The data governance approach is a combination of processes and practices which help to ensure the management od data assets within an organization and enterprise.
7 best tips to winning successful data governance shopiawilson
In this PPT, We describing the, 7 best tips winning successful data governance. data governance approach ensures that fair people are assigned the right data responsibilities.
How is data management different from information management?shopiawilson
An effective data management strategy allows the process of businesses to know whether the data they are accessing is old and current data, it will be safe and valuable for analysis.
In this PPT, We describing the important things about Data Management and Data Governance. The data governance approach provides the right practices and processes that help an enterprise manage its data flows.
Real-World Data Governance Webinar: Using Data Governance to Achieve Data Qua...DATAVERSITY
Data Governance programs can focus on improving the quality of data. Improvements in quality require that people are held formally accountable for following defined processes for defining, producing and using data across the organization. These processes become the focal point of institutionalizing data quality.
In this month’s installment of the Real-World Data Governance webinar series, Bob Seiner will speak about how to focus your data governance program on improving the quality of data across the organization. Bob will talk about the data governance roles and processes required change organizational behavior associated with defining, producing and using quality data.
In the webinar Bob will discuss:
Defining data governance in terms of data quality
Delivering roles appropriate for improving data quality
Selecting appropriate data quality processes to govern
Using working groups to focus on data quality projects
Measuring quality to demonstrate governance performance
How to Strengthen Enterprise Data Governance with Data QualityDATAVERSITY
If your organization is in a highly-regulated industry – or relies on data for competitive advantage – data governance is undoubtedly a top priority. Whether you’re focused on “defensive” data governance (supporting regulatory compliance and risk management) or “offensive” data governance (extracting the maximum value from your data assets, and minimizing the cost of bad data), data quality plays a critical role in ensuring success.
Join our webinar to learn how enterprise data quality drives stronger data governance, including:
The overlaps between data governance and data quality
The “data” dependencies of data governance – and how data quality addresses them
Key considerations for deploying data quality for data governance
Data-Ed Online Webinar: Data Governance StrategiesDATAVERSITY
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
How to Build & Sustain a Data Governance Operating Model DATUM LLC
Learn how to execute a data governance strategy through creation of a successful business case and operating model.
Originally presented to an audience of 400+ at the Master Data Management & Data Governance Summit.
Visit www.datumstrategy.com for more!
7 best tips to winning successful data governance shopiawilson
In this PPT, We describing the, 7 best tips winning successful data governance. data governance approach ensures that fair people are assigned the right data responsibilities.
How is data management different from information management?shopiawilson
An effective data management strategy allows the process of businesses to know whether the data they are accessing is old and current data, it will be safe and valuable for analysis.
In this PPT, We describing the important things about Data Management and Data Governance. The data governance approach provides the right practices and processes that help an enterprise manage its data flows.
Real-World Data Governance Webinar: Using Data Governance to Achieve Data Qua...DATAVERSITY
Data Governance programs can focus on improving the quality of data. Improvements in quality require that people are held formally accountable for following defined processes for defining, producing and using data across the organization. These processes become the focal point of institutionalizing data quality.
In this month’s installment of the Real-World Data Governance webinar series, Bob Seiner will speak about how to focus your data governance program on improving the quality of data across the organization. Bob will talk about the data governance roles and processes required change organizational behavior associated with defining, producing and using quality data.
In the webinar Bob will discuss:
Defining data governance in terms of data quality
Delivering roles appropriate for improving data quality
Selecting appropriate data quality processes to govern
Using working groups to focus on data quality projects
Measuring quality to demonstrate governance performance
How to Strengthen Enterprise Data Governance with Data QualityDATAVERSITY
If your organization is in a highly-regulated industry – or relies on data for competitive advantage – data governance is undoubtedly a top priority. Whether you’re focused on “defensive” data governance (supporting regulatory compliance and risk management) or “offensive” data governance (extracting the maximum value from your data assets, and minimizing the cost of bad data), data quality plays a critical role in ensuring success.
Join our webinar to learn how enterprise data quality drives stronger data governance, including:
The overlaps between data governance and data quality
The “data” dependencies of data governance – and how data quality addresses them
Key considerations for deploying data quality for data governance
Data-Ed Online Webinar: Data Governance StrategiesDATAVERSITY
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
How to Build & Sustain a Data Governance Operating Model DATUM LLC
Learn how to execute a data governance strategy through creation of a successful business case and operating model.
Originally presented to an audience of 400+ at the Master Data Management & Data Governance Summit.
Visit www.datumstrategy.com for more!
RWDG Webinar: Align Data Modeling with Data GovernanceDATAVERSITY
Data Modeling can be described as the discipline of data definition and database design. Data Governance must be applied to the definition, production, and usage of data in order to be effective. So therefore data modeling is an effective way to initiate a program to govern your data.
Join Bob Seiner for this month’s installment of the RWDG webinar series that will focus on how to align data modeling as a core competency of an effective data governance program. Data modeling that results in solid business definition and database design lays the groundwork for improved business understanding of the organization’s most important data.
In this webinar Bob will discuss:
Data modeling as a data governance discipline
Using data modeling to improve the business understanding of data
Why the data model is a key data governance artifact
How to use the data model as an effective communications tool
Including modeling as a core service associated with data governance
Formalize Data Governance with Policies and ProceduresDATAVERSITY
Policies and procedures lie at the heart of institutionalizing data governance. Data Governance is defined as the act of “executing and enforcing authority” to follow the procedures and enforce the policies. You can formalize Data Governance by clearly defining and following policies and procedures.
Join Bob Seiner for this month’s installment of the Real-World Data Governance webinar series where he will discuss how data governance can be formalized in parallel to the delivery of data policy and detailed procedures. Challenges associated with the changing the behavior of the data stewards will be identified, discussed and resolved during this session.
In this webinar Bob will discuss:
The relationship between Data Governance and Data Policy
Core guidelines to embrace through policy
DG Roles and their importance to following Policies and Procedures
Using RACIs and similar constructs to formalize Data Governance
Measuring the results of formalizing policies and procedures
Most Common Data Governance Challenges in the Digital EconomyRobyn Bollhorst
Todays’ increasing emphasis on differentiation in the digital economy further complicates the data governance challenge. Learn about today’s common challenges and about the new adaptations that are required to support the digital era. Avoid the pitfalls and follow along on Johnson & Johnson’s journey to:
- Establish and scale a best in class enterprise data governance program
- Identify and focus on the most critical data and information to bolster incremental wins and garner executive support
- Ensure readiness for automation with SAP MDG on HANA
You Can’t Have Best in Class Governance Without Best in Class Data LineageDATAVERSITY
Without a complete and accurate understanding of how data flows throughout the organization, it is extremely difficult to establish the processes and metrics necessary for a successful data governance program. Best-in-class data lineage that provides multi-layered views of the data (cross-system, end-to-end and inner-lineage) plays a critical role in knowledge transfer, issue identification, information on the use of sources/resources, impact analysis, & definition clarity - all extremely necessary for best-in-class data governance.
In this presentation, you'll hear it straight from the horse's mouth as Anilh Rameshwar, Data Architect at Zego, shares exactly how automated data lineage provides his department with unprecedented visibility into their data, which is absolutely critical for the organization's data governance efforts.
Slides: Empowering Data Consumers to Deliver Business ValueDATAVERSITY
Today, the role of Chief Data Officers and their teams has expanded from risk and compliance-based activities to delivering business value through trusted data. With the exponential growth in data and data consumers throughout an organization, ensuring that everyone gets the information that they need — and that it can be relied upon — is no small feat. CDOs need to rely on modern Data Governance leaders to discover where all of the data lives, define the context, measure the quality, ensure privacy, and then democratize data to empower the rest of the organization. Join us for this informative webinar as we highlight the challenges of today’s data leaders, how they can democratize trusted, secure data, and ultimately discover how to deliver business value.
Change management success for data governanceReid Elliott
As a data management professional you know that improving data governance is a top priority for many organisations. We know that data governance frameworks, processes and tools only enable benefits to the extent that our stakeholders adopt and use them effectively.
As well as technical proficiency and good project management and delivery, data governance success also requires effective change management. Preparing for change, managing change, and sustaining change are critical steps on the journey to effective data governance. So how can data management professionals best use change management principles and techniques to contribute to the success of our data governance initiatives?
This presentation was prepared to accompany a Data Management Association Australia webinar on change management success for data governance initiatives.
Aims of the facilitated discussion in the webinar were to explore:
How change management can enable the success of your data governance, reporting and analytics initiatives.
Common people change related challenges that many data governance, reporting and analytics initiatives need to navigate.
Change management techniques you can use to drive successful project delivery, change adoption and sustainable use of data governance, and reporting and analytics solutions.
How to identify the top change management priority for your own current project, and the change management techniques that you can use to address it.
Understanding the Data You Have Before Applying a Governance StrategyDATAVERSITY
Data Governance is a challenge in today’s world with massive amounts of data being created, duplicated, and stored. How can a company know they are making the best decisions about their data without truly understanding what they have? In this session, Darryl will walk you through a customer use case and explain the importance of truly knowing your data before applying a governance strategy.
You’ll walk away knowing how to
• Find your most sensitive data, and protect it
• Classify your massive unstructured data repositories, and manage it
• Identify ROT (Redundant/Obsolete/Trivial) and remove it
• Learn from your data to make data driven decisions
Knowing your data puts you in the driver’s seat to make decisions that will allow you to be pro-active against cyber threats, reduce costs from hardware to energy, and even reduce your data footprint.
Data governance and data quality are often described as two sides of the same coin. Data governance provides a data framework relevant to business needs, and data quality provides visibility into the health of the data. If you only have a data governance tool, you’re missing half the picture.
Trillium Discovery seamlessly integrates with Collibra for a complete, closed-loop data governance solution. Build your data quality rules in Collibra, and they are automatically passed to Trillium for data quality processing. The data quality results and metrics are then passed back to Collibra – allowing data stewards and business users to see the health of the data right within their Collibra dashboard.
View this webinar on-demand to see how you can leverage this integration in your organization to readily build, apply, and execute business rules based on data governance policies within Collibra.
Slides: Applying Artificial Intelligence (AI) in All the Right Places in the ...DATAVERSITY
Data and Analytics are fundamental to digital transformation, yet many companies are still under-utilizing them. To go full throttle, AI and automation technologies can be added across the full spectrum of your data journey to truly re-imagine processes and business models.
Join Information Builders for this webinar on how AI:
• Augments your traditional business intelligence and analytics systems
• Minimizes manual inefficiencies with the way data is generated, collected, cleansed, and organized
• Helps you realize substantial performance gains with use cases such as churn forecasting, predictive maintenance, supply chain planning, risk mitigation, and more
Big data governance as a corporate governance imperativeGuy Pearce
Poor data governance impacts reputation risk by data breach, by privacy violations and by acting on poor quality data. Furthermore, there are some important differences in what data governance means for big data compared to data governance for operational data.
That poor data governance impacts reputation risk means it has considerable implications for the Board of Directors, for whom reputation risk is the number one risk according to Deloitte (2013).
This presentation targeting the Board of Directors and the C-Suite and presented at the National Data Governance and Privacy Congress in Calgary, Canada presented some reasons why data governance is critical, from the perspective of both the C-Suite and the Board of Directors.
(Also on YouTube at http://youtu.be/QR4KO3Yx0n4)
Data Governance Roles as the Backbone of Your ProgramDATAVERSITY
The method you follow to form your Data Governance roles and responsibilities will impact the success of your program. There are industry-standard roles that require adjustment to fit the culture of your organization when getting started, gaining acceptance, and demonstrating sustained value. Roles are the backbone of a productive Data Governance program.
Bob Seiner will share his updated operating model of roles and responsibilities in this topical RWDG webinar. The model Bob uses is meant to overlay your present organizational structure rather than requiring you to try and plug your organization into someone else’s model. This webinar will provide everything you need to know about Data Governance roles.
Bob will address the following in this webinar:
• An operating model of Data Governance roles and responsibilities
• How to customize the model to mimic your existing structure
• The meaning behind the oft-used “roles pyramid”
• Detailed responsibilities at each level of the organization
• Using the model to influence Data Governance acceptance
Building an Effective Data Management StrategyHarley Capewell
In June 2013, Experian hosted a Data
Management Summit in London, with over
100 delegates from the public, private and
third sectors. Speakers from Experian
and across the data industry explored the
challenges of developing and implementing
data quality strategies - and how to
overcome them. Read on for more information.
The Chief Data Officer Agenda: Metrics for Information and Data ManagementDATAVERSITY
Welcome to The Chief Data Officer Agenda, a DATAVERSITY monthly webinar focused on the emerging priorities of the Chief Data Officer (CDO). What issues are CDOs facing now, and what should be on their Agenda. The webinar series is moderated by DATAVERSITY CEO and Founder, Tony Shaw, who will be joined each month by guest experts to discuss the requirements and demands on the burgeoning CDO role.
This month in the series:
The value proposition of enterprise information management is founded on Information being treated as an Asset. Information management professionals concur, but CxOs will say "So what?" In most organizations, they are both right! The conflict starts with one group thinking metaphorically, and the other literally. CDOs know that “Information asset” needs to be more than a metaphor…it has to be actionable. When you’re in charge of the application and value of data, how do you measure that? How do you measure progress? What types of metrics are there and which ones actually work? There is a lot more to measuring the value of information than common ROI.
This presentation will give you some starting points for real information asset management and information economics. You’ll learn some of the techniques being used successfully today, and considerations for quantifying the value and progress of information management. There is a means of reconciliation between the metaphors and reality, and this talk will outline a vision for the future, but with practical steps to help you get there.
How to Implement Data Governance Best PracticeDATAVERSITY
Data Governance Best Practice is defined as basis and guidelines for suggested governing activities. Organizations define best practices to be used as a point of comparison when determining their readiness, willingness and actions necessary to put a Data Governance program in place. But what are the best practices and how can they be implemented? This webinar will address these questions and more.
In this RWDG webinar, Bob Seiner will talk about how to create, validate, assess and implement Data Governance Best Practice with immediate impact on present and future Data Governance activities. The result of a Best Practice assessment is a thorough actionable plan focused on demonstrating value from your Data Governance program.This webinar will cover:
• Two Criteria for Data Governance Best Practice Development
• How to Assess against Best Practice to Build Program Success
• Examples of Industry Selected DG Best Practice
• How to Communicate DG Best Practice in a Non-Threatening Way
• How to Build DG Best Practice into Daily Operations
What is the value of data? Data governance must look beyond master data to deliver real value.
Visit www,masterdata.co.za/index.php/data-governance-solutions
Real-World Data Governance: Governance Risk and ComplianceDATAVERSITY
The target of many a Data Governance Program is to nail their regulatory and compliance requirements first to appease the government and industry regulators before doing anything else. Risk Management, as a practice, is already in place in most organizations under a variety of names. Even though most organizations do not consider Risk Management the same thing as Data Governance, the similarities abound. Compliance is not optional. Nothing about Regulatory and Compliance mentions optional. Governance is not optional either.
The session will cover:
Risk Management Vs. Data Governance – A Close Comparison
Risk Management as the Face of Data Governance
Measuring Success of Governance in terms of Risk Management
Using Risk and Compliance to Explain Governance
Using “Not Optional” as Your Crutch
RWDG Webinar: Align Data Modeling with Data GovernanceDATAVERSITY
Data Modeling can be described as the discipline of data definition and database design. Data Governance must be applied to the definition, production, and usage of data in order to be effective. So therefore data modeling is an effective way to initiate a program to govern your data.
Join Bob Seiner for this month’s installment of the RWDG webinar series that will focus on how to align data modeling as a core competency of an effective data governance program. Data modeling that results in solid business definition and database design lays the groundwork for improved business understanding of the organization’s most important data.
In this webinar Bob will discuss:
Data modeling as a data governance discipline
Using data modeling to improve the business understanding of data
Why the data model is a key data governance artifact
How to use the data model as an effective communications tool
Including modeling as a core service associated with data governance
Formalize Data Governance with Policies and ProceduresDATAVERSITY
Policies and procedures lie at the heart of institutionalizing data governance. Data Governance is defined as the act of “executing and enforcing authority” to follow the procedures and enforce the policies. You can formalize Data Governance by clearly defining and following policies and procedures.
Join Bob Seiner for this month’s installment of the Real-World Data Governance webinar series where he will discuss how data governance can be formalized in parallel to the delivery of data policy and detailed procedures. Challenges associated with the changing the behavior of the data stewards will be identified, discussed and resolved during this session.
In this webinar Bob will discuss:
The relationship between Data Governance and Data Policy
Core guidelines to embrace through policy
DG Roles and their importance to following Policies and Procedures
Using RACIs and similar constructs to formalize Data Governance
Measuring the results of formalizing policies and procedures
Most Common Data Governance Challenges in the Digital EconomyRobyn Bollhorst
Todays’ increasing emphasis on differentiation in the digital economy further complicates the data governance challenge. Learn about today’s common challenges and about the new adaptations that are required to support the digital era. Avoid the pitfalls and follow along on Johnson & Johnson’s journey to:
- Establish and scale a best in class enterprise data governance program
- Identify and focus on the most critical data and information to bolster incremental wins and garner executive support
- Ensure readiness for automation with SAP MDG on HANA
You Can’t Have Best in Class Governance Without Best in Class Data LineageDATAVERSITY
Without a complete and accurate understanding of how data flows throughout the organization, it is extremely difficult to establish the processes and metrics necessary for a successful data governance program. Best-in-class data lineage that provides multi-layered views of the data (cross-system, end-to-end and inner-lineage) plays a critical role in knowledge transfer, issue identification, information on the use of sources/resources, impact analysis, & definition clarity - all extremely necessary for best-in-class data governance.
In this presentation, you'll hear it straight from the horse's mouth as Anilh Rameshwar, Data Architect at Zego, shares exactly how automated data lineage provides his department with unprecedented visibility into their data, which is absolutely critical for the organization's data governance efforts.
Slides: Empowering Data Consumers to Deliver Business ValueDATAVERSITY
Today, the role of Chief Data Officers and their teams has expanded from risk and compliance-based activities to delivering business value through trusted data. With the exponential growth in data and data consumers throughout an organization, ensuring that everyone gets the information that they need — and that it can be relied upon — is no small feat. CDOs need to rely on modern Data Governance leaders to discover where all of the data lives, define the context, measure the quality, ensure privacy, and then democratize data to empower the rest of the organization. Join us for this informative webinar as we highlight the challenges of today’s data leaders, how they can democratize trusted, secure data, and ultimately discover how to deliver business value.
Change management success for data governanceReid Elliott
As a data management professional you know that improving data governance is a top priority for many organisations. We know that data governance frameworks, processes and tools only enable benefits to the extent that our stakeholders adopt and use them effectively.
As well as technical proficiency and good project management and delivery, data governance success also requires effective change management. Preparing for change, managing change, and sustaining change are critical steps on the journey to effective data governance. So how can data management professionals best use change management principles and techniques to contribute to the success of our data governance initiatives?
This presentation was prepared to accompany a Data Management Association Australia webinar on change management success for data governance initiatives.
Aims of the facilitated discussion in the webinar were to explore:
How change management can enable the success of your data governance, reporting and analytics initiatives.
Common people change related challenges that many data governance, reporting and analytics initiatives need to navigate.
Change management techniques you can use to drive successful project delivery, change adoption and sustainable use of data governance, and reporting and analytics solutions.
How to identify the top change management priority for your own current project, and the change management techniques that you can use to address it.
Understanding the Data You Have Before Applying a Governance StrategyDATAVERSITY
Data Governance is a challenge in today’s world with massive amounts of data being created, duplicated, and stored. How can a company know they are making the best decisions about their data without truly understanding what they have? In this session, Darryl will walk you through a customer use case and explain the importance of truly knowing your data before applying a governance strategy.
You’ll walk away knowing how to
• Find your most sensitive data, and protect it
• Classify your massive unstructured data repositories, and manage it
• Identify ROT (Redundant/Obsolete/Trivial) and remove it
• Learn from your data to make data driven decisions
Knowing your data puts you in the driver’s seat to make decisions that will allow you to be pro-active against cyber threats, reduce costs from hardware to energy, and even reduce your data footprint.
Data governance and data quality are often described as two sides of the same coin. Data governance provides a data framework relevant to business needs, and data quality provides visibility into the health of the data. If you only have a data governance tool, you’re missing half the picture.
Trillium Discovery seamlessly integrates with Collibra for a complete, closed-loop data governance solution. Build your data quality rules in Collibra, and they are automatically passed to Trillium for data quality processing. The data quality results and metrics are then passed back to Collibra – allowing data stewards and business users to see the health of the data right within their Collibra dashboard.
View this webinar on-demand to see how you can leverage this integration in your organization to readily build, apply, and execute business rules based on data governance policies within Collibra.
Slides: Applying Artificial Intelligence (AI) in All the Right Places in the ...DATAVERSITY
Data and Analytics are fundamental to digital transformation, yet many companies are still under-utilizing them. To go full throttle, AI and automation technologies can be added across the full spectrum of your data journey to truly re-imagine processes and business models.
Join Information Builders for this webinar on how AI:
• Augments your traditional business intelligence and analytics systems
• Minimizes manual inefficiencies with the way data is generated, collected, cleansed, and organized
• Helps you realize substantial performance gains with use cases such as churn forecasting, predictive maintenance, supply chain planning, risk mitigation, and more
Big data governance as a corporate governance imperativeGuy Pearce
Poor data governance impacts reputation risk by data breach, by privacy violations and by acting on poor quality data. Furthermore, there are some important differences in what data governance means for big data compared to data governance for operational data.
That poor data governance impacts reputation risk means it has considerable implications for the Board of Directors, for whom reputation risk is the number one risk according to Deloitte (2013).
This presentation targeting the Board of Directors and the C-Suite and presented at the National Data Governance and Privacy Congress in Calgary, Canada presented some reasons why data governance is critical, from the perspective of both the C-Suite and the Board of Directors.
(Also on YouTube at http://youtu.be/QR4KO3Yx0n4)
Data Governance Roles as the Backbone of Your ProgramDATAVERSITY
The method you follow to form your Data Governance roles and responsibilities will impact the success of your program. There are industry-standard roles that require adjustment to fit the culture of your organization when getting started, gaining acceptance, and demonstrating sustained value. Roles are the backbone of a productive Data Governance program.
Bob Seiner will share his updated operating model of roles and responsibilities in this topical RWDG webinar. The model Bob uses is meant to overlay your present organizational structure rather than requiring you to try and plug your organization into someone else’s model. This webinar will provide everything you need to know about Data Governance roles.
Bob will address the following in this webinar:
• An operating model of Data Governance roles and responsibilities
• How to customize the model to mimic your existing structure
• The meaning behind the oft-used “roles pyramid”
• Detailed responsibilities at each level of the organization
• Using the model to influence Data Governance acceptance
Building an Effective Data Management StrategyHarley Capewell
In June 2013, Experian hosted a Data
Management Summit in London, with over
100 delegates from the public, private and
third sectors. Speakers from Experian
and across the data industry explored the
challenges of developing and implementing
data quality strategies - and how to
overcome them. Read on for more information.
The Chief Data Officer Agenda: Metrics for Information and Data ManagementDATAVERSITY
Welcome to The Chief Data Officer Agenda, a DATAVERSITY monthly webinar focused on the emerging priorities of the Chief Data Officer (CDO). What issues are CDOs facing now, and what should be on their Agenda. The webinar series is moderated by DATAVERSITY CEO and Founder, Tony Shaw, who will be joined each month by guest experts to discuss the requirements and demands on the burgeoning CDO role.
This month in the series:
The value proposition of enterprise information management is founded on Information being treated as an Asset. Information management professionals concur, but CxOs will say "So what?" In most organizations, they are both right! The conflict starts with one group thinking metaphorically, and the other literally. CDOs know that “Information asset” needs to be more than a metaphor…it has to be actionable. When you’re in charge of the application and value of data, how do you measure that? How do you measure progress? What types of metrics are there and which ones actually work? There is a lot more to measuring the value of information than common ROI.
This presentation will give you some starting points for real information asset management and information economics. You’ll learn some of the techniques being used successfully today, and considerations for quantifying the value and progress of information management. There is a means of reconciliation between the metaphors and reality, and this talk will outline a vision for the future, but with practical steps to help you get there.
How to Implement Data Governance Best PracticeDATAVERSITY
Data Governance Best Practice is defined as basis and guidelines for suggested governing activities. Organizations define best practices to be used as a point of comparison when determining their readiness, willingness and actions necessary to put a Data Governance program in place. But what are the best practices and how can they be implemented? This webinar will address these questions and more.
In this RWDG webinar, Bob Seiner will talk about how to create, validate, assess and implement Data Governance Best Practice with immediate impact on present and future Data Governance activities. The result of a Best Practice assessment is a thorough actionable plan focused on demonstrating value from your Data Governance program.This webinar will cover:
• Two Criteria for Data Governance Best Practice Development
• How to Assess against Best Practice to Build Program Success
• Examples of Industry Selected DG Best Practice
• How to Communicate DG Best Practice in a Non-Threatening Way
• How to Build DG Best Practice into Daily Operations
What is the value of data? Data governance must look beyond master data to deliver real value.
Visit www,masterdata.co.za/index.php/data-governance-solutions
Real-World Data Governance: Governance Risk and ComplianceDATAVERSITY
The target of many a Data Governance Program is to nail their regulatory and compliance requirements first to appease the government and industry regulators before doing anything else. Risk Management, as a practice, is already in place in most organizations under a variety of names. Even though most organizations do not consider Risk Management the same thing as Data Governance, the similarities abound. Compliance is not optional. Nothing about Regulatory and Compliance mentions optional. Governance is not optional either.
The session will cover:
Risk Management Vs. Data Governance – A Close Comparison
Risk Management as the Face of Data Governance
Measuring Success of Governance in terms of Risk Management
Using Risk and Compliance to Explain Governance
Using “Not Optional” as Your Crutch
The CFO Guide to Data with Deloitte & WorkdayWorkday, Inc.
A recent explosion of data and rapidly evolving tools and techniques for managing it have made it difficult to turn data into value.
View this deck to hear how Deloitte and Workday are helping organizations get a handle on their data, deploying automated, analytics-based planning models, streamlining finance operations, and becoming truly decision ready.
A Business-first Approach to Building Data Governance ProgramsPrecisely
Traditional data governance initiatives fail by focusing too heavily on policies, compliance, and enforcement, which quickly lose business interest and support. This leaves data management and governance leaders having to continually make the case for data governance to secure business adoption. In this presentation, we share a lean, business-first data governance approach that connects key initiatives to governance capabilities and quickly delivers business value for the long-term.
The data management procedure employed by your firm is capable of building your brand or breaking it all over. So, be wise in choosing the right strategy.
Linking Data Governance to Business GoalsPrecisely
The importance of data to businesses has increased exponentially over recent years as companies seek benefits such as gains in efficiency, the ability to respond to growing privacy regulations scale quickly and increased and increase customer loyalty.
Despite being a vital part of any Data Transformation, Data Governance has sometimes been misrepresented as a restrictive and controlling process leaving governance leaders having to continually make the case for business buy-in.
In this on-demand webinar we will explore the concept of business-first Data Governance, an approach that promotes adoption by the organisation, lays the foundation for data integrity and consistently delivers business value in the long term.
7 steps for guides how to build a successful data strategyshopiawilson
Enterprise Data Strategy decisions and sets of choices that together, chart a high-level course of action to get high-level goals. Some important steps to build a successful data strategy.
Presentation to introduce information governance. This should be used in conjunction with the paper I published on my website. A full information governance methodology, with research included from the foremost authorities on data governance.
An effective data management solution can help businesses achieve best business practices and quality customer service responses. It helps make the process easier and faster.
Enterprise-Level Preparation for Master Data Management.pdfAmeliaWong21
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.
Federated data organizations in public sector face more challenges today than ever before. As discovered via research performed by North Highland Consulting, these are the top issues you are most likely experiencing:
• Knowing what data is available to support programs and other business functions
• Data is more difficult to access
• Without insight into the lineage of data, it is risky to use as the basis for critical decisions
• Analyzing data and extracting insights to influence outcomes is difficult at best
The solution to solving these challenges lies in creating a holistic enterprise data governance program and enforcing the program with a full-featured enterprise data management platform. Kreig Fields, Principle, Public Sector Data and Analytics, from North Highland Consulting and Rob Karel, Vice President, Product Strategy and Product Marketing, MDM from Informatica will walk through a pragmatic, “How To” approach, full of useful information on how you can improve your agency’s data governance initiatives.
Learn how to kick start your data governance intiatives and how an enterprise data management platform can help you:
• Innovate and expose hidden opportunities
• Break down data access barriers and ensure data is trusted
• Provide actionable information at the speed of business
Data has enormous power in the present day. As a primary asset of organizations, it is revolutionizing various sectors. Simply put, data is the information stored in or utilised by a computer, smartphone, or other electronic devices. The process of "Datafication," which includes the identification of data, is seen by businesses and analysts worldwide as the way of the future of commerce
Data has enormous power in the present day. As a primary asset of organizations, it is revolutionizing various sectors. Simply put, data is the information stored in or utilised by a computer, smartphone, or other electronic devices. The process of "Datafication," which includes the identification of data, is seen by businesses and analysts worldwide as the way of the future of commerce.
Similar to 5 top reasons why data governance needs to business success (20)
Benefits of data management assessment for an enterpriseshopiawilson
In today’s digital age, one of the primary requirements for a successful business venture is having an efficient system of management and analysis of all the vital information. Enterprises employ data management services for controlling the flow and evaluation of information in order to increase their efficiency but hardly ever give a thought to undertake a data management assessment to analyze the effectiveness of the methodologies being used for the purpose.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
2. INTRODUCTION
Implementation of good data
governance is one of the unique
policy using which an enterprise
and company could transform a
crude of data into a valuable asset.
The business and organization
usually use the optimized form of
best data streaming by their own
data governance approach strategy
for maximizing the profit involved.
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3. Understand Data
Governance
Data Governance is a combination of
processes and practices which help to
ensure the management of data assets
within an organization.
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4. Some Essential Points For Original
Data Governance Strategy
● Information regarding accounts and consumers such as past records,
demographics and interactions etc.
● Included the activities from both parties.
● Referential Data
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5. Making Money And Additional
Saving
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6. Maintaining The
Fixture Of Data
The Fixture of data can only be agreed
upon by implementing the intelligent
data governance strategy.
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8. Clarity Of Data
● Importance and Function of the given data
● External and Internal statistics involved
● Risk involved
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