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.
5 top reasons why data governance needs to business successshopiawilson
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.
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: Data Governance ExpectationsDATAVERSITY
When starting a Data Governance program, significant time, effort and bandwidth is typically spent selling the concept of data governance and telling people in your organization what data governance will do for them. This may not be the best strategy to take. We should focus on making Data Governance THEIR idea not ours.
Shouldn’t the strategy be that we get the business people from our organization to tell US why data governance is necessary and what data governance will do for them? If only we could get them to tell us these things? Maybe we can.
Join Bob Seiner and DATAVERSITY for this informative Real-World Data Governance webinar that will focus on getting THEM to tell US where data governance will add value. Seiner will review techniques for acquiring this information and will share information of where this information will add specific value to your data governance program. Some of those places may surprise you.
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.
5 top reasons why data governance needs to business successshopiawilson
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.
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: Data Governance ExpectationsDATAVERSITY
When starting a Data Governance program, significant time, effort and bandwidth is typically spent selling the concept of data governance and telling people in your organization what data governance will do for them. This may not be the best strategy to take. We should focus on making Data Governance THEIR idea not ours.
Shouldn’t the strategy be that we get the business people from our organization to tell US why data governance is necessary and what data governance will do for them? If only we could get them to tell us these things? Maybe we can.
Join Bob Seiner and DATAVERSITY for this informative Real-World Data Governance webinar that will focus on getting THEM to tell US where data governance will add value. Seiner will review techniques for acquiring this information and will share information of where this information will add specific value to your data governance program. Some of those places may surprise you.
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
Data Governance Best Practices and Lessons LearnedDATAVERSITY
Best practices and lessons learned are powerful tools used to assess an organization’s readiness and initial activities associated with delivering a Data Governance program. There are two criteria to determine if something is best practice for your organization. And the definition of data governance best practice is best way to learn from others and begin with the end in mind.
Bob Seiner will share industry data governance best practices in this month’s installment of the RWDG webinar series. Learn how to use the best practices defined in this webinar to address opportunities to improve your organization’s data governance implementation. Attend this webinar and learn that assessing your organization may not be as difficult as you think.
During this webinar Bob will discuss:
How to define data governance best practices for your organization
Criteria used to determine if a practice is best practice
How to assess your organization against industry best practice
Assessing risks associated with best practice gaps
Addressing opportunities to improve gaps uncovered in the assessment
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
How to get started on your data governance journey and support your cyber and information security programs. Presented at the AISA Cyber Conference Canberra March 2021
Real-World Data Governance: How to Write a Data Steward Job DescriptionDATAVERSITY
A Data Steward Job Description is a list of job responsibilities that a Data Steward uses for tasks, or functions, and responsibilities of them in their everyday role. It includes to whom they report, the qualifications or skills needed by the person, and sometimes even includes a salary range. The job description of a Data Steward is not a new job description or different from their other job description. Is this confusing? We thought so.
This Real-World Data Governance webinar with Bob Seiner will focus on defining the typical responsibilities for every data steward all at once, no matter the industry, their role in the organization, or their role in the Data Governance program. Bob will focus on a list of competencies required for people to become great Data Stewards.
The session will include:
Components of a Data Steward Job Description
Seiner’s Rules for Becoming a Data Steward and How They Apply
Getting the Data Steward Involved in the Writing
Evaluating a Data Steward Based on the Job Description
Is a Job Description Even Necessary
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!
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
Navigating the Complex World of Compliance GuidelinesDATAVERSITY
Regulatory guidelines include many mandates for organizations to interpret and implement to protect their data. You know that you’re supposed to be monitoring and auditing certain data elements to demonstrate compliance, but how can you be sure you’re auditing the right things and translating the requirements correctly? IDERA’s Kim Brushaber will help to simplify and address some of the compliance concerns for complex data environments.
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
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
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
CRMCS GDPR - Why it matters and how to make it EasyPaul McQuillan
CRM has focused on User Adoption and Business Alignment, however technology is rewriting the rules.
This brings new opportunities but also new responsibilities for conduct in the Data Economy – notably the introduction of GDPR.
Paul will illustrate why the ethos behind GDPR will sit at the heart of the new relationship we will have with the customer, and how to realise the opportunity in having a customer-centric approach to our business.
Data Privacy in the DMBOK - No Need to Reinvent the WheelDATAVERSITY
World wide, Data Privacy laws are increasing. Customers are increasingly aware, and concerned, about how data is processed. The Chief Privacy Officer is (or should be) a key stakeholder for many Data Governance initiatives, and new terms like “Privacy by Design” and “Privacy Engineering” are entering our conversations with peers. Non-EU organizations selling into the EU will soon have to comply with EU Data Privacy laws. However, data professionals who take a structured, principles based approach, to building their Data Privacy capabilities stand a better chance of sustainable success than those who don’t. Rather than reinventing the wheel, organizations should look at how the DMBOK framework, in conjunction with other approaches and methods, can provide a robust platform for Data Privacy initiatives in their organizations.
Real-World Data Governance: Managing Governance Metadata for Mass ConsumptionDATAVERSITY
Metadata is a byproduct of a successful data governance program. More often than not, the success of a data governance program depends on the ability to record, validate and share metadata that is produced while implementing a data governance program. Metadata provides more than just the meaning of the data, the lineage of the data, and the rules associated with consuming the data. Governance metadata includes the people aspect of the data, who owns it (if you use that term), who stewards it, and who defines, produces and uses the data across the organization as well as other things.
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.
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
Data Governance Best Practices and Lessons LearnedDATAVERSITY
Best practices and lessons learned are powerful tools used to assess an organization’s readiness and initial activities associated with delivering a Data Governance program. There are two criteria to determine if something is best practice for your organization. And the definition of data governance best practice is best way to learn from others and begin with the end in mind.
Bob Seiner will share industry data governance best practices in this month’s installment of the RWDG webinar series. Learn how to use the best practices defined in this webinar to address opportunities to improve your organization’s data governance implementation. Attend this webinar and learn that assessing your organization may not be as difficult as you think.
During this webinar Bob will discuss:
How to define data governance best practices for your organization
Criteria used to determine if a practice is best practice
How to assess your organization against industry best practice
Assessing risks associated with best practice gaps
Addressing opportunities to improve gaps uncovered in the assessment
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
How to get started on your data governance journey and support your cyber and information security programs. Presented at the AISA Cyber Conference Canberra March 2021
Real-World Data Governance: How to Write a Data Steward Job DescriptionDATAVERSITY
A Data Steward Job Description is a list of job responsibilities that a Data Steward uses for tasks, or functions, and responsibilities of them in their everyday role. It includes to whom they report, the qualifications or skills needed by the person, and sometimes even includes a salary range. The job description of a Data Steward is not a new job description or different from their other job description. Is this confusing? We thought so.
This Real-World Data Governance webinar with Bob Seiner will focus on defining the typical responsibilities for every data steward all at once, no matter the industry, their role in the organization, or their role in the Data Governance program. Bob will focus on a list of competencies required for people to become great Data Stewards.
The session will include:
Components of a Data Steward Job Description
Seiner’s Rules for Becoming a Data Steward and How They Apply
Getting the Data Steward Involved in the Writing
Evaluating a Data Steward Based on the Job Description
Is a Job Description Even Necessary
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!
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
Navigating the Complex World of Compliance GuidelinesDATAVERSITY
Regulatory guidelines include many mandates for organizations to interpret and implement to protect their data. You know that you’re supposed to be monitoring and auditing certain data elements to demonstrate compliance, but how can you be sure you’re auditing the right things and translating the requirements correctly? IDERA’s Kim Brushaber will help to simplify and address some of the compliance concerns for complex data environments.
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
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
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
CRMCS GDPR - Why it matters and how to make it EasyPaul McQuillan
CRM has focused on User Adoption and Business Alignment, however technology is rewriting the rules.
This brings new opportunities but also new responsibilities for conduct in the Data Economy – notably the introduction of GDPR.
Paul will illustrate why the ethos behind GDPR will sit at the heart of the new relationship we will have with the customer, and how to realise the opportunity in having a customer-centric approach to our business.
Data Privacy in the DMBOK - No Need to Reinvent the WheelDATAVERSITY
World wide, Data Privacy laws are increasing. Customers are increasingly aware, and concerned, about how data is processed. The Chief Privacy Officer is (or should be) a key stakeholder for many Data Governance initiatives, and new terms like “Privacy by Design” and “Privacy Engineering” are entering our conversations with peers. Non-EU organizations selling into the EU will soon have to comply with EU Data Privacy laws. However, data professionals who take a structured, principles based approach, to building their Data Privacy capabilities stand a better chance of sustainable success than those who don’t. Rather than reinventing the wheel, organizations should look at how the DMBOK framework, in conjunction with other approaches and methods, can provide a robust platform for Data Privacy initiatives in their organizations.
Real-World Data Governance: Managing Governance Metadata for Mass ConsumptionDATAVERSITY
Metadata is a byproduct of a successful data governance program. More often than not, the success of a data governance program depends on the ability to record, validate and share metadata that is produced while implementing a data governance program. Metadata provides more than just the meaning of the data, the lineage of the data, and the rules associated with consuming the data. Governance metadata includes the people aspect of the data, who owns it (if you use that term), who stewards it, and who defines, produces and uses the data across the organization as well as other things.
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.
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.
A data monetization framework from Accenture Interactive. Three questions your company should answer to start realizing revenue opportunities from your data.
50 most valuable brands of the year 2019Pavan Kumar
A company’s dream to become valuable to its customers and to maintain their reputation in the market at the same time is a very tough feat. But some companies pulled it off, and how you ask? Here we present you the 50 valuable brands which are driven by excellent leaders and strategists, and lay out clear and compelling strategy.
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.
Data as a Service (DaaS): The What, Why, How, Who, and WhenRocketSource
Data as a Service (DaaS) is one of the most ambiguous offerings in the "as a service" family. Yet, in today's world, data and analytics are key to building a competitive advantage. We're clearing up the confusion around DaaS and helping your company understand when and how to tap into this service.
Don’t wait till your competitors have gobbled up your market share. Get started now with Data Management. Stay ahead of the competition! Try using this cheatsheet
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
Show drafts
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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.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
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
Data governance is the best practice of
identifying necessary data across an
organization, ensuring it is high and
improving its value to the business. The data
governance approach also provides the
policy to the organization of how data will be
managed and controlled.
Email us: Info@EWSolutions.Com
Call us: (630) 920-0005
3. Get a good executive sponsor
For an advantageous data governance project, a good executive
sponsor is a must. Some data experts directly quote the significance of
an executive sponsor by saying that the data governance program might
not go far if an executive sponsor is not there.
Email us: Info@EWSolutions.Com
Call us: (630) 920-0005
4. Assign a Data
Specialist and a
Data Governance
team
Email us: Info@EWSolutions.Com
Call us: (630) 920-0005
5. Build Up Your Network
Email us: Info@EWSolutions.Com
Call us: (630) 920-0005
If you do not build up secure networks from the beginning, then you
might see your authority challenged and your position questioned in
the future. So build up a secure network for your data.
6. Be always crystal clear
about your vision and
strategy
Email us: Info@EWSolutions.Com
Call us: (630) 920-0005
7. Set your right and first
priority for the data
Once you have figured out the
characteristics of your data governance
program, it's equally important to set
them in the right order.
Email us: Info@EWSolutions.Com
Call us: (630) 920-0005
8. Begin small but think big
Email us: Info@EWSolutions.Com
Call us: (630) 920-0005
The beginning scale should be small as that will
help you in understanding the business better
and get used to the process.
9. Keep a close watch
Email us: Info@EWSolutions.Com
Call us: (630) 920-0005
