data subject areas & tooling for your MDM...
Christopher Bradley
Empfohlen
Reference matter data management: Two categories of structured data : Master data: is data associated with core business entities such as customer, product, asset, etc. Transaction data: is the recording of business transactions such as orders in manufacturing, loan and credit card payments in banking, and product sales in retail. Reference data: is any kind of data that is used solely to categorize other data found in a database, or solely for relating data in a database to information beyond the boundaries of the enterprise .
Reference master data management
Reference master data management
Dr. Hamdan Al-Sabri
Master Data Management (MDM) can provide significant value to the organization in creating consistent key data assets such as Customer, Product, Supplier, Patient, and the list goes on. But getting MDM “right” requires a strategic mix of Data Architecture, business process, and Data Governance. Join this webinar to learn how to find the “sweet spot” between technology, design, process, and people for your MDM initiative.
Master Data Management - Aligning Data, Process, and Governance
Master Data Management - Aligning Data, Process, and Governance
DATAVERSITY
MDM Strategy & Roadmap
MDM Strategy & Roadmap
victorlbrown
Mdm: why, when, how
Mdm: why, when, how
Jean-Michel Franco
Despite its immaterial nature, data has a tendency to pile up as time goes on, and can quickly be rendered unusable or obsolete without careful maintenance and streamlining of processes for its management. This presentation will provide you with an understanding of reference and Master Data Management (MDM), one such method for keeping mass amounts of business data organized and functional towards achieving business goals. MDM’s guiding principles include the establishment and implementation of authoritative data sources and effective means of delivering data to various business processes, as well as increases to the quality of information used in organizational analytical functions (such as BI). To that end, attendees of this webinar will learn how to: Structure their Data Management processes around these principles Incorporate Data Quality engineering into the planning of reference and MDM Understand why MDM is so critical to their organization’s overall data strategy Discuss foundational MDM concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
The Importance of Master Data Management
The Importance of Master Data Management
DATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Master Data Management – Aligning Data, Process, and Governance
Master Data Management – Aligning Data, Process, and Governance
DATAVERSITY
In MDM (Master Data Management) area, there are evolution of maturity. This slide explain briefly characteristics of each level.
5 Level of MDM Maturity
5 Level of MDM Maturity
PanaEk Warawit
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
How to identify the correct Master Data subject areas & tooling for your MDM...
How to identify the correct Master Data subject areas & tooling for your MDM...
Christopher Bradley
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
The what, why, and how of master data management
The what, why, and how of master data management
Mohammad Yousri
Gartner will further examine key trends shaping the future MDM market during the Gartner MDM Summit 2011, 2-3 February in London. More information at www.europe.gartner.com/mdm
Gartner: Master Data Management Functionality
Gartner: Master Data Management Functionality
Gartner
Database Architechs has designed a step-by-step Master Data Management methodology http://www.dbarchitechs.com/?page=wp
Master Data Management methodology
Master Data Management methodology
Database Architechs
introduce Informatica MDM to provide a background about what we do, whom we have helped, and our key differentiators.
Informatica MDM Presentation
Informatica MDM Presentation
MaxHung
An insightful guide to understand all about mastering data management.
Ebook - The Guide to Master Data Management
Ebook - The Guide to Master Data Management
Hazelknight Media & Entertainment Pvt Ltd
Gartner will further examine key trends shaping the future MDM market during the Gartner MDM Summit 2011, 2-3 February in London. More information at www.europe.gartner.com/mdm.
Gartner: Seven Building Blocks of Master Data Management
Gartner: Seven Building Blocks of Master Data Management
Gartner
Metadata is hotter than ever, according a number of recent DATAVERSITY surveys. More and more organizations are realizing that in order to drive business value from data, robust metadata is needed to gain the necessary context and lineage around key data assets. At the same time, industry regulations are driving the need for better transparency and understanding of information. While metadata has been managed for decades, new strategies & approaches have been developed to support the ever-evolving data landscape, and provide more innovative ways to drive business value from metadata. This webinar will provide an overview of metadata strategies & technologies available to today’s organization, and provide insights into building successful business strategies for metadata adoption & use.
Modern Metadata Strategies
Modern Metadata Strategies
DATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Master Data Management - Aligning Data, Process and Governance
Master Data Management - Aligning Data, Process and Governance
Precisely
SAP MDM expertise of SITA CORP
Mdm
Mdm
amithkulkarni
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.
Enterprise Architecture vs. Data Architecture
Enterprise Architecture vs. Data Architecture
DATAVERSITY
Data modelling for the business half day workshop presented at the Enterprise Data & Business Intelligence conference in London on November 3rd 2014 chris.bradley@dmadvisors.co.uk
Data modeling for the business
Data modeling for the business
Christopher Bradley
Roles and responsibilities are a critical component of every Data Governance program. Building a set of roles that are practical and that will not interfere with people’s “day jobs” is an important consideration that will influence how well your program is adopted. This tutorial focuses on sharing a proven model guaranteed to represent your organization. Join Bob Seiner for this lively webinar where he will dissect a complete Operating Model of Roles and Responsibilities that encompasses all levels of the organization. Seiner will detail the roles and describe the most effective way to associate people with the roles. You will walk out of this webinar with a model to apply to your organization. In this session Bob will share: - The five levels of Data Governance roles - A proven Operating Model of Roles and Responsibilities - How to customize the model to meet your requirements - Setting appropriate role expectations - How to operationalize the roles and demonstrate value
Driving Data Intelligence in the Supply Chain Through the Data Catalog at TJX
Driving Data Intelligence in the Supply Chain Through the Data Catalog at TJX
DATAVERSITY
The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy. Takeaways: Understanding why data governance can be tricky for most organizations Steps for improving data governance within your organization Guiding principles & lessons learned Understanding foundational data governance concepts based on the DAMA DMBOK
Data-Ed Webinar: Data Governance Strategies
Data-Ed Webinar: Data Governance Strategies
DATAVERSITY
Most people recognize that Data Stewards play an essential role in their Data Governance and Information Governance programs. However, the manner in which Data Stewards are used is not the same from organization to organization. How you use Data Stewards depends on your goals for Data Governance. Join Bob Seiner for this month’s RWDG webinar where he will share different ways to activate Data Stewards based on the purpose of your program. Bob will talk about options to extend existing Data Steward activity and how to build new functionality into the role of your Data Stewards. In this webinar, Bob will discuss: - The crucial role of the Data Steward in Data Governance - Different types of Data Stewards and what they do - Aligning Data Steward activities with program goals - Improving existing Data Steward actions - Finding new ways to use your Data Stewards
RWDG Slides: What is a Data Steward to do?
RWDG Slides: What is a Data Steward to do?
DATAVERSITY
In today’s digital economy, data drives the core processes that deliver profitability and growth - from marketing, to finance, to sales, supply chain, and more. It is also likely that for many large organizations much of their key data is retained in application packages from SAP, Oracle, Microsoft, Salesforce and others. In order to ensure that their foundational data infrastructure runs smoothly, most organizations have adopted a data governance initiative. These typically focus on the people and processes around managing data and information. Without an actionable link to the physical systems that run key business processes, however, governance programs can often lack the ‘teeth’ to effectively implement business change. Metadata management is a process that can link business processes and drivers with the technical applications that support them. This makes data governance actionable and relevant in today’s fast-paced and results-driven business environment. One of the challenges facing data governance teams however, is the variety in format, accessibility and complexity of metadata across the organization’s systems.
The Business Value of Metadata for Data Governance
The Business Value of Metadata for Data Governance
Roland Bullivant
In business, master data management is a method used to define and manage the critical data of an organization to provide, with data integration, a single point of reference.
Master Data Management
Master Data Management
Sreekanth Narendran
MDS - is the SQL Server solution for master data management, central repository for data, rule-based which can work with DQS.
Master Data Management
Master Data Management
MoniqueO Opris
Data Ownership: Most companies and organizations have this notion that data governance should be taken care of , by the Information Technology department, because IT owns the system which stores the data. The owner of the data is responsible for providing attributes to the data and answerable to any questions regarding data. The people answerable to these kinds of data are generally the ones involved in defining business rules, data cleaning and consolidation.? Data Stewardship:? Data stewards should be favorably those people who are familiar with the data. It is often seen that there is need to deploy several people, to handle and correct data, whereas a single data steward could have done the same job. Since the data being handled involves organizational level data, it is important that there are governance rules for this process.? If there is some certain rule in the data which causes large data volumes to fail, this rule should be fixed while data cleansing. So it is important to take care of the amount of clean data sent to the stewards, since we are not aware of which rules might trigger what amount of data.? Choice of data stewards is again a difficult selection. Data Security:? Although the master data is data on organization level, but there is some confidentiality level linked to it.? Not every employee has the authorization to view its aspects. Security rules can be applied to the data. The various departments in the organization must set different rules to the data they own. They need to grant permissions to these rules , so that the user can view the data. A large company can have data sourced out of many regions. It is to be ensured that they are responsible to correct only their own data.? Data survivorship: There are some guidelines which are set up by data governance. These rules can often change over hthe time according to new data sources being added. The changes made to the data , are communicated to the organization so that data stewards and users can understand the process. So from a data steward's point of view, it is important to apply security rules to the people who are involved in data handling and correction. This is a result of how data governance and data security can be applied while implementing MDM.? ?
Master Data Management
Master Data Management
Sabir Akhtar
3 Keys To Successful Master Data Management - Final Presentation
3 Keys To Successful Master Data Management - Final Presentation
James Chi
Data catalogs, business glossaries, and data dictionaries house metadata that is important to your organization’s governance of data. People in your organization need to be engaged in leveraging the tools, understanding the data that is available, who is responsible for the data, and knowing how to get their hands on the data to perform their job function. The metadata will not govern itself. Join Bob Seiner for the webinar where he will discuss how glossaries, dictionaries, and catalogs can result in effective Data Governance. People must have confidence in the metadata associated with the data that you need them to trust. Therefore, the metadata in your data catalog, business glossary, and data dictionary must result in governed data. Learn how glossaries, dictionaries, and catalogs can result in Data Governance in this webinar. Bob will discuss the following subjects in this webinar: - Successful Data Governance relies on value from very important tools - What it means to govern your data catalog, business glossary, and data dictionary - Why governing the metadata in these tools is important - The roles necessary to govern these tools - Governance expected from metadata in catalogs, glossaries, and dictionaries
Glossaries, Dictionaries, and Catalogs Result in Data Governance
Glossaries, Dictionaries, and Catalogs Result in Data Governance
DATAVERSITY
Rob Karel - Ensuring The Value Of Your Trusted Data - Data Quality Summit 2008
Rob Karel - Ensuring The Value Of Your Trusted Data - Data Quality Summit 2008
DataValueTalk
This presentation was created to provide some practical advise in aligning IT projects to business objectives for a firm.
Business Alignment
Business Alignment
Michael Galo
Weitere ähnliche Inhalte
Was ist angesagt?
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
The what, why, and how of master data management
The what, why, and how of master data management
Mohammad Yousri
Gartner will further examine key trends shaping the future MDM market during the Gartner MDM Summit 2011, 2-3 February in London. More information at www.europe.gartner.com/mdm
Gartner: Master Data Management Functionality
Gartner: Master Data Management Functionality
Gartner
Database Architechs has designed a step-by-step Master Data Management methodology http://www.dbarchitechs.com/?page=wp
Master Data Management methodology
Master Data Management methodology
Database Architechs
introduce Informatica MDM to provide a background about what we do, whom we have helped, and our key differentiators.
Informatica MDM Presentation
Informatica MDM Presentation
MaxHung
An insightful guide to understand all about mastering data management.
Ebook - The Guide to Master Data Management
Ebook - The Guide to Master Data Management
Hazelknight Media & Entertainment Pvt Ltd
Gartner will further examine key trends shaping the future MDM market during the Gartner MDM Summit 2011, 2-3 February in London. More information at www.europe.gartner.com/mdm.
Gartner: Seven Building Blocks of Master Data Management
Gartner: Seven Building Blocks of Master Data Management
Gartner
Metadata is hotter than ever, according a number of recent DATAVERSITY surveys. More and more organizations are realizing that in order to drive business value from data, robust metadata is needed to gain the necessary context and lineage around key data assets. At the same time, industry regulations are driving the need for better transparency and understanding of information. While metadata has been managed for decades, new strategies & approaches have been developed to support the ever-evolving data landscape, and provide more innovative ways to drive business value from metadata. This webinar will provide an overview of metadata strategies & technologies available to today’s organization, and provide insights into building successful business strategies for metadata adoption & use.
Modern Metadata Strategies
Modern Metadata Strategies
DATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Master Data Management - Aligning Data, Process and Governance
Master Data Management - Aligning Data, Process and Governance
Precisely
SAP MDM expertise of SITA CORP
Mdm
Mdm
amithkulkarni
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.
Enterprise Architecture vs. Data Architecture
Enterprise Architecture vs. Data Architecture
DATAVERSITY
Data modelling for the business half day workshop presented at the Enterprise Data & Business Intelligence conference in London on November 3rd 2014 chris.bradley@dmadvisors.co.uk
Data modeling for the business
Data modeling for the business
Christopher Bradley
Roles and responsibilities are a critical component of every Data Governance program. Building a set of roles that are practical and that will not interfere with people’s “day jobs” is an important consideration that will influence how well your program is adopted. This tutorial focuses on sharing a proven model guaranteed to represent your organization. Join Bob Seiner for this lively webinar where he will dissect a complete Operating Model of Roles and Responsibilities that encompasses all levels of the organization. Seiner will detail the roles and describe the most effective way to associate people with the roles. You will walk out of this webinar with a model to apply to your organization. In this session Bob will share: - The five levels of Data Governance roles - A proven Operating Model of Roles and Responsibilities - How to customize the model to meet your requirements - Setting appropriate role expectations - How to operationalize the roles and demonstrate value
Driving Data Intelligence in the Supply Chain Through the Data Catalog at TJX
Driving Data Intelligence in the Supply Chain Through the Data Catalog at TJX
DATAVERSITY
The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy. Takeaways: Understanding why data governance can be tricky for most organizations Steps for improving data governance within your organization Guiding principles & lessons learned Understanding foundational data governance concepts based on the DAMA DMBOK
Data-Ed Webinar: Data Governance Strategies
Data-Ed Webinar: Data Governance Strategies
DATAVERSITY
Most people recognize that Data Stewards play an essential role in their Data Governance and Information Governance programs. However, the manner in which Data Stewards are used is not the same from organization to organization. How you use Data Stewards depends on your goals for Data Governance. Join Bob Seiner for this month’s RWDG webinar where he will share different ways to activate Data Stewards based on the purpose of your program. Bob will talk about options to extend existing Data Steward activity and how to build new functionality into the role of your Data Stewards. In this webinar, Bob will discuss: - The crucial role of the Data Steward in Data Governance - Different types of Data Stewards and what they do - Aligning Data Steward activities with program goals - Improving existing Data Steward actions - Finding new ways to use your Data Stewards
RWDG Slides: What is a Data Steward to do?
RWDG Slides: What is a Data Steward to do?
DATAVERSITY
In today’s digital economy, data drives the core processes that deliver profitability and growth - from marketing, to finance, to sales, supply chain, and more. It is also likely that for many large organizations much of their key data is retained in application packages from SAP, Oracle, Microsoft, Salesforce and others. In order to ensure that their foundational data infrastructure runs smoothly, most organizations have adopted a data governance initiative. These typically focus on the people and processes around managing data and information. Without an actionable link to the physical systems that run key business processes, however, governance programs can often lack the ‘teeth’ to effectively implement business change. Metadata management is a process that can link business processes and drivers with the technical applications that support them. This makes data governance actionable and relevant in today’s fast-paced and results-driven business environment. One of the challenges facing data governance teams however, is the variety in format, accessibility and complexity of metadata across the organization’s systems.
The Business Value of Metadata for Data Governance
The Business Value of Metadata for Data Governance
Roland Bullivant
In business, master data management is a method used to define and manage the critical data of an organization to provide, with data integration, a single point of reference.
Master Data Management
Master Data Management
Sreekanth Narendran
MDS - is the SQL Server solution for master data management, central repository for data, rule-based which can work with DQS.
Master Data Management
Master Data Management
MoniqueO Opris
Data Ownership: Most companies and organizations have this notion that data governance should be taken care of , by the Information Technology department, because IT owns the system which stores the data. The owner of the data is responsible for providing attributes to the data and answerable to any questions regarding data. The people answerable to these kinds of data are generally the ones involved in defining business rules, data cleaning and consolidation.? Data Stewardship:? Data stewards should be favorably those people who are familiar with the data. It is often seen that there is need to deploy several people, to handle and correct data, whereas a single data steward could have done the same job. Since the data being handled involves organizational level data, it is important that there are governance rules for this process.? If there is some certain rule in the data which causes large data volumes to fail, this rule should be fixed while data cleansing. So it is important to take care of the amount of clean data sent to the stewards, since we are not aware of which rules might trigger what amount of data.? Choice of data stewards is again a difficult selection. Data Security:? Although the master data is data on organization level, but there is some confidentiality level linked to it.? Not every employee has the authorization to view its aspects. Security rules can be applied to the data. The various departments in the organization must set different rules to the data they own. They need to grant permissions to these rules , so that the user can view the data. A large company can have data sourced out of many regions. It is to be ensured that they are responsible to correct only their own data.? Data survivorship: There are some guidelines which are set up by data governance. These rules can often change over hthe time according to new data sources being added. The changes made to the data , are communicated to the organization so that data stewards and users can understand the process. So from a data steward's point of view, it is important to apply security rules to the people who are involved in data handling and correction. This is a result of how data governance and data security can be applied while implementing MDM.? ?
Master Data Management
Master Data Management
Sabir Akhtar
3 Keys To Successful Master Data Management - Final Presentation
3 Keys To Successful Master Data Management - Final Presentation
James Chi
Data catalogs, business glossaries, and data dictionaries house metadata that is important to your organization’s governance of data. People in your organization need to be engaged in leveraging the tools, understanding the data that is available, who is responsible for the data, and knowing how to get their hands on the data to perform their job function. The metadata will not govern itself. Join Bob Seiner for the webinar where he will discuss how glossaries, dictionaries, and catalogs can result in effective Data Governance. People must have confidence in the metadata associated with the data that you need them to trust. Therefore, the metadata in your data catalog, business glossary, and data dictionary must result in governed data. Learn how glossaries, dictionaries, and catalogs can result in Data Governance in this webinar. Bob will discuss the following subjects in this webinar: - Successful Data Governance relies on value from very important tools - What it means to govern your data catalog, business glossary, and data dictionary - Why governing the metadata in these tools is important - The roles necessary to govern these tools - Governance expected from metadata in catalogs, glossaries, and dictionaries
Glossaries, Dictionaries, and Catalogs Result in Data Governance
Glossaries, Dictionaries, and Catalogs Result in Data Governance
DATAVERSITY
Was ist angesagt?
(20)
The what, why, and how of master data management
The what, why, and how of master data management
Gartner: Master Data Management Functionality
Gartner: Master Data Management Functionality
Master Data Management methodology
Master Data Management methodology
Informatica MDM Presentation
Informatica MDM Presentation
Ebook - The Guide to Master Data Management
Ebook - The Guide to Master Data Management
Gartner: Seven Building Blocks of Master Data Management
Gartner: Seven Building Blocks of Master Data Management
Modern Metadata Strategies
Modern Metadata Strategies
Master Data Management - Aligning Data, Process and Governance
Master Data Management - Aligning Data, Process and Governance
Mdm
Mdm
Enterprise Architecture vs. Data Architecture
Enterprise Architecture vs. Data Architecture
Data modeling for the business
Data modeling for the business
Driving Data Intelligence in the Supply Chain Through the Data Catalog at TJX
Driving Data Intelligence in the Supply Chain Through the Data Catalog at TJX
Data-Ed Webinar: Data Governance Strategies
Data-Ed Webinar: Data Governance Strategies
RWDG Slides: What is a Data Steward to do?
RWDG Slides: What is a Data Steward to do?
The Business Value of Metadata for Data Governance
The Business Value of Metadata for Data Governance
Master Data Management
Master Data Management
Master Data Management
Master Data Management
Master Data Management
Master Data Management
3 Keys To Successful Master Data Management - Final Presentation
3 Keys To Successful Master Data Management - Final Presentation
Glossaries, Dictionaries, and Catalogs Result in Data Governance
Glossaries, Dictionaries, and Catalogs Result in Data Governance
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Building your IT strategy - a look at what goes into a successful IT strategy. Delivered at the Housing Technology Conference, February 27th 2014
Building your IT strategy (Housing Technology Conference 2014)
Building your IT strategy (Housing Technology Conference 2014)
dansimms
In this presentation, we'll help you better understand Master Data Management (MDM) and data governance, present some useful MDM and data governance best practices, talk about what works and what doesn’t, cover the importance of a holistic approach, and discuss how to get the political aspects right.
Best Practices in MDM, OAUG COLLABORATE 09
Best Practices in MDM, OAUG COLLABORATE 09
Hub Solution Designs, Inc.
Master Data Management (MDM) continues to play a foundational role in the Data Management Architecture of every 21st century enterprise. In a forward-looking organization, MDM is significant in the Enterprise Integration Hub.
Enterprise-Level Preparation for Master Data Management.pdf
Enterprise-Level Preparation for Master Data Management.pdf
AmeliaWong21
Mdm strategy
Mdm strategy
Andrew Bonanni
A presentation on practical application of a portfolio based approach to IT investments and Enterprise Architecture.
Managing Your IT Portfolio
Managing Your IT Portfolio
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How to rapidly model a business or department.
Si Eac San Diego Rapid Business Modeling V1.2 Generic (2)
Si Eac San Diego Rapid Business Modeling V1.2 Generic (2)
Bill Branson
For Educational Purposes.
Performance Measurement
Performance Measurement
lleuciuc1
Data Analytics is the process of extracting meaning from raw data using computer software. This process transforms organizes and models data to extract meaningful conclusions and identify patterns.
Data Analytics: Improving Business
Data Analytics: Improving Business
Symptai Consulting Limited
This presentation contains our view on how data can be Strategically managed and stewarded in an organization, and the categories where rules can be applied to facilitate that process.
SDM Presentation V1.0
SDM Presentation V1.0
KirSinc
Understand the nuances of data risk Management and their alignment with Data Management and Governance. Which organisation model will be a best fit to implement Data Risk Management in Governance.
Success by integrating risk management in data governance
Success by integrating risk management in data governance
Tejasvi Addagada, CBAP
strategy formulation
Strategy formulation
Strategy formulation
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Best Practices in MDM, OAUG COLLABORATE 09
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Fulfill your short term investment goals with 100% Transparency & Eliminating Financial risk.
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Business model Canvas (BMC) Value proposition Business model vs business plan Customer Segments Customer relationships Channels Key activities Key resources Revenue Streams Key partners Cost structure
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Falcon's Invoice Discounting: Your Path to Prosperity
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Master Data Management
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Reference Architecture Viewpoint
17.
Visible Security Architecture
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