Slide deck from a webinar presented by Earley Information Science on "MDM - The Key to Successful Customer Experience Management." Featured speaker is EIS Director of Delivery Services, Tim Barnes.
Webinar produced jointly by Earley Information Science and Riversand on how "Product Information is Key to Winning the Customer Experience Race." Featured speakers are Jeannine Bartlett, Chief Digital Strategist with EIS, and Cody Bateman, Client Relations Executive with Riversand.
360 metadata - crucial for digital marketing - framework for youHeimo Hänninen
Digital Marketing requires high quality metadata about: your consumers, your products, product data and marketing content, your partners, your sales activities and pricing, to mention a few. Linked Open Data (LOD) and semantic technologies are robust, yet flexible way of merging and managing metadata for marketing from different sources. With LOD you can also realize Enterprise Linked Data in wider scope.
Linking Data Governance to Business GoalsPrecisely
The importance of data to businesses has increased exponentially over recent years as companies seek benefits such as gains in efficiency, the ability to respond to growing privacy regulations scale quickly and increased and increase customer loyalty.
Despite being a vital part of any Data Transformation, Data Governance has sometimes been misrepresented as a restrictive and controlling process leaving governance leaders having to continually make the case for business buy-in.
In this on-demand webinar we will explore the concept of business-first Data Governance, an approach that promotes adoption by the organisation, lays the foundation for data integrity and consistently delivers business value in the long term.
Top 7 Capabilities for Next-Gen Master Data ManagementDATAVERSITY
This session will discuss how the master data management platforms are evolving to meet needs of digital economy. A modern master data management platform incorporates graph technology, infuses insights from the data using advanced analytics and ML, and offer big data scale performance in the cloud. Join this webinar to learn about these and other critical capabilities that power connected customer experience, compliance, and business alignment.
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.
Master Data Management - Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) can provide significant value to the organization in creating consistent key data assets such as Customer, Product, Supplier, Patient, and the list goes on. But getting MDM “right” requires a strategic mix of Data Architecture, business process, and Data Governance. Join this webinar to learn how to find the “sweet spot” between technology, design, process, and people for your MDM initiative.
Webinar produced jointly by Earley Information Science and Riversand on how "Product Information is Key to Winning the Customer Experience Race." Featured speakers are Jeannine Bartlett, Chief Digital Strategist with EIS, and Cody Bateman, Client Relations Executive with Riversand.
360 metadata - crucial for digital marketing - framework for youHeimo Hänninen
Digital Marketing requires high quality metadata about: your consumers, your products, product data and marketing content, your partners, your sales activities and pricing, to mention a few. Linked Open Data (LOD) and semantic technologies are robust, yet flexible way of merging and managing metadata for marketing from different sources. With LOD you can also realize Enterprise Linked Data in wider scope.
Linking Data Governance to Business GoalsPrecisely
The importance of data to businesses has increased exponentially over recent years as companies seek benefits such as gains in efficiency, the ability to respond to growing privacy regulations scale quickly and increased and increase customer loyalty.
Despite being a vital part of any Data Transformation, Data Governance has sometimes been misrepresented as a restrictive and controlling process leaving governance leaders having to continually make the case for business buy-in.
In this on-demand webinar we will explore the concept of business-first Data Governance, an approach that promotes adoption by the organisation, lays the foundation for data integrity and consistently delivers business value in the long term.
Top 7 Capabilities for Next-Gen Master Data ManagementDATAVERSITY
This session will discuss how the master data management platforms are evolving to meet needs of digital economy. A modern master data management platform incorporates graph technology, infuses insights from the data using advanced analytics and ML, and offer big data scale performance in the cloud. Join this webinar to learn about these and other critical capabilities that power connected customer experience, compliance, and business alignment.
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.
Master Data Management - Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) can provide significant value to the organization in creating consistent key data assets such as Customer, Product, Supplier, Patient, and the list goes on. But getting MDM “right” requires a strategic mix of Data Architecture, business process, and Data Governance. Join this webinar to learn how to find the “sweet spot” between technology, design, process, and people for your MDM initiative.
DAS Slides: Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key inter-relationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how Data Architecture is a key component of an overall enterprise architecture for enhanced business value and success.
Master Data Management's Place in the Data Governance Landscape CCG
For many organizations, Master Data Management is a necessity to ensure consistency and accuracy of essential business entities. It further plays alongside data architecture, metadata management, data quality, security & privacy, and program management in the Data Governance ecosystem.
Join CCG's data governance subject matter experts as they overview the fundamentals of Master Data Management at our Atlanta-based Data Analytics Meetup. This event will discuss how to enable components of data governance within your organization and review how to best leverage Microsoft's SQL Server Master Data Services.
DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...DATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task. The opportunity in getting it right can be significant, however, as data drives many of the key initiatives in today’s marketplace: digital transformation, marketing, customer centricity, and more. This webinar will help de-mystify Data Strategy and Data Architecture and will provide concrete, practical ways to get started.
Align Business Data & Analytics for Digital TransformationPerficient, Inc.
Your success in the digital world relies primarily on how well you manage and analyze the data coming from disparate internal systems and external channels. You need to understand how to innovate and leverage digital data to drive sales and productivity.
Existing principles driving traditional data architecture are inadequate to support the volume, variety, and velocity of this new data ecosystem. In these scenarios, information governance (master data management, metadata, data quality and data governance) becomes highly critical in terms of providing the context for operational, competitive and advanced analytics.
Companies require a data architecture and strategy that can support efficient digital transformation by unlocking the value in all data sources to provide mission-critical insights and informed decision-making.
Our experts covered:
-Five information management pillars necessary for digital transformation
-Stages of digital information maturity, reflecting the typical path of an organization implementing this new data ecosystem
-Issues, challenges, and approaches to governing this new architecture
How to Create and Manage a Successful Analytics OrganizationDATAVERSITY
For the last few years, analytics, data science and data management have achieved tremendous exposure on all the media channels. Big Data has become a major topic of discussion, catalyzing attention among the C-Level executives and driving investments and projects inside the enterprise. However, it is really interesting that just a selected group of business has created successful data teams and has mastered the skills to manage it. What we have seen is that most companies still do not know how to create, implement and manage a data and analytics organization. Above all, if data has become an strategic asset and is being considered the new oil for the 21st century economy, what your strategy to handle it ? This webinar will help to bring some concepts and ideas to enlighten your path to create and manage an analytics organization, providing some real life examples on companies which did it.
Bridging the Data Divide: Driving Data and Analytics Projects Forward with Tr...Precisely
There’s no debate that data is the most valuable strategic asset available to your business today. According to ‘Voice of the Enterprise: Data Management and Analytics 2020’ by 451 Research, 63% of enterprises use data to drive nearly all or most of their strategic decisions.
Join Amy O’Connor, Precisely Chief Data and Information Officer, and Paige Bartley, 451 Research Senior Research Analyst for Data, AI, and Analytics as Paige shares the latest research on data and analytics drawn from surveys of business and technology decision-makers and chats with Amy about her experience implementing Precisely products to ensure data integrity and fuel the company’s data-driven business model.
View this on-demand webinar to hear Amy and Paige share their perspectives on key points from the research, including how:
• Only 25% of respondents rate more than 80% of their recent data and analytics initiatives as successful
• 78% of those most successful with data and analytics initiatives are using or considering using technologies to accelerate the analysis of distributed data
• 24% of respondents are investing in programs that increase trust in data by improving accuracy, quality, lineage and/or governance to improve their data culture
Be Digital or Die - Predictive Analytics for Digital TransformationFintricity
A look at leveraging big data and predictive analytics for digital transformation. This deck was presented at the Predictive Analytics & Innovation Summit in London. 10th May 2016, by Alpesh Doshi, Founder of Fintricity.
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
RWDG Slides: Governing Your Data Catalog, Business Glossary, and Data DictionaryDATAVERSITY
Data catalogs, business glossaries, and data dictionaries house the metadata that builds organizational confidence in your data. First and foremost, the people in your organization need to be engaged in leveraging the tools, understanding the data that is available and who is responsible for the data, and knowing how to get their hands on the data they need to perform their job function. This metadata will not govern itself.
Join Bob Seiner for the April RWDG webinar, where he will discuss how to govern the metadata in a data catalog, business glossary, and data dictionary. People must have confidence in the metadata associated with the data that you need them to trust. Therefore, the metadata in your data catalog, business glossary, and data dictionary must be governed. Learn how to govern that metadata in this webinar.
Bob will discuss the following subjects in this webinar:
• Successful Data Governance relies on value from very important tools
• What it means to govern your data catalog, business glossary, and data dictionary
• Why governing the metadata in these tools is so important
• The roles necessary to govern these tools
• Value expected from governing the catalog, glossary, and dictionary
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
Models & Tags: Building User-Focused Content Models That Actually WorkSeth Maislin
Reliable, user-focused domain and content models are foundational in all information processes, from findability to reuse to security. In this session you'll learn why models are so important, and a repeatable process for creating and using them effectively. Written by Seth Maislin, Principal Consultant of Taxonomy at Earley & Associates. www.earley.com
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.
Conference Chairman Keynote & Welcome
Capitalizing on MDM in Times of Crisis
Aaron Zornes, Founder & Chief Research Officer, The MDM Institute
--------------------------------------------------------------------------------
MDM is particularly important in today’s increasingly complex and harsh global business landscape – in part due to increasingly demanding suppliers, trading partners, customers … as well as financial challenges and government regulations. Despite the current economic crisis, analyst firms have declared MDM to be “recession proof” as businesses strive to dramatically reduce costs, meet compliance reporting mandates, deliver increased sales and marketing effectiveness, and provide superior service to customers and suppliers. MDM and its variants – customer data integration (CDI), product information management (PIM), and data governance – all significantly contribute to these tactical business priorities.
Research analysts at the MDM Institute annually produce a set of twelve milestones for their MDM Road Map to help Global 5000 enterprises focus efforts for their own large-scale, mission-critical MDM projects. This keynote will focus on this set of strategic planning assumptions and present an enlightening view of the key trends and issues facing IT organizations during 2009-10 and beyond by highlighting:
Understanding the impact of MDM market momentum, maturation, and consolidation
Coping with the skills shortage for data governance, MDM project leadership, & enterprise architecture
Identifying the essential (vs. desirable) features of an enterprise-strength MDM solution
Smart Data - The Foundation for Better Business OutcomesDATAVERSITY
This webinar will explore emerging technologies that enable a new generation of intelligent applications and enterprise systems. It will also act as a roadmap for evaluating and integrating these technologies and practices, and set the stage for our 2016 series of Smart Data webinars.
In the last few years, we have witnessed an AI renaissance with significant advances in areas such as machine-learning/deep learning, natural language processing, and biologically-inspired processor architectures. Simultaneously, the rise of the Industrial Internet of Things - which together with the “traditional” Internet form the Internet of Everything – foreshadows a connected world of smarter homes, cities, and even business relationships.
These “cognitive connections” are supported by advanced analytics and smart data. Join the discussion to see how you and your organization can benefit from getting started now.
Slides: Bridging the Data Disconnect – Trends in Global Data ManagementDATAVERSITY
Maintaining a competitive edge in today’s digital landscape hinges on the ability to leverage accurate and reliable data to make informed and strategic business decisions. But transforming data from liability to strategic asset is far from simply flipping a switch.
New research from Experian shows that while 85 percent of businesses believe data is one of their most valuable assets, a high degree of inaccuracy is hindering critical initiatives. In addition, rising levels of data debt and a data skills shortage are converging to make data insights harder to achieve. To tackle the large degree of distrust in information, a growing number of companies are investing in specialized data talent and data literacy programs.
Join us to uncover new research from more than 1,000 global professionals as we take a deep dive into:
• The top challenges in leveraging trusted data
• How data debt drags down ROI
• Trends around data skills, talent, and the rise of data literacy
• Tips for how you can drive a data-driven culture
Data Integration Trends Businesses Should Watch for in 2021Safe Software
2020 reminded us that the future is never certain. However, it also showed that the future could be quickly adapted to if we have up-to-date and readily available data to make decisions.
To offer the most business value and stay competitive in 2021, data leaders need to embrace digital transformation in the form of:
- Automation
- Augmented Reality (AR)
- Improving the customer experience (with machine learning)
- Evolution to the cloud
- Spatial data importance to the enterprise
- IoT data streams
- And more!
In this webinar, join co-founders Don Murray and Dale Lutz as they offer insight and predictions on these areas. Plus, they’ll do an extended Q&A session so you can get feedback on your own data strategy or solutions to your data challenges.
This presentation provides you with an understanding of reference and master data management (MDM) goals, including establishing and implementing authoritative data sources, establishing and implementing more effective means of delivering data to various business processes, and increasing the quality of information used in organizational analytical functions (such as BI). Attendees will learn how to incorporate data quality engineering into the planning of reference and MDM. Finally, we will discuss why MDM is so critical to the organization’s overall data strategy.
Takeaways:
•What is reference and MDM?
•Why are reference and MDM important?
•How to use Reference and MDM Frameworks
•Guiding principles & best practices for MDM
DAS Slides: Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key inter-relationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how Data Architecture is a key component of an overall enterprise architecture for enhanced business value and success.
Master Data Management's Place in the Data Governance Landscape CCG
For many organizations, Master Data Management is a necessity to ensure consistency and accuracy of essential business entities. It further plays alongside data architecture, metadata management, data quality, security & privacy, and program management in the Data Governance ecosystem.
Join CCG's data governance subject matter experts as they overview the fundamentals of Master Data Management at our Atlanta-based Data Analytics Meetup. This event will discuss how to enable components of data governance within your organization and review how to best leverage Microsoft's SQL Server Master Data Services.
DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...DATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task. The opportunity in getting it right can be significant, however, as data drives many of the key initiatives in today’s marketplace: digital transformation, marketing, customer centricity, and more. This webinar will help de-mystify Data Strategy and Data Architecture and will provide concrete, practical ways to get started.
Align Business Data & Analytics for Digital TransformationPerficient, Inc.
Your success in the digital world relies primarily on how well you manage and analyze the data coming from disparate internal systems and external channels. You need to understand how to innovate and leverage digital data to drive sales and productivity.
Existing principles driving traditional data architecture are inadequate to support the volume, variety, and velocity of this new data ecosystem. In these scenarios, information governance (master data management, metadata, data quality and data governance) becomes highly critical in terms of providing the context for operational, competitive and advanced analytics.
Companies require a data architecture and strategy that can support efficient digital transformation by unlocking the value in all data sources to provide mission-critical insights and informed decision-making.
Our experts covered:
-Five information management pillars necessary for digital transformation
-Stages of digital information maturity, reflecting the typical path of an organization implementing this new data ecosystem
-Issues, challenges, and approaches to governing this new architecture
How to Create and Manage a Successful Analytics OrganizationDATAVERSITY
For the last few years, analytics, data science and data management have achieved tremendous exposure on all the media channels. Big Data has become a major topic of discussion, catalyzing attention among the C-Level executives and driving investments and projects inside the enterprise. However, it is really interesting that just a selected group of business has created successful data teams and has mastered the skills to manage it. What we have seen is that most companies still do not know how to create, implement and manage a data and analytics organization. Above all, if data has become an strategic asset and is being considered the new oil for the 21st century economy, what your strategy to handle it ? This webinar will help to bring some concepts and ideas to enlighten your path to create and manage an analytics organization, providing some real life examples on companies which did it.
Bridging the Data Divide: Driving Data and Analytics Projects Forward with Tr...Precisely
There’s no debate that data is the most valuable strategic asset available to your business today. According to ‘Voice of the Enterprise: Data Management and Analytics 2020’ by 451 Research, 63% of enterprises use data to drive nearly all or most of their strategic decisions.
Join Amy O’Connor, Precisely Chief Data and Information Officer, and Paige Bartley, 451 Research Senior Research Analyst for Data, AI, and Analytics as Paige shares the latest research on data and analytics drawn from surveys of business and technology decision-makers and chats with Amy about her experience implementing Precisely products to ensure data integrity and fuel the company’s data-driven business model.
View this on-demand webinar to hear Amy and Paige share their perspectives on key points from the research, including how:
• Only 25% of respondents rate more than 80% of their recent data and analytics initiatives as successful
• 78% of those most successful with data and analytics initiatives are using or considering using technologies to accelerate the analysis of distributed data
• 24% of respondents are investing in programs that increase trust in data by improving accuracy, quality, lineage and/or governance to improve their data culture
Be Digital or Die - Predictive Analytics for Digital TransformationFintricity
A look at leveraging big data and predictive analytics for digital transformation. This deck was presented at the Predictive Analytics & Innovation Summit in London. 10th May 2016, by Alpesh Doshi, Founder of Fintricity.
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
RWDG Slides: Governing Your Data Catalog, Business Glossary, and Data DictionaryDATAVERSITY
Data catalogs, business glossaries, and data dictionaries house the metadata that builds organizational confidence in your data. First and foremost, the people in your organization need to be engaged in leveraging the tools, understanding the data that is available and who is responsible for the data, and knowing how to get their hands on the data they need to perform their job function. This metadata will not govern itself.
Join Bob Seiner for the April RWDG webinar, where he will discuss how to govern the metadata in a data catalog, business glossary, and data dictionary. People must have confidence in the metadata associated with the data that you need them to trust. Therefore, the metadata in your data catalog, business glossary, and data dictionary must be governed. Learn how to govern that metadata in this webinar.
Bob will discuss the following subjects in this webinar:
• Successful Data Governance relies on value from very important tools
• What it means to govern your data catalog, business glossary, and data dictionary
• Why governing the metadata in these tools is so important
• The roles necessary to govern these tools
• Value expected from governing the catalog, glossary, and dictionary
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
Models & Tags: Building User-Focused Content Models That Actually WorkSeth Maislin
Reliable, user-focused domain and content models are foundational in all information processes, from findability to reuse to security. In this session you'll learn why models are so important, and a repeatable process for creating and using them effectively. Written by Seth Maislin, Principal Consultant of Taxonomy at Earley & Associates. www.earley.com
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.
Conference Chairman Keynote & Welcome
Capitalizing on MDM in Times of Crisis
Aaron Zornes, Founder & Chief Research Officer, The MDM Institute
--------------------------------------------------------------------------------
MDM is particularly important in today’s increasingly complex and harsh global business landscape – in part due to increasingly demanding suppliers, trading partners, customers … as well as financial challenges and government regulations. Despite the current economic crisis, analyst firms have declared MDM to be “recession proof” as businesses strive to dramatically reduce costs, meet compliance reporting mandates, deliver increased sales and marketing effectiveness, and provide superior service to customers and suppliers. MDM and its variants – customer data integration (CDI), product information management (PIM), and data governance – all significantly contribute to these tactical business priorities.
Research analysts at the MDM Institute annually produce a set of twelve milestones for their MDM Road Map to help Global 5000 enterprises focus efforts for their own large-scale, mission-critical MDM projects. This keynote will focus on this set of strategic planning assumptions and present an enlightening view of the key trends and issues facing IT organizations during 2009-10 and beyond by highlighting:
Understanding the impact of MDM market momentum, maturation, and consolidation
Coping with the skills shortage for data governance, MDM project leadership, & enterprise architecture
Identifying the essential (vs. desirable) features of an enterprise-strength MDM solution
Smart Data - The Foundation for Better Business OutcomesDATAVERSITY
This webinar will explore emerging technologies that enable a new generation of intelligent applications and enterprise systems. It will also act as a roadmap for evaluating and integrating these technologies and practices, and set the stage for our 2016 series of Smart Data webinars.
In the last few years, we have witnessed an AI renaissance with significant advances in areas such as machine-learning/deep learning, natural language processing, and biologically-inspired processor architectures. Simultaneously, the rise of the Industrial Internet of Things - which together with the “traditional” Internet form the Internet of Everything – foreshadows a connected world of smarter homes, cities, and even business relationships.
These “cognitive connections” are supported by advanced analytics and smart data. Join the discussion to see how you and your organization can benefit from getting started now.
Slides: Bridging the Data Disconnect – Trends in Global Data ManagementDATAVERSITY
Maintaining a competitive edge in today’s digital landscape hinges on the ability to leverage accurate and reliable data to make informed and strategic business decisions. But transforming data from liability to strategic asset is far from simply flipping a switch.
New research from Experian shows that while 85 percent of businesses believe data is one of their most valuable assets, a high degree of inaccuracy is hindering critical initiatives. In addition, rising levels of data debt and a data skills shortage are converging to make data insights harder to achieve. To tackle the large degree of distrust in information, a growing number of companies are investing in specialized data talent and data literacy programs.
Join us to uncover new research from more than 1,000 global professionals as we take a deep dive into:
• The top challenges in leveraging trusted data
• How data debt drags down ROI
• Trends around data skills, talent, and the rise of data literacy
• Tips for how you can drive a data-driven culture
Data Integration Trends Businesses Should Watch for in 2021Safe Software
2020 reminded us that the future is never certain. However, it also showed that the future could be quickly adapted to if we have up-to-date and readily available data to make decisions.
To offer the most business value and stay competitive in 2021, data leaders need to embrace digital transformation in the form of:
- Automation
- Augmented Reality (AR)
- Improving the customer experience (with machine learning)
- Evolution to the cloud
- Spatial data importance to the enterprise
- IoT data streams
- And more!
In this webinar, join co-founders Don Murray and Dale Lutz as they offer insight and predictions on these areas. Plus, they’ll do an extended Q&A session so you can get feedback on your own data strategy or solutions to your data challenges.
This presentation provides you with an understanding of reference and master data management (MDM) goals, including establishing and implementing authoritative data sources, establishing and implementing more effective means of delivering data to various business processes, and increasing the quality of information used in organizational analytical functions (such as BI). Attendees will learn how to incorporate data quality engineering into the planning of reference and MDM. Finally, we will discuss why MDM is so critical to the organization’s overall data strategy.
Takeaways:
•What is reference and MDM?
•Why are reference and MDM important?
•How to use Reference and MDM Frameworks
•Guiding principles & best practices for MDM
The Connected Consumer – Real-time Customer 360Capgemini
With Business Data Lake technologies based on EMC’s Big Data portfolio it becomes possible to move away from channel specific analytics towards a 360 customer view.
This presentation will show how technologies like Spark, Hadoop, and Kafka help companies gain a real-time view of everything their customers do and make changes to customer touch points whether mobile, web, in-store, direct marketing or existing transactional systems.
Presented by Steve Jones, Vice President, Insights & Data, Capgemini at EMC World 2016
http://www.capgemini.com/emc
Strategic Business Requirements for Master Data Management SystemsBoris Otto
This presentation describes strategic business requirements of master data management (MDM) systems. The requirements were developed in a consortium research approach by the Institute of Information Management at the University of St. Gallen, Switzerland, and 20 multinational enterprises.
The presentation was given at the 17th Amercias Conference on Information Systems (AMCIS 2011) in Detroit, MI.
The research paper on which this presentation is based on can be found here: http://www.alexandria.unisg.ch/Publikationen/Zitation/Boris_Otto/177697
As the strategic importance of data has increased, new approaches to customer analytics have emerged as well. As customer interactions with companies grow and diversify, the need to integrate data faster and deliver real-time insights is critical. This presentation explores the underlying trends driving companies to become more data-driven and invest in customer analytics. And, it outlines three types of approaches to capturing, managing, analyzing, and activating customer knowledge and insights.
The concept of a 360° view, especially of customers, although it potentially applies to other things too, has been around for a substantial period of time. The idea behind the 360° view of customers is that the more you know about your customers the easier it will be to meet their needs, both in terms of products and aftersales care, and to market additional goods and services to them in the most efficient fashion. Thus a 360° view helps both in terms of customer retention and acquisition, as well as up-sell and cross-sell.
In this presentation which complements Bloor Whitepaper on the "Extended 360 degree view" we will discuss why we believe that extending the traditional 360° view makes sense and we will give some uses that demonstrate why the extended 360° view represents an opportunity, both for those that have already implemented a 360° view and for those that have not.
Big MDM Part 2: Using a Graph Database for MDM and Relationship ManagementCaserta
During this Big Data Warehousing Meetup, we discussed how graph databases work, shared some real world use cases, and showed a live demo of the world’s leading graph database, Neo4J. Pitney Bowes demonstrated their new MDM product developed on a graph database.
For more information, check out the other slides from this meetup or visit our website at www.casertaconcepts.com
The Importance of MDM - Eternal Management of the Data MindDATAVERSITY
Despite its immaterial nature, data has a tendency to pile up as time goes on, and can quickly be rendered unusable or obsolete without careful maintenance and streamlining of processes for its management. This presentation will provide you with an understanding of reference and master data management (MDM), one such method for keeping mass amounts of business data organized and functional towards achieving business goals.
MDM’s guiding principles include the establishment and implementation of authoritative data sources and effective means of delivering data to various business processes, as well as increases to the quality of information used in organizational analytical functions (such as BI).
To that end, attendees of this webinar will learn how to:
- Structure their data management processes around these principles
- Incorporate data quality engineering into the planning of reference and MDM
- Understand why MDM is so critical to their organization’s overall data strategy
Master data management (mdm) & plm in context of enterprise product managementTata Consultancy Services
The presentation discusses the classical features and advantages of Master Data Management (MDM) system along with appropriate situations to use it. How do companies apply MDM who design, manufacture and sell their products in several geographies facing challenges in making appropriate decisions on their investment in PLM & MDM space?
Another important aspect covers the comparison/relation between a MDM system (or Product Master System) and Enterprise PLM system. How can you maximize your ROI on both PLM and MDM investments? With examples from different industries the key takeaways include whether your organization requires an MDM solution or not.
The what, why, and how of master data managementMohammad Yousri
This presentation explains what MDM is, why it is important, and how to manage it, while identifying some of the key MDM patterns and best practices that are emerging. This presentation is a high-level treatment of the problem space.
The presentation is summarizing the article of Microsoft in a simple way.
https://msdn.microsoft.com/en-us/library/bb190163.aspx
Organizations across diverse industries are in pursuit of Customer 360, by integrating customer information across multiple channels, systems, devices and products. Having a 360-degree view of the customer enables enterprises to improve the interaction experience, drive customer loyalty and improve retention. However delivering a true Customer 360 can be very challenging.
Overcoming the Challenges of your Master Data Management JourneyJean-Michel Franco
This Presentaion runs you through all the key steps of an MDM initiative. It considers and showcase the key milestones and building blocks that you will have to roll-out to make your MDM
journey
-> Please contact Talend for a dedicated interactive sessions with a storyboard by customer domain
How to Drive Better Business Insights with Strong Data GovernanceMatt Dillon
Learn why leading CMOs and CEOs are making data governance and data integration a top priority for driving revenue growth and improving profitability.
Your data is one of the most important assets you have as a business but are you taking the necessary steps to manage your data with care?
Are you using your data to improve the customer experience and make better business decisions?
Webinar includes:
- Creating a centre of excellence
- Establishing data standardization
- Developing application management plans
- Release management
- Incorporating data & systems integration strategies
- Data cleansing essentials
A Pre-Built Customer Intelligence Management System
AllSight empowers your customer-facing employees to create exceptional customer experiences. AllSight is different than your existing systems.
It manages an evolving likeness of your customer. It investigates every possible source of customer data. And it generates deep customer intelligence through analytics. It delivers that intelligence to your customer-facing employees through their existing applications or via its customer intelligence dashboard.
Learn more by reading our FREE white paper on Customer Intelligence Management and the new era of Customer 360.
A pre-built Customer Intelligence Management system.
AllSight empowers your customer-facing employees to create exceptional customer experiences. AllSight is different than your existing systems.
It manages an evolving likeness of your customer. It investigates every possible source of customer data. And it generates deep customer intelligence through analytics. It delivers that intelligence to your customer-facing employees through their existing applications or via its customer intelligence dashboard.
Learn more by reading our FREE white paper on Customer Intelligence Management and the new era of Customer 360.
Why there are so many problems with streamlining data strategy ? What are the major problems ? How do you solve them ?
Using an approach based on Agile and Lean Concepts to achieve the goal of actionable data & analytics
These slides - based on the webinar featuring Dennis Drogseth, VP of research at leading IT analyst firm Enterprise Management Associates (EMA), and Sasha Gilenson, founder and CEO at Evolven Software - examine how “tiered” or “blended” sources can bring fast time to value across performance management, change management and other use cases.
These slides cover:
- Why, and in what contexts, do IT organizations need to change to become more effective and valued?
- What is tiered or blended analytics, and how can it come to the rescue?
- How is blended analytics different from more traditional big data approaches?
Data-Ed Online Webinar: Business Value from MDMDATAVERSITY
This presentation provides you with an understanding of the goals of reference and master data management (MDM), including establishing and implementing authoritative data sources, establishing and implementing more effective means of delivery data to various business processes, as well as increasing the quality of information used in organizational analytical functions (such as BI). You will understand the parallel importance of incorporating data quality engineering into the planning of reference and MDM.
Takeaways:
What is reference and MDM?
Why are reference and MDM important?
Reference and MDM Frameworks
Guiding principles & best practices
This presentation provides you with an understanding of the goals of reference and master data management (MDM), including establishing and implementing authoritative data sources, establishing and implementing more effective means of delivery data to various business processes, as well as increasing the quality of information used in organizational analytical functions (such as BI). You will understand the parallel importance of incorporating data quality engineering into the planning of reference and MDM.
Check out more of our Data-Ed webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/
Increasing Your Business Data and Analytics MaturityDATAVERSITY
For a few years now, companies of all sizes have been looking at data as a lever to increase revenues, reduce costs or improve efficiency. However, we believe the power of using data as a strategic asset is still in its early stages. One of the main reasons for that is business leaders still do not understand that the data & analytics maturity should be seen as a long time journey and an evolving enterprise learning. This webinar will present some key points on how data management leaders can succeed in their mission by sharing some practical experiences.
Creating the golden record that makes every click personalJean-Michel Franco
This presentation shares real-world customer examples that illustrate how Master Data Management can make every customer interaction personal, including:
- Collect and reconcile customer data about identities, profiles, purchase history, preferences, and transactions
- Transform and augment this data into a 360° view of the customer with context, intentions, relationships, and interactions
- Turn data into insights with segments, scores, forecasts and recommendations
- Connect in real time to customer touch-points and turn those insights into increased conversion rates and customer loyalty
Data Integrity: From speed dating to lifelong partnershipPrecisely
Governance has little to do with governance…it’s about delivering and demonstrating value. It’s one thing for your colleagues to intellectually believe in the value of data, good data, and governed data, but it’s another thing entirely to have them emotionally engaged and excited to be involved. In this presentation from the CDO Sit-Down series, Shaun Connolly, Vice President of International Strategic Services, shares his thoughts and experience on approaches to win over reluctant leaders and business teams and describe the key components of successful programs.
The Business Value of Metadata for Data GovernanceRoland Bullivant
In today’s digital economy, data drives the core processes that deliver profitability and growth - from marketing, to finance, to sales, supply chain, and more. It is also likely that for many large organizations much of their key data is retained in application packages from SAP, Oracle, Microsoft, Salesforce and others. In order to ensure that their foundational data infrastructure runs smoothly, most organizations have adopted a data governance initiative. These typically focus on the people and processes around managing data and information. Without an actionable link to the physical systems that run key business processes, however, governance programs can often lack the ‘teeth’ to effectively implement business change.
Metadata management is a process that can link business processes and drivers with the technical applications that support them. This makes data governance actionable and relevant in today’s fast-paced and results-driven business environment. One of the challenges facing data governance teams however, is the variety in format, accessibility and complexity of metadata across the organization’s systems.
In an era where artificial intelligence (AI) stands at the forefront of business innovation, Information Architecture (IA) is at the core of functionality. See “There’s No AI Without IA” – (from 2016 but even more relevant today)
Understanding and leveraging how Information Architecture (IA) supports AI synergies between knowledge engineering and prompt engineering is critical for senior leaders looking to successfully deploy AI for internal and externally facing knowledge processes. This webinar be a high-level overview of the methodologies that can elevate AI-driven knowledge processes supporting both employees and customers.
Core Insights Include:
Strategic Knowledge Engineering: Delve into how structuring AI's knowledge base is required to prevent hallucinations, enable contextual retrieval of accurate information. This will include discussion of gold standard libraries of use cases support testing various LLMs and structures and configurations of knowledge base.
Precision in Prompt Engineering: Learn the art of crafting prompts that direct AI to deliver targeted, relevant responses, thereby optimizing customer experiences and business outcomes.
Unified Approach for Enhanced AI Performance: Explore the intersection of knowledge and prompt engineering to develop AI systems that are not only more responsive but also aligned with overarching business strategies.
Guiding Principles for Implementation: Equip yourself with best practices, ethical guidelines, and strategic considerations for embedding these technologies into your business ecosystem effectively.
This webinar is designed to empower business and technology leaders with the knowledge to harness the full potential of AI, ensuring their organizations not only keep pace with digital transformation but lead the charge. Join us to map a roadmap to fully leverage Information Architecture (IA) and AI chart a course towards a future where AI is a key pillar of strategic innovation and business success.
Many Organizations are struggling with the best way to govern and manage the use of Generative AI in the enterprise. There are many dimensions to this challenge ranging from ethical issues, data architecture and quality, legal and copywrite, operational and more.
This is why a governance framework needs to be carefully designed and put into place so the business can make the most use of this truly revolutionary technology, reduce and mitigate risks, control costs, maintain a positive employee and customer experience and most importantly, find competitive advantage in the marketplace.
Improving product data quality will inevitably increase your sales. However, there are other benefits (beyond improved revenue) from investing in product data to sustain your margins while lowering costs.
One poorly understood benefit of having complete, accurate, consistent product data is the reduction in costs of product returns. Managing logistics and resources needed to process returns, as well as the reduction in margins based on the costs of re-packaging or disposing of returned products, are getting more attention and analysis than in previous years.
This is a B2C and a B2B issue, and keeping more of your already-sold product in your customer’s hands will lower costs and increase margins at a fraction of the cost of building new market share.
This webinar will discuss how EIS can assist in all aspects of product data including increasing revenue and reducing the costs of returns. We will discuss how to frame the data problems and solutions tied to product returns, and ways to implement scalable and durable changes to improve margins and increase revenue.
In the rapidly evolving world of ChatGPT and Large Language Models (LLMs), businesses are understandably apprehensive. Numerous potential hazards and hurdles exist such as:
Unrealistic expectations of LLMs as a magic solution to managing corporate content without requisite human involvement
Difficulty distinguishing between creative outputs and fabricated responses (hallucinations)
Decisions around training models: balancing usefulness with the threat of exposing trade secrets or other proprietary knowledge
Absence of clear audit trails and citation sources
The risk of generating responses misaligned with company policies or brand image
Potential financial burden of proprietary LLMs and related enterprise software platforms
In this webinar, we will examine a structured approach to harvest, utilize, and protect corporate knowledge resources. We will explore how both commercial and open-source large language models can be leveraged to deliver precise conversational responses without jeopardizing intellectual property.
Learn how your organization can effectively use LLM based applications for competitive advantage. Using a general LLM will provide efficiency, but through standardization. Differentiation using your corporate terminology and knowledge will allow for competitive advantage. You don’t have to deploy ChatGPT to benefit from these approaches. They will improve the information metabolism of the enterprise and pave the way for advanced AI applications.
In this session we will be discussing the challenges the organization faced in content usability, traceability, and findability, hindering their internal training workflows and access to critical knowledge assets.
We will also discuss what’s next on the content and information horizon, including the role of machine learning and why these approaches are needed for AI-Powered applications, including LLMs and ChatGPT types of information access.
Generative AI is getting all the attention, headlines, and industry hype. Organizations are looking at how it can be used to create better employee and customer experiences by unlocking the potential stored in the vast troves of unstructured data that house knowledge assets.
We will begin by providing an overview of the fundamental concepts and advances in generative AI, followed by an in-depth examination of the importance of knowledge management in developing, implementing, and improving these systems.
We’ll discuss knowledge management approaches for the organization and retrieval of information, how retrieval fits in with content generation, and the challenges and opportunities it presents for the enterprise.
The Increasing Criticality of MDM for Personalization for Customers and Employees
Master data management seems to be one of those perennial, evergreen programs that organizations continue to struggle with.
Every couple of years people say, “we're going to get a handle on our master data” and then spend hundreds of thousands to millions and tens of millions of dollars working toward a solution.
The challenge is that many of these solutions are not really getting to the root cause of the problem. They start with technology and begin by looking at specific data elements rather than looking at the business concepts that are important to the organization.
MDM programs are also difficult to anchor on a specific business value proposition such as improving the top line. Many initiatives are so deep in the weeds and so far upstream that executives lose interest and they lose faith in the business value that the project promises. Meanwhile frustrated data analysts, data architects and technology organizations feel cut off at the knees because they can't get the funding, support and attention that they need to be successful.
We've seen this time after time and until senior executives recognize the value and envision where the organization can go with control over its data across domains, this will continue to happen over and over again. Executives all nod their heads and say “Yes! Data is important, really important!” But when they see the price tag they say, “Whoa hold on there, it's not that important”.
Well, actually, it is that important.
We can't forget that under all of the systems, processes and shiny new technologies such as artificial intelligence and machine learning lies data. And that data is more important than the algorithm. If you have bad data your AI is not going to be able to fix it. Yes there are data remediation applications and there are mechanisms to harmonize or normalize certain data elements. But looking at this holistically requires human judgment: understanding business processes, understanding data flows, understanding dependencies and understanding of the entire customer experience ecosystem and the role of upstream tools, technologies and processes that enable that customer experience.
Until we take that holistic approach and connect it to business value these things are not going to get the time, attention and resources that they need.
Seth Earley, Founder & CEO, Earley Information Science
Dan O'Connor, Senior Product Manager at inriver
A knowledge graph is a type of data representation that utilizes a network of interconnected nodes to represent real-world entities and the relationships between them. This makes it an ideal tool for data discovery, compliance, and governance tasks, as it allows users to easily navigate and understand complex data sets.
In this webinar, we will demystify knowledge graphs and explore their various applications in data discovery, compliance, and governance. We will begin by discussing the basics of knowledge graphs and how they differ from other data representation methods. Next, we will delve into specific use cases for knowledge graphs in data discovery, such as for exploring and understanding large and complex datasets or for identifying hidden patterns and relationships in data.
We will also discuss how knowledge graphs can be used in compliance and governance tasks, such as for tracking changes to data over time or for auditing data to ensure compliance with regulations. Throughout the webinar, we will provide practical examples and case studies to illustrate the benefits of using knowledge graphs in these contexts.
Finally, we will cover best practices for implementing and maintaining a knowledge graph, including tips for choosing the right technology and data sources, and strategies for ensuring the accuracy and reliability of the data within the graph.
Overall, this webinar will provide an executive level overview of knowledge graphs and their applications in data discovery, compliance, and governance, and will equip attendees with the tools and knowledge they need to successfully implement and utilize knowledge graphs in their own organizations.
*Thanks to ChatGPT for help writing this abstract.
Some product information management (PIM) tools make it difficult to change core data models once they have been set up in the system. To avoid costly rework, you can utilize a “pre-PIM” design tool as a PIM accelerator. This class of software allows you to:
**Iterate on designs before committing to a PIM architecture
Improve data quality
**Collaborate on decision-making and audit trails
**Set up metrics around product data and attribute structure
**Correlate performance measures with metrics – product data and hierarchy improvements are correlated with user behaviors and outcomes
**Integrate governance content prior to PIM load
**Decrease reliance on spreadsheets
While some PIM tools include a subset of these functions, they are often lacking in flexibility, functionality, and integration capabilities, especially around product data model and hierarchy design changes.
In this webinar our PIM experts introduce a pre-PIM software solution that enables fluid design changes while ensuring data integrity, reducing risk, increasing stakeholder engagement, and showing clear ROI on investments in product data.
If you want to deliver a truly personalized product experience and strengthen customer loyalty, a Product Information Management System (PIM) is a must. PIM systems ensure clean, complete, and consistent data to enhance both the customer and employee experience. With intuitive management of complex product information, PIM unites internal teams with better visibility and reporting.
In this session our experts in enterprise information architecture and PIM technology explain ways you can:
--Streamline the complexity of supply chain information
--Publish consistent product information across all channels
--Adapt quickly to market changes and bring products to market faster
--Increase the total performance and profitability your Ecommerce business
Speakers:
Chantal Schweizer, Director of Solution Delivery at Earley Information Science
Jon C. Marsella, Founder, Chairman, and CEO at Jasper Commerce Inc.
How Large Enterprises are Saving Millions in Operational Costs and Improving the Employee Experience.
In this session, Earley Information Science, with partner PeopleReign, will show how these programs can rapidly produce measurable results in weeks rather than months and years. While large-scale knowledge problems cannot be solved overnight, by focusing on narrow AI with clearly defined processes and curated knowledge, organizations can see ROI in as little as 30 days.
In today's world everyone, including your B2B customers, expect personalized buying experiences. Unless you have the right information architecture in place to power your digital experience tools you will not be able to scale and retain trust with your customers.
In this webinar, B2B ecommerce experts Allison Brown with Earley Information Science and Jason Hein with Bloomreach walk through the reasons why you must invest in information architecture foundations in order to compete.
Understand the key steps to set up your next data discovery initiative for success using the latest methodology and technologies with Earley Information Science. In this webinar we partner with Expert.AI, a recognized leader in document-oriented text analytics platforms to explain the technical and methodological advances that enable better data discovery.
Seth Earley, CEO & Founder of Earley Information Science and Peter Crocker, CEO & Co-founder of Oxford Semantic Technologies discuss powering personalized search with knowledge graphs to transform legacy faceted search into personalized product discovery.
In this webinar Seth Earley establishes the formula for AI success, demystifies the topic for executives and provides actionable advice for data strategists.
Key Takeaways:
**AI-Powered solutions begin with a focus on business goals
**Successful AI requires a semantic data layer built on a solid enterprise information architecture.
**Instrumenting measuring ROI should be part of every AI program
Enterprises are increasingly recognizing the critical need for knowledge management (KM) to power cognitive AI. In fact, KM and AI are two sides of the same coin. Training a chatbot requires the same organized information that we use to train a human. When you engineer knowledge correctly, you serve the needs of people today and prepare for greater automation in the future. In fact, the long term success of the organization will depend on doing just that – especially when the competition builds high functionality bots that will produce lower costs and better customer service. Those without the capability will not be competitive.
In this panel discussion, our experts discuss examples and approaches that show how KM supports AI and how to ensure the success of your KM initiative.
Knowledge management and AI
People and cultural considerations
Business justification for long term investment
In this session Seth Earley, author of the AI Powered Enterprise, discusses how to harness the power of artificial intelligence to drive extraordinary competitive advantage.
Seth Earley, Founder & CEO of Earley Information Science and author of the award winning book, "The AI Powered Enterprise" explains how advanced concepts in information architecture, such as ontologies and knowledge engineering, are the basis for streamlined content workflows.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
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.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
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).