Originally Published: Jan 21, 2015
The size and complexity of data make it difficult for companies to unlock the true value of their data. IBM Information Integration Governance can improve data quality, protect sensitive data, and reduce cost and risk. Free up your resources and get more out of your data.
ADV Slides: Data Curation for Artificial Intelligence StrategiesDATAVERSITY
This webinar will focus on the promise AI holds for organizations in every industry and every size, and how to overcome some of the challenge today of how to prepare for AI in the organization and how to plan AI applications.
The foundation for AI is data. You must have enough data to analyze and build models. Your data determines the depth of AI you can achieve — for example, statistical modeling, machine learning, or deep learning — and its accuracy. The increased availability of data is the single biggest contributor to the uptake in AI where it is thriving. Indeed, data’s highest use in the organization soon will be training algorithms. AI is providing a powerful foundation for impending competitive advantage and business disruption.
The Merger is Happening, Now What Do We Do?DATUM LLC
This was presented on October 24, 2018 at the ASUG EIM Conference. One of the many challenges presented by an acquisition and divestiture event is unifying disparate data and integrating systems together. If you are leading an integration, you may have more questions than answers on how to approach this event. Learn how to best leverage the momentum and budgets that accompany these activities to jump start good governance practices up front, as well as how to measure the return on investment, ensuring data and EIM professionals' ongoing success.
Designed to address more mature programs, this tutorial covers the issues and approaches to sustaining Data Governance and value creation over time, amongst a changing business and personnel environment.
Part of the reason many companies launch a Data Governance program again and again is that over time, it is challenging to maintain the enthusiasm and excitement that accompanies a newly initiated program.
Learn about:
• Typical obstacles to sustainable Data Governance
• Re-energizing your program after a key player (or two) leave and other personnel challenges
• Staying relevant to the company as the business evolves over time
• Understanding the role of metrics and why they are critical
• Leveraging Communication and Stakeholder Management practices to maintain commitment
• Embedding Data Governance into the operations of the company
Real-World Data Governance Webinar: Big Data Governance - What Is It and Why ...DATAVERSITY
Big Data is all the rage. Everybody is asking about Big Data, researching Big Data, considering Big Data, some are even doing Big Data. Certainly many people are asking questions about Big Data Governance. We have some answers for them.
This Real-World Data Governance webinar with Bob Seiner will focus on the strength of Big Data Governance as a concept and a practice and will highlight how the concepts of each, Big Data and Data Governance, both benefit and hurt each other.
This session will include:
Defining Big Data Governance
Ways to Govern Big Data
Making the Connection for IT and Business People
Determining the Vitality of Big Data Governance
Considerations for Big Data Governance
ADV Slides: Data Curation for Artificial Intelligence StrategiesDATAVERSITY
This webinar will focus on the promise AI holds for organizations in every industry and every size, and how to overcome some of the challenge today of how to prepare for AI in the organization and how to plan AI applications.
The foundation for AI is data. You must have enough data to analyze and build models. Your data determines the depth of AI you can achieve — for example, statistical modeling, machine learning, or deep learning — and its accuracy. The increased availability of data is the single biggest contributor to the uptake in AI where it is thriving. Indeed, data’s highest use in the organization soon will be training algorithms. AI is providing a powerful foundation for impending competitive advantage and business disruption.
The Merger is Happening, Now What Do We Do?DATUM LLC
This was presented on October 24, 2018 at the ASUG EIM Conference. One of the many challenges presented by an acquisition and divestiture event is unifying disparate data and integrating systems together. If you are leading an integration, you may have more questions than answers on how to approach this event. Learn how to best leverage the momentum and budgets that accompany these activities to jump start good governance practices up front, as well as how to measure the return on investment, ensuring data and EIM professionals' ongoing success.
Designed to address more mature programs, this tutorial covers the issues and approaches to sustaining Data Governance and value creation over time, amongst a changing business and personnel environment.
Part of the reason many companies launch a Data Governance program again and again is that over time, it is challenging to maintain the enthusiasm and excitement that accompanies a newly initiated program.
Learn about:
• Typical obstacles to sustainable Data Governance
• Re-energizing your program after a key player (or two) leave and other personnel challenges
• Staying relevant to the company as the business evolves over time
• Understanding the role of metrics and why they are critical
• Leveraging Communication and Stakeholder Management practices to maintain commitment
• Embedding Data Governance into the operations of the company
Real-World Data Governance Webinar: Big Data Governance - What Is It and Why ...DATAVERSITY
Big Data is all the rage. Everybody is asking about Big Data, researching Big Data, considering Big Data, some are even doing Big Data. Certainly many people are asking questions about Big Data Governance. We have some answers for them.
This Real-World Data Governance webinar with Bob Seiner will focus on the strength of Big Data Governance as a concept and a practice and will highlight how the concepts of each, Big Data and Data Governance, both benefit and hurt each other.
This session will include:
Defining Big Data Governance
Ways to Govern Big Data
Making the Connection for IT and Business People
Determining the Vitality of Big Data Governance
Considerations for Big Data Governance
It’s been almost two years since the General Data Protection Regulation shook up how organizations manage data security and privacy, ushering in a new focus on Data Governance. This complex but critical practice still has most enterprises grappling to master it for a myriad of reasons.
In this webinar, we’ll examine how Data Governance attitudes and practices continue to evolve and discuss what new research reveals as the most predominant challenges. We’ll delve into technology trends, including how adding certain capabilities will benefit your organization in terms of data asset availability, quality, and usability, including data consumer literacy and confidence.
When you attend this webinar, you will learn about:
• The requirements for a successful and sustainable Data Governance program
• Increasing confidence in data analytics for faster speed to insights
• How to automate data preparation and intelligence and where to start
How to Crunch Petabytes with Hadoop and Big Data Using InfoSphere BigInsights...DATAVERSITY
Do you wonder how to process huge amounts of data in short amount of time? If yes, this session is for you! You will learn why Apache Hadoop and Streams is the core framework that enables storing, managing and analyzing of vast amounts of data. You will learn the idea behind Hadoop's famous map-reduce algorithm and why it is at the heart of solutions that process massive amounts of data with flexible workloads and software based scaling. We explore how to go beyond Hadoop with both real-time and batch analytics, usability, and manageability. For practical examples, we will use IBM InfoSphere BigInsights and Streams, which build on top of open source tooling when going beyond basics and scaling up and out is needed.
Automated Data Governance 101 - A Guide to Proactively Addressing Your Privac...DATAVERSITY
“Data privacy,” “data security,” “data protection” –
whatever we call the way we control our data, it isn’t working. Data is as
vulnerable as ever. And this is true for both consumers hoping to keep their
data safe, and for enterprises seeking to govern their corporate and customer
data.
We’re at a crossroads: Governing data and putting data to
use are two dueling objectives, and businesses are stuck in the middle.
Can this problem be solved? In a word: yes.
The answer is through what we call automated Data Governance, which introduces speed, agility, and precision into the process of applying rules on data. Join Immuta for a webinar as we explore these Data Governance challenges and discuss how you can proactively address them with automated Data Governance.
Data Management Meets Human Management - Why Words MatterDATAVERSITY
At Fifth Third Bank, about 450 people use data every day. They all start with Alation. But this wasn't always the case. In fact, getting hundreds of folks working in sync has been a monumental task.
Just ask Greg Swygart, VP of enterprise data at Fifth Third Bank. Greg has led data consumption and interaction efforts since adopting Alation. Currently he’s scaling out data literacy for Fifth Third, replicating data capabilities to all roles across the company.
Join Greg to learn how Fifth Third Bank moved from a command-and-control governance approach to non-invasive — and reaped the benefits. Greg will be followed by Bob Seiner, creator of Non-Invasive Data Governance, who will speak to data governance’s evolution, with an eye to what’s next.
In this webinar, you'll learn:
• About Fifth Third’s transition away from command-and-control governance
• How Fifth Third leverages Alation as its data marketplace for curation & consumption
• Why words matter when driving adoption
• About the data catalog — and its role in human management
To take a “ready, aim, fire” tactic to implement Data Governance, many organizations assess themselves against industry best practices. The process is not difficult or time-consuming and can directly assure that your activities target your specific needs. Best practices are always a strong place to start.
Join Bob Seiner for this popular RWDG topic, where he will provide the information you need to set your program in the best possible direction. Bob will walk you through the steps of conducting an assessment and share with you a set of typical results from taking this action. You may be surprised at how easy it is to organize the assessment and may hear results that stimulate the actions that you need to take.
In this webinar, Bob will share:
- The value of performing a Data Governance best practice assessment
- A practical list of industry Data Governance best practices
- Criteria to determine if a practice is best practice
- Steps to follow to complete an assessment
- Typical recommendations and actions that result from an assessment
Designing a Successful Governed Citizen Data Science StrategyDATAVERSITY
To compete in today’s digital economy, enterprises require new ways to expand AI across their entire organization. Nearly all firms want to do more with data science, but they don't know where to begin or how to properly empower citizen data scientists to avoid common AI gone wrong accidents.
In this session, we will discuss how to approach your journey into citizen data science with existing analytics talent. Proven best practices and lessons learned from successful early adopters of augmented data science will be shared. We will walk through example initiative roadmaps, recommended staffing, upskilling, mentoring and ongoing governance.
Top 3 Hot Data Security And Privacy TechnologiesTyrone Systems
Organizations are transforming with Cloud Modernization, Big
Data, Customer Centricity and Data Governance. The foundation
for these initiatives is critical business data, that allows
organizations to deliver faster, more effective services and
products for their customers.
Webinar: Decoding the Mystery - How to Know if You Need a Data Catalog, a Dat...DATAVERSITY
There’s a lot of confusion out there about the differences between a data catalog, a data dictionary and a business glossary, and it's not always easy to understand who needs which and why. Join Malcolm Chisholm, Ph.D., President of Data Millennium, and Amichai Fenner, Product Lead at Octopai, as they help decode the mystery. Spoiler alert: one of these enables collaboration across BI and IT, which is it?
ADV Slides: When and How Data Lakes Fit into a Modern Data ArchitectureDATAVERSITY
Whether to take data ingestion cycles off the ETL tool and the data warehouse or to facilitate competitive Data Science and building algorithms in the organization, the data lake – a place for unmodeled and vast data – will be provisioned widely in 2020.
Though it doesn’t have to be complicated, the data lake has a few key design points that are critical, and it does need to follow some principles for success. Avoid building the data swamp, but not the data lake! The tool ecosystem is building up around the data lake and soon many will have a robust lake and data warehouse. We will discuss policy to keep them straight, send data to its best platform, and keep users’ confidence up in their data platforms.
Data lakes will be built in cloud object storage. We’ll discuss the options there as well.
Get this data point for your data lake journey.
Unlocking Greater Insights with Integrated Data Quality for CollibraPrecisely
Data is arguably your company’s greatest asset, and a thoughtful data governance strategy, along with robust tools like Collibra Data Governance Center (DGC), is essential to getting the most value from that data. However, even the best data governance programs will falter without data quality.
Data governance systems provide a framework for the policies, processes, rules, roles and responsibilities that help you manage your enterprise data. But they don’t give you insight into the characteristics and quality of that data – such as errors, outliers and issues – nor how the data changes over time.
During this webinar, we discuss how seamlessly integrating Trillium DQ with Collibra DGC creates a complete data governance solution that delivers rapid insights into the health of your data, ensuring trust and compliance with organizational policies and plans. We demonstrate how data is automatically exchanged between the tools so users can:
• Quickly establish the rules needed to support policies
• Evaluate their data against those rules on an ongoing basis
• Identify problems or improvements with their data quality to take action
Slides: Accelerate and Assure the Adoption of Cloud Data Platforms Using Inte...DATAVERSITY
Greater agility, scalability, and lower total cost of ownership made the decision to move key elements of your organization’s data capability to the cloud easy. The real challenge is migrating data from your legacy systems to your new cloud platform so you can unleash its potential and value while minimizing the migration risks.
Combining erwin‘s data modeling, governance, and intelligence solutions with Snowflake’s modern cloud data platform, organizations can realize a scalable, governed, and transparent enterprise data capability.
In this session, we’ll show you how enterprise stakeholders with different skills and needs can work together to accelerate and assure the success of cloud migration projects of any size. You’ll learn how to:
• Reduce costs and mitigate risks when migrating legacy applications to Snowflake with erwin’s model-driven schema design and transformation capabilities
• Increase the precision, speed, and agility of Snowflake deployments with erwin data automation
• Assure transparency, compliance, and governance for Snowflake data and processes
• Increase the efficiency and accuracy of analytics and other data usage on the Snowflake Cloud Platform
RWDG Slides: Using Tools to Advance Your Data Governance ProgramDATAVERSITY
Data Governance tools can be used to advance your Data Governance program … or they can become the reason why Data Governance fails to meet people’s expectations. Tools can be developed internally or acquired from reliable vendors to attempt to address your organization’s needs. Sometimes the best environment is made up of a hybrid of tools developed internally and tools acquired.
Join Bob Seiner for this month’s RWDG webinar where he will share tools that you can build yourself and talk about how the tools can be used to determine requirements to acquire outside tools. Tools developed internally at little or no cost have helped to solve many Data Governance problems. Several of these problems and their solutions will be described in detail during this webinar.
In this webinar, Bob will discuss:
• Several easy-to-build Data Governance tools
• Customizing these tools to address specific issues
• How internally developed tools can lead to tool acquisition
• Knowing when it is time to acquire tools
• Integrating DIY tools with acquired tools
It’s been almost two years since the General Data Protection Regulation shook up how organizations manage data security and privacy, ushering in a new focus on Data Governance. This complex but critical practice still has most enterprises grappling to master it for a myriad of reasons.
In this webinar, we’ll examine how Data Governance attitudes and practices continue to evolve and discuss what new research reveals as the most predominant challenges. We’ll delve into technology trends, including how adding certain capabilities will benefit your organization in terms of data asset availability, quality, and usability, including data consumer literacy and confidence.
When you attend this webinar, you will learn about:
• The requirements for a successful and sustainable Data Governance program
• Increasing confidence in data analytics for faster speed to insights
• How to automate data preparation and intelligence and where to start
How to Crunch Petabytes with Hadoop and Big Data Using InfoSphere BigInsights...DATAVERSITY
Do you wonder how to process huge amounts of data in short amount of time? If yes, this session is for you! You will learn why Apache Hadoop and Streams is the core framework that enables storing, managing and analyzing of vast amounts of data. You will learn the idea behind Hadoop's famous map-reduce algorithm and why it is at the heart of solutions that process massive amounts of data with flexible workloads and software based scaling. We explore how to go beyond Hadoop with both real-time and batch analytics, usability, and manageability. For practical examples, we will use IBM InfoSphere BigInsights and Streams, which build on top of open source tooling when going beyond basics and scaling up and out is needed.
Automated Data Governance 101 - A Guide to Proactively Addressing Your Privac...DATAVERSITY
“Data privacy,” “data security,” “data protection” –
whatever we call the way we control our data, it isn’t working. Data is as
vulnerable as ever. And this is true for both consumers hoping to keep their
data safe, and for enterprises seeking to govern their corporate and customer
data.
We’re at a crossroads: Governing data and putting data to
use are two dueling objectives, and businesses are stuck in the middle.
Can this problem be solved? In a word: yes.
The answer is through what we call automated Data Governance, which introduces speed, agility, and precision into the process of applying rules on data. Join Immuta for a webinar as we explore these Data Governance challenges and discuss how you can proactively address them with automated Data Governance.
Data Management Meets Human Management - Why Words MatterDATAVERSITY
At Fifth Third Bank, about 450 people use data every day. They all start with Alation. But this wasn't always the case. In fact, getting hundreds of folks working in sync has been a monumental task.
Just ask Greg Swygart, VP of enterprise data at Fifth Third Bank. Greg has led data consumption and interaction efforts since adopting Alation. Currently he’s scaling out data literacy for Fifth Third, replicating data capabilities to all roles across the company.
Join Greg to learn how Fifth Third Bank moved from a command-and-control governance approach to non-invasive — and reaped the benefits. Greg will be followed by Bob Seiner, creator of Non-Invasive Data Governance, who will speak to data governance’s evolution, with an eye to what’s next.
In this webinar, you'll learn:
• About Fifth Third’s transition away from command-and-control governance
• How Fifth Third leverages Alation as its data marketplace for curation & consumption
• Why words matter when driving adoption
• About the data catalog — and its role in human management
To take a “ready, aim, fire” tactic to implement Data Governance, many organizations assess themselves against industry best practices. The process is not difficult or time-consuming and can directly assure that your activities target your specific needs. Best practices are always a strong place to start.
Join Bob Seiner for this popular RWDG topic, where he will provide the information you need to set your program in the best possible direction. Bob will walk you through the steps of conducting an assessment and share with you a set of typical results from taking this action. You may be surprised at how easy it is to organize the assessment and may hear results that stimulate the actions that you need to take.
In this webinar, Bob will share:
- The value of performing a Data Governance best practice assessment
- A practical list of industry Data Governance best practices
- Criteria to determine if a practice is best practice
- Steps to follow to complete an assessment
- Typical recommendations and actions that result from an assessment
Designing a Successful Governed Citizen Data Science StrategyDATAVERSITY
To compete in today’s digital economy, enterprises require new ways to expand AI across their entire organization. Nearly all firms want to do more with data science, but they don't know where to begin or how to properly empower citizen data scientists to avoid common AI gone wrong accidents.
In this session, we will discuss how to approach your journey into citizen data science with existing analytics talent. Proven best practices and lessons learned from successful early adopters of augmented data science will be shared. We will walk through example initiative roadmaps, recommended staffing, upskilling, mentoring and ongoing governance.
Top 3 Hot Data Security And Privacy TechnologiesTyrone Systems
Organizations are transforming with Cloud Modernization, Big
Data, Customer Centricity and Data Governance. The foundation
for these initiatives is critical business data, that allows
organizations to deliver faster, more effective services and
products for their customers.
Webinar: Decoding the Mystery - How to Know if You Need a Data Catalog, a Dat...DATAVERSITY
There’s a lot of confusion out there about the differences between a data catalog, a data dictionary and a business glossary, and it's not always easy to understand who needs which and why. Join Malcolm Chisholm, Ph.D., President of Data Millennium, and Amichai Fenner, Product Lead at Octopai, as they help decode the mystery. Spoiler alert: one of these enables collaboration across BI and IT, which is it?
ADV Slides: When and How Data Lakes Fit into a Modern Data ArchitectureDATAVERSITY
Whether to take data ingestion cycles off the ETL tool and the data warehouse or to facilitate competitive Data Science and building algorithms in the organization, the data lake – a place for unmodeled and vast data – will be provisioned widely in 2020.
Though it doesn’t have to be complicated, the data lake has a few key design points that are critical, and it does need to follow some principles for success. Avoid building the data swamp, but not the data lake! The tool ecosystem is building up around the data lake and soon many will have a robust lake and data warehouse. We will discuss policy to keep them straight, send data to its best platform, and keep users’ confidence up in their data platforms.
Data lakes will be built in cloud object storage. We’ll discuss the options there as well.
Get this data point for your data lake journey.
Unlocking Greater Insights with Integrated Data Quality for CollibraPrecisely
Data is arguably your company’s greatest asset, and a thoughtful data governance strategy, along with robust tools like Collibra Data Governance Center (DGC), is essential to getting the most value from that data. However, even the best data governance programs will falter without data quality.
Data governance systems provide a framework for the policies, processes, rules, roles and responsibilities that help you manage your enterprise data. But they don’t give you insight into the characteristics and quality of that data – such as errors, outliers and issues – nor how the data changes over time.
During this webinar, we discuss how seamlessly integrating Trillium DQ with Collibra DGC creates a complete data governance solution that delivers rapid insights into the health of your data, ensuring trust and compliance with organizational policies and plans. We demonstrate how data is automatically exchanged between the tools so users can:
• Quickly establish the rules needed to support policies
• Evaluate their data against those rules on an ongoing basis
• Identify problems or improvements with their data quality to take action
Slides: Accelerate and Assure the Adoption of Cloud Data Platforms Using Inte...DATAVERSITY
Greater agility, scalability, and lower total cost of ownership made the decision to move key elements of your organization’s data capability to the cloud easy. The real challenge is migrating data from your legacy systems to your new cloud platform so you can unleash its potential and value while minimizing the migration risks.
Combining erwin‘s data modeling, governance, and intelligence solutions with Snowflake’s modern cloud data platform, organizations can realize a scalable, governed, and transparent enterprise data capability.
In this session, we’ll show you how enterprise stakeholders with different skills and needs can work together to accelerate and assure the success of cloud migration projects of any size. You’ll learn how to:
• Reduce costs and mitigate risks when migrating legacy applications to Snowflake with erwin’s model-driven schema design and transformation capabilities
• Increase the precision, speed, and agility of Snowflake deployments with erwin data automation
• Assure transparency, compliance, and governance for Snowflake data and processes
• Increase the efficiency and accuracy of analytics and other data usage on the Snowflake Cloud Platform
RWDG Slides: Using Tools to Advance Your Data Governance ProgramDATAVERSITY
Data Governance tools can be used to advance your Data Governance program … or they can become the reason why Data Governance fails to meet people’s expectations. Tools can be developed internally or acquired from reliable vendors to attempt to address your organization’s needs. Sometimes the best environment is made up of a hybrid of tools developed internally and tools acquired.
Join Bob Seiner for this month’s RWDG webinar where he will share tools that you can build yourself and talk about how the tools can be used to determine requirements to acquire outside tools. Tools developed internally at little or no cost have helped to solve many Data Governance problems. Several of these problems and their solutions will be described in detail during this webinar.
In this webinar, Bob will discuss:
• Several easy-to-build Data Governance tools
• Customizing these tools to address specific issues
• How internally developed tools can lead to tool acquisition
• Knowing when it is time to acquire tools
• Integrating DIY tools with acquired tools
This presentation reports on data governance best practices. Based on a definition of fundamental terms and the business rationale for data governance, a set of case studies from leading companies is presented. The content of this presentation is a result of the Competence Center Corporate Data Quality (CC CDQ) at the University of St. Gallen, Switzerland.
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!
Enabling Data as a Service with the JBoss Enterprise Data Services Platformprajods
This presentation was given at JUDCon 2013, Jan 17,18 at Bangalore. Presented by Prajod Vettiyattil and Gnanaguru Sattanathan. The presentation deals with the Why, What and How of Data Services and Data Services Platforms. It also explains the features of the JBoss Enterprise Data Services Platform.
The need for Data Services is explained with 3 Business use cases:
1. Post purchase customer experience improvement for an Auto manufacturer
2. Enterprise Data Access Layer
3. Data Services for Regulatory Reporting requirements like Dodd Frank
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)
This slideshow presents
* Why it is critical to properly structure and organize data integration processes
* How to automate deployments
* The importance of production monitoring
To view the entire webinar with the demonstration, click on : http://nxy.in/srqft
If you wish to see other webinars, click on: http://nxy.in/hkidj
For Live Webinars, click here: http://nxy.in/pjeph
Start today on a relevant and incremental MDM journey.
A turnkey MDM solution allows you to collaborate on, maintain and provision accurate and reliable data across the enterprise; however, extended implementation times can delay time to value. Many successful MDM projects start small and grow over time. Open source provides a vehicle to start your MDM journey and deliver value - today.
This slideshow will show you:
* How an integrated solution for data integration, data quality and master data management can speed up and simplify implementation
* Why an active data model allows you to quickly reflect unique data requirements
* The importance of a dynamic MDM interface that enables immediate collaboration and stewardship
To view the entire webinar with the demonstration, click on : http://nxy.in/bhl3z
If you wish to see other webinars, click on: http://nxy.in/hkidj
For Live Webinars, click here: http://nxy.in/pjeph
Real-World DG Webinar: A Data Governance Framework for Success DATAVERSITY
A Data Governance Framework must include best practices, a practical set of roles & responsibilities for Data Governance built specifically for your organization, a plan for communicating with the entire organization and an action plan for applying governance in effective and measurable ways.
Join Bob Seiner for this Real-World Data Governance webinar as he discusses how to stay practical and work within the culture of your organization to develop and deliver a Data Governance Framework to meet your specifications and the business’ expectations.
This session will focus on:
Defining a Non-Invasive Operating Model of Roles & Responsibilities
Clearly Stating the Difference between Executive, Strategic, Tactical, Operational & Supporting Roles
Defining Data Stewards, Data Stewardship and How to Steward the Data
Recognizing & Identifying People into Roles Rather than Handing them to People as New Responsibilities
Leveraging the Framework to Implement a Successful Data Governance Program
RWDG Webinar: Achieving Data Quality Through Data GovernanceDATAVERSITY
Data quality requires sustained discipline around the management of data definition and production. Data Governance is a large part of that discipline. The relationship between how well data is governed and the quality of the data is obvious. You cannot have high quality data without active Data Governance.
This month’s Real-World Data Governance webinar with Bob Seiner addresses how to improve data quality through the application of Data Governance practices. Quality starts with a plan and requires formal execution and enforcement of authority over the data. Attend this webinar and take away a plan to achieve data quality through Data Governance.
In this webinar, Bob will discuss:
• How Data Governance leads to data quality
• Core principles of Data Governance and data quality success
• Quality metrics based on governance practices
• Relationship between quality and governance roles
• Steps to achieve quality through governance
Smart Data Slides: Leverage the IOT to Build a Smart Data EcosystemDATAVERSITY
No (successful) business is an island. For decades, business schools have taught strategies for improving competitiveness by evaluating strengths, weaknesses, opportunities and threats (SWOT), and considering market forces represented by competitors, consumers, and suppliers. Today, enterprises of all sizes are expected to manage their transactions and customer engagement “touch points” using applications that capture and measure everything from materials to customer satisfaction. As we automate and monitor every aspect of manufacturing and distribution (including the production and delivery of intellectual property for service-oriented businesses) there is a significant and growing role for smart data and sensor/IOT data.
Participants in this webinar will learn to define, capture, and analyze new IOT-based data to improve supply-chain performance.
RWDG Slides: Corporate Data Governance - The CDO is the Data Governance ChiefDATAVERSITY
The CDO is a relatively new and evolving role. Many CDO job descriptions detail specific Data Governance responsibilities. Some CDO job descriptions read all-data-governance and all-the-time. It has become obvious. The CDO is the new chief of Data Governance.
In this Real-World Data Governance webinar, Bob Seiner and special guest Anthony Algmin will focus on the evolution of the Chief Data Officer role and associated responsibilities. Someone must lead Data Governance and the CDO is the obvious choice. Attend this webinar to learn why.
In this webinar, Bob will present:
• A Detailed CDO Job Description
• Why the CDO is the Data Governance Chief
• The Makeup of the Chief’s Tribe
• Lessons Learned from the CDO’s Office
• Suggestions for new and existing CDOs
Presentation of use cases of Master Data Management for product Data. It presents the five facets of MDM for product Data (MDM for Material, MDM for Lean Managed Services, MDM for Regulated Products, Product Information Management, MDM for “Anything”) and how Talend platform for MDM can adress them
IBM's big data seminar programme -moving beyond Hadoop - Ian Radmore, IBMInternet World
Big Data Meets Big Analytics Theatre - June 18th, 15:00-15:30
Eighty percent of the world's data is unstructured, and most businesses don't even attempt to use this data to their advantage. Imagine if you could afford to keep and analyse all the data generated by your business. Imagine that you had a way to analyse and exploit that data as it is created! Whether you're a telecoms provider trying to minimise customer churn, a utility company looking to exploit the potential of smart-metering or a surveillance company ensuring the security of clients' premises, there are genuine business opportunities from deploying big data analytics in real-time. Using live client examples, Ian will show how real-time analytics provide a powerful extension to any big data platform and is applicable across many types of information and real-world problems to deliver tangible business value.
Ian Radmore, an IBM Big Data Specialist spoke about the velocity aspect of the 4Vs associated with Big Data at the recent Internet World conference, this is the supporting presentation.
This presentation from IBM's Business Continuity and Resiliency Services examines the trends and challenges that support cloud-based resiliency, and how IBM's Cloud Resilience portfolio can help.
Empowering you with Democratized Data Access, Data Science and Machine LearningDataWorks Summit
Data science with its specialized tools and knowledge has been a forte of data scientists. However, it is not easy even for data scientists to get access to data that could be in different data stores in the organization. To unleash the power of data and gain valuable insights, machine learning needs to be made easily consumable by various stake holders and access to data made simpler. As an organization's data volumes continue to grow, delivering these insights real time is a complex challenge to solve.
This session will provide on overview of an approach to building a scalable solution where machine and deep learning and access to data is made much more consumable and simpler by the fastest SQL on Hadoop engine on the planet, a rich data scientist toolset and an infrastructure that can deliver the responsiveness needed for production environments.
Speakers:
Pandit Prasad, Program Director, IBM
Ashutosh Mate, Global Senior Solutions Architect, IBM
Dallas Digital Summit: 6 Steps to Big Data SuccessSameer Khan
The Big Data phenomenon was all about the collection of masses and masses of data: it was a technology challenge. But for most of us, this is no longer a problem – we know how to collect the data – the challenge now is one of processing the data, to make smart data work for us. Econsultancy, reports only 25% of the organizations are able to make proactive use of digital data to drive business outcomes. In this session, IBM’s Sameer Khan will outline a 6 step action plan to manage your data and derive relevant insights from it.
90 % av alla dataintrång fokuserar på data i databaser. Det är där ditt företags känsliga och åtråvärda information finns. I 38 % av dessa intrång tar det minuter att få ut känsligt data, samtidigt som det för hälften av intrången tar månader eller mer innan de upptäcks. Dave Valovcin, från IBM WW Guardium Sales, berättar om hur du kan skydda din känsliga data.
Application Consolidation and RetirementIBM Analytics
Originally Published: Feb 04, 2015
Multiple, disconnected systems or an outdated application infrastructure can negatively impact your business and increase your costs. Consolidating applications, retiring outdated databases and modernizing systems can streamline your infrastructure and free resources to focus on important new projects.
An introduction to IBM Data Lake by Mandy Chessell CBE FREng CEng FBCS, Distinguished Engineer & Master Inventor.
Learn more about IBM Data Lake: https://ibm.biz/Bdswi9
10 WealthTech podcasts every wealth advisor should listen toIBM Analytics
Listen to this “Finance in Focus” podcast series to hear a cast of interesting experts discuss how the wealth management industry is adapting to new and emerging technologies that include robo-advisors, blockchain, analytics, and cognitive. Over the course of 10 episodes, hosts Rob Stanich and Alex Baghdjian are joined by wealth management experts to discuss behavior financing, DOL fiduciary rule, social media marketing, account aggregation, millennials, surveillance, and regulations.
Advantages of an integrated governance, risk and compliance environmentIBM Analytics
Risk management is increasingly becoming a strategic, executive-sponsored solution that many organizations view as providing a competitive advantage. When companies have an aggregated view of all the different kinds of risk and compliance data, they can start to generate insights about how to run the business better. In this presentation, learn why and how to empower business leaders to make more risk-aware decisions with visibility across controls and associated issues and actions throughout the organization.
The banking industry will benefit from adopting the latest technology advancements that include artificial intelligence and cognitive computing. These technologies provide the opportunity to mine the massive amounts of transactional data that banks have collected over the past decades to better serve their customers, automate time-consuming mundane tasks and to integrate the act of banking into the lives of consumers.
Learn how: http://ibm.co/bankinganalytics
Sales performance management and C-level goalsIBM Analytics
Before diving into planning for sales compensation, get a fix on the company’s business goals and strategy. See why having a framework in place is critical when designing a sales strategy and compensation program.
Learn more: http://www.ibm.com/analytics/us/en/business/sales-performance-management/
The science of client insight: Increase revenue through improved engagementIBM Analytics
As they compete in the modern business environment, companies are increasingly looking to sophisticated analytics and cognitive capabilities to help them gain a deep understanding of what matters to their clients. By knowing their customers well, organizations can provide targeted, personalized service that adds value and heightens customer loyalty. When they do, they can avoid churn while generating additional revenue models by creating meaningful cross-selling opportunities in a customer-centric world. Explore this ebook to discover a wide array of uses for client insights in banking and wealth management.
Expert opinion on managing data breachesIBM Analytics
For the first time, cybersecurity strategy is an integral part of the platforms for the US presidential candidates. Today, data breaches and cyber attacks are no longer just one offs but seemingly happen daily and impact both the private sector and government. What are we doing to minimize these data breaches and counter cyber attacks? What’s the role of government in fighting cyber crime? Where does the public sector fit in the cyber-crime puzzle? Cybersecurity experts Dan Lohrmann, Scott Schober, Shahid Shah, Eric Vanderburg and Morgan Wright address these questions.
Top industry use cases for streaming analyticsIBM Analytics
Organizations need to get high value from streaming data to gain new clients and capitalize on market opportunities. Discover how IBM Streams is best suited for use cases that has the need for high speed and low latency.
The key to the cognitive business is putting data to work. What is needed is a platform, an ecosystem, and a method.
Learn more about http://ibm.co/dataworks
IBM CDO Fall Summit 2016 Keynote: Driving innovation in the cognitive eraIBM Analytics
What does it take to drive Innovation in the Cognitive Era? Bob Picciano, Senior Vice President IBM Analytics and Inderpal Bhandari, Global Chief Data Officer, IBM gave this presentation to the CDOs and data professionals in attendance at the IBM Chief Data Officer Strategy Summit in Fall of 2016.
Learn more about the role of CDO: http://ibm.co/2cXasXy
4 common headaches with sales compensation managementIBM Analytics
Gain insights and solutions to four highly common headaches that companies face in their sales performance management processes. Learn more: http://ibm.com/spm
IBM Virtual Finance Forum 2016: Top 10 reasons to attendIBM Analytics
Explore the top 10 reasons to attend IBM's Virtual Finance Forum 2016 for insights and best practices on performance management in the cognitive era. Attend your choice of three broadcasts of IBM's Virtual Finance Forum 2016: http://bit.ly/oct5am, http://bit.ly/Oct512Noon or http://bit.ly/oct5eve.
In the domain of data science, solving problems and answering questions through data analysis is standard practice. Data scientists experiment continuously by constructing models to predict outcomes or discover underlying patterns, with the goal of gaining new insights. Organizations can then use these insights to strengthen customer relationships, improve service delivery and drive new opportunities. To help guide the processes and activities within a given domain, data scientists and engineers need a foundational methodology that provides a framework for how to proceed with whichever methods or tools they will use to obtain answers and deliver results. In this presentation, we will share data science tips for data engineers.
Join the Data Science Experience: http://ibm.co/data-science
How secure is your enterprise from threats? IBM Analytics
Modern enterprises are vulnerable to a wide range of threats that can put customers, employees and even the organization’s brand at serious risk. Staying ahead of diverse threats as they evolve requires not only continuous monitoring and analysis of disparate data sets but also the fusing of the resulting insights into a single intelligence picture. This allows organizations to gain a comprehensive understanding of the diverse threats and vulnerabilities that can put the entire enterprise at risk.
Noting that defense and national security agencies have employed this ongoing analysis and fusion approach for years, commercial organizations and civilian government agencies have begun adopting similar processes when setting up security operations centers and fusion centers. Whether you have a fusion center or are simply seeking to understand and mitigate your threats, IBM i2 Enterprise Insight Analysis can help you develop a comprehensive approach to enterprise intelligence with which you can neutralize the threats that menace your enterprise.
Collaboration is crucial to today’s workforce. Whether you are in a traditional office setting, work from home or travel extensively, there are tools needed to achieve successful content collaboration.
Whether your mission is to improve external collaboration, increase scalability or focus on security and compliance, find out how content collaboration with Box can improve your ROI.
To find out more on how to improve your content journey, visit IBM ECM and Box: http://ibm.co/ibm-box-partnership
The digital transformation of the French OpenIBM Analytics
For decades, IBM and the Fédération Francaise de Tennis have been tennis partners, using real-time analytics as their winning serve to create a cross-platform fan experience. Learn about IBM’s game-changing site redesign for The French Open and platform innovations to enhance the tournament experience for both attendees and virtual fans.
Bridging to a hybrid cloud data services architectureIBM Analytics
Enterprises are increasingly evolving their data infrastructures into entire cloud-facing environments. Interfacing private and public cloud data assets is a hallmark of initiatives such as logical data warehouses, data lakes and online transactional data hubs. These projects may involve deploying two or more of the following cloud-based data platforms into a hybrid architecture: Apache Hadoop, data warehouses, graph databases, NoSQL databases, multiworkload SQL databases, open source databases, data refineries and predictive analytics.
Data application developers, data scientists and analytics professionals are driving their organizations’ efforts to bridge their data to the cloud. Several questions are of keen interest to those who are driving an organization’s evolution of its data and analytics initiatives into more holistic cloud-facing environments:
• What is a hybrid cloud data services architecture?
• What are the chief applications and benefits of a hybrid cloud data services architecture?
• What are the best practices for bridging a logical data warehouse to the cloud?
• What are the best practices for bridging advanced analytics and data lakes to the cloud?
• What are the best practices for bridging an enterprise database hub to the cloud?
• What are the first steps to take for bridging private data assets to the cloud?
• How can you measure ROI from bridging private data to public cloud data services?
• Which case studies illustrate the value of bridging private data to the cloud?
Sign up now for a free 3-month trial of IBM Analytics for Apache Spark and IBM Cloudant, IBM dashDB or IBM DB2 on Cloud.
http://ibm.co/ibm-cloudant-trial
http://ibm.co/ibm-dashdb-trial
http://ibm.co/ibm-db2-trial
http://ibm.co/ibm-spark-trial
What does data tell you about the customer journey?IBM Analytics
In this omnichannel world, consumers leave clues about their purchasing decisions at every touch point. What data analytics can you leverage to optimize your marketing message and merchandising? Well, it turns out, a lot.
What CEOs want from CDOs and how to deliver on itIBM Analytics
Cortnie Abercrombie, Emerging Roles Leader, IBM gave this presentation on what Chief Executive Officers want from Chief Data Officers and how to deliver on it at CDOvision 2016.
Learn more about the various roles of CDOs: http://ibm.co/cdolookbook
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
Reporting to Tracking Authorities:
We immediately notify all relevant centralized exchanges (CEX), decentralized exchanges (DEX), and wallet providers about the stolen cryptocurrency. This ensures that the stolen assets are flagged as scam transactions, making it impossible for the thief to use them.
Assistance with Filing Police Reports:
We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
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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.
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).
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
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