The document describes an upcoming webinar on creating controlled vocabularies for competitive intelligence. The webinar will feature two speakers, Justin Soles and Lisa Coady, and will cover topics such as what a controlled vocabulary is, how it can help competitive intelligence work, and best practices for developing one. Attendees are encouraged to ask questions during the webinar.
ADV Slides: How to Improve Your Analytic Data Architecture MaturityDATAVERSITY
Many organizations are immature when it comes to data use. The answer lies in delivering a greater level of insight from data, straight to the point of need. Enter: machine learning.
In this webinar, William will look at categories of organizational response to the challenge across strategy, architecture, modeling, processes, and ethics. Machine learning maturity levels tend to move in harmony across these categories. As a general principle of maturity models, you can’t skip levels in any category, nor can you advance in one category well beyond the others.
Vis-à-vis ML, attaining and retaining momentum up the model is paramount for success. You will ascend the model through concerted efforts delivering business wins utilizing progressive elements of the model, and thereby increasing your machine learning maturity. The model will evolve. No plateaus are comfortable for long.
With ML maturity markers, sequencing, and tactics, this webinar provides a plan for how to build analytic Data Architecture maturity in your organization.
DAS Slides: Emerging Trends in Data Architecture — What’s the Next Big Thing?DATAVERSITY
With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY survey on emerging trends in data architecture, along with practical commentary and advice from industry expert Donna Burbank.
DAS Slides: Data Quality Best PracticesDATAVERSITY
Tackling data quality problems requires more than a series of tactical, one off improvement projects. By their nature, many data quality problems extend across and often beyond an organization. Addressing these issues requires a holistic architectural approach combining people, process and technology. Join Nigel Turner and Donna Burbank as they provide practical ways to control data quality issues in your organization.
Data-Ed Online: Unlock Business Value through Reference & MDMDATAVERSITY
In order to succeed, organizations must realize what it means to utilize reference and MDM in support of business strategy. This presentation provides you with an understanding of the goals of reference and MDM, including the establishment and implementation of authoritative data sources, more effective means of delivering data to various business processes, as well as increasing the quality of information used in organizational analytical functions, e.g. BI. We also highlight the equal importance of incorporating data quality engineering into all efforts related to reference and master data management.
Learning objectives include:
What is Reference & MDM and why is it important?
Reference & MDM Frameworks and building blocks
Guiding principles & best practices
Understanding foundational reference & MDM concepts based on the Data Management Body of Knowledge (DMBOK)
Utilizing reference & MDM in support of business strategy
Metadata is hotter than ever, according to a number of recent DATAVERSITY surveys. More and more organizations are realizing that in order to drive business value from data, robust metadata is needed to gain the necessary context and lineage around key data assets. At the same time, industry regulations are driving the need for better transparency and understanding of information.
While metadata has been managed for decades, new strategies & approaches have been developed to support the ever-evolving data landscape, and provide more innovative ways to drive business value from metadata. This webinar will provide an overview of metadata strategies & technologies available to today’s organization, and provide insights into building successful business strategies for metadata adoption & use.
DAS Slides: Data Modeling at the Environment Agency of England – Case StudyDATAVERSITY
The Environment Agency uses data models as a key part of their digital journey in reporting scientific results for water quality, fisheries, conservation and ecology, flood management, and more. Join special guest Becky Russell from the Environment Agency along with host Donna Burbank as they discuss how they were able to gain buy-in from various departments across the organization using data models and data standards.
Data Architecture Strategies Webinar: Emerging Trends in Data Architecture – ...DATAVERSITY
A robust data architecture is at the core what’s driving today’s innovative, data-driven organizations. From AI to machine learning to Big Data – a strong data architecture is needed in order to be successful, and core fundamentals such as data quality, metadata management, and efficient data storage are more critical than ever.
With the vast array of new technologies available to support these trends, how do you make sense of it all? Our panel of experts will offer their perspectives on how the latest trends in data architecture can support your organization’s data-driven goals.
ADV Slides: How to Improve Your Analytic Data Architecture MaturityDATAVERSITY
Many organizations are immature when it comes to data use. The answer lies in delivering a greater level of insight from data, straight to the point of need. Enter: machine learning.
In this webinar, William will look at categories of organizational response to the challenge across strategy, architecture, modeling, processes, and ethics. Machine learning maturity levels tend to move in harmony across these categories. As a general principle of maturity models, you can’t skip levels in any category, nor can you advance in one category well beyond the others.
Vis-à-vis ML, attaining and retaining momentum up the model is paramount for success. You will ascend the model through concerted efforts delivering business wins utilizing progressive elements of the model, and thereby increasing your machine learning maturity. The model will evolve. No plateaus are comfortable for long.
With ML maturity markers, sequencing, and tactics, this webinar provides a plan for how to build analytic Data Architecture maturity in your organization.
DAS Slides: Emerging Trends in Data Architecture — What’s the Next Big Thing?DATAVERSITY
With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY survey on emerging trends in data architecture, along with practical commentary and advice from industry expert Donna Burbank.
DAS Slides: Data Quality Best PracticesDATAVERSITY
Tackling data quality problems requires more than a series of tactical, one off improvement projects. By their nature, many data quality problems extend across and often beyond an organization. Addressing these issues requires a holistic architectural approach combining people, process and technology. Join Nigel Turner and Donna Burbank as they provide practical ways to control data quality issues in your organization.
Data-Ed Online: Unlock Business Value through Reference & MDMDATAVERSITY
In order to succeed, organizations must realize what it means to utilize reference and MDM in support of business strategy. This presentation provides you with an understanding of the goals of reference and MDM, including the establishment and implementation of authoritative data sources, more effective means of delivering data to various business processes, as well as increasing the quality of information used in organizational analytical functions, e.g. BI. We also highlight the equal importance of incorporating data quality engineering into all efforts related to reference and master data management.
Learning objectives include:
What is Reference & MDM and why is it important?
Reference & MDM Frameworks and building blocks
Guiding principles & best practices
Understanding foundational reference & MDM concepts based on the Data Management Body of Knowledge (DMBOK)
Utilizing reference & MDM in support of business strategy
Metadata is hotter than ever, according to a number of recent DATAVERSITY surveys. More and more organizations are realizing that in order to drive business value from data, robust metadata is needed to gain the necessary context and lineage around key data assets. At the same time, industry regulations are driving the need for better transparency and understanding of information.
While metadata has been managed for decades, new strategies & approaches have been developed to support the ever-evolving data landscape, and provide more innovative ways to drive business value from metadata. This webinar will provide an overview of metadata strategies & technologies available to today’s organization, and provide insights into building successful business strategies for metadata adoption & use.
DAS Slides: Data Modeling at the Environment Agency of England – Case StudyDATAVERSITY
The Environment Agency uses data models as a key part of their digital journey in reporting scientific results for water quality, fisheries, conservation and ecology, flood management, and more. Join special guest Becky Russell from the Environment Agency along with host Donna Burbank as they discuss how they were able to gain buy-in from various departments across the organization using data models and data standards.
Data Architecture Strategies Webinar: Emerging Trends in Data Architecture – ...DATAVERSITY
A robust data architecture is at the core what’s driving today’s innovative, data-driven organizations. From AI to machine learning to Big Data – a strong data architecture is needed in order to be successful, and core fundamentals such as data quality, metadata management, and efficient data storage are more critical than ever.
With the vast array of new technologies available to support these trends, how do you make sense of it all? Our panel of experts will offer their perspectives on how the latest trends in data architecture can support your organization’s data-driven goals.
Data Governance and Data Science to Improve Data QualityDATAVERSITY
Data Science uses systematic methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Data Science requires high-quality data that is trusted by the organization and data scientists. Many organizations focus their Data Governance programs on improving Data Quality results. These three concepts (governance, science, and quality) seem to be made for each other.
In this RWDG webinar, Bob Seiner and his special guest will discuss how the people focusing on Data Governance and Data Science must work together to improve the level of confidence the organization has in its most critical data assets. Heavy investments are being made in Data Science but not so much for Data Governance. Bob will talk about how Data Governance and Data Science must work together to improve Data Quality.
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
Slides: The Automated Business GlossaryDATAVERSITY
You can’t do business without being able to successfully extract insights from your organization’s data supply chain. You need a strong foundation for visibility and control of data. Flying by the seat of your pants, when it comes to analyzing your market, your performance, and your competitors’ performances, just doesn’t work.
In this webinar, we’ll examine the real-life daily struggles and frustrations plaguing the data supply chain and discuss how these struggles can be eliminated by automation of metadata operations such as data lineage, data discovery and business glossary.
When you attend this webinar, you will learn about:
• What data consumers are really spending their time on and why they are so frustrated
• The challenges of building a business glossary
• How to get started with an automated business glossary and why it’s critical for BI intelligence
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.
Data Architecture Strategies: Building an Enterprise Data Strategy – Where to...DATAVERSITY
The majority of successful organizations in today’s economy are data-driven, and innovative companies are looking at new ways to leverage data and information for strategic advantage. While the opportunities are vast, and the value has clearly been shown across a number of industries in using data to strategic advantage, the choices in technology can be overwhelming. From Big Data to Artificial Intelligence to Data Lakes and Warehouses, the industry is continually evolving to provide new and exciting technological solutions.
This webinar will help make sense of the various data architectures & technologies available, and how to leverage them for business value and success. A practical framework will be provided to generate “quick wins” for your organization, while at the same time building towards a longer-term sustainable architecture. Case studies will also be provided to show how successful organizations have successfully built a data strategies to support their business goals.
Join us as we launch our 2015 webinar series, ‘Metadata Matters’, with Martin Garland, President of Concept Searching, and expert guest speaker Doug Miles, Director of Market Intelligence at AIIM, as they explore the state of the market for unstructured content. Find out what your peers are doing, what’s on the horizon, and how other organizations are tackling and solving many of the same metadata challenges that you face.
Unstructured data is both a liability and an opportunity. With the uncontrollable rate of unstructured content growth, organizations are beginning to realize that the time has come to proactively manage content from inception to disposal. The real problem that disruptively impacts the management of unstructured data is metadata. This informative webinar will discuss the factors that prevent and enable organizations to leverage metadata to improve the bottom line.
Topics to be discussed include:
• Are organizations living with or fixing the problem of metadata, and what is Business Critical Metadata?
• What are the biggest challenges your peers are facing in applications such as enterprise search, records management, security, migration, content management, collaboration, social tagging, and text analytics?
• Has the cloud become a debilitating factor when managing metadata?
• How is Microsoft changing the role of SharePoint, and what’s the impact of Office 365, OneDrive for Business, and Delve in managing content as an integrated enterprise asset?
• What are sound strategies that successful organizations use?
• Why adding structure and application functionality with metadata assists in identifying and achieving business value
• When evaluating vendors and tools, what are some of the questions you should ask?
• Hear case studies on how organizations have solved their challenges from an enterprise and a departmental level
ADV Slides: Strategies for Fitting a Data Lake 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 2019.
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 “horses to courses,” and keep up users’ confidence in the Data Platforms.
As for platform, although Hadoop received the early majority of Data Lakes, organizations are now weighing in that the Data Lake will be built in Cloud object storage. We’ll discuss these options as well.
Get this data point for your Data Lake journey.
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
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.
Data-Ed Online: Unlock Business Value through Document & Content ManagementDATAVERSITY
Organizations must realize what it means to utilize document and content management in support of business strategy. The volume of unstructured data is growing at an enormous pace. While we are still far away from automated content comprehension, increasingly sophisticated technologies are extending our business and data management capabilities into more critical and regulated areas. This presentation provides you with an understanding of the dimensions of these new developments, including electronic and physical document monitoring, storage systems, content analysis and archive, retrieve and purge cycling.
Learning objectives include:
What is Document & Content Management and why is it important?
Planning and Implementing Document & Content Management
Document/Record Management Lifecycle
Levels of Control
Content management building blocks
Guiding principles & best practices
Understanding foundational document & content management concepts based on the Data Management Body of Knowledge (DMBOK)
How to utilize document & content management in support of business strategy
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.
Building an Effective Data & Analytics Operating Model A Data Modernization G...Mark Hewitt
This is the age of analytics—information resulting from the systematic analysis of data.
Insights gained from applying data and analytics to business allows large and small organizations across diverse industries—be it healthcare, retail, manufacturing, financial, or others—to identify new opportunities, improve core processes, enable continuous learning and differentiation, remain competitive, and thrive in an increasingly challenging business environment.
The key to building a data-driven practice is a Data and Analytics Operating Model (D&AOM) which enables the organization to establish standards for data governance, controls for data flows (both within and outside the organization), and adoption of appropriate technological innovations.
Success measures of a data initiative may include:
• Creating a competitive advantage by fulfilling unmet needs,
• Driving adoption and engagement of the digital experience platform (DXP),
• Delivering industry standard data and metrics, and
• Reducing the lift on service teams.
This green paper lays out the framework for building and customizing an effective data and analytics operating model.
ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...DATAVERSITY
Thirty years is a long time for a technology foundation to be as active as relational databases. Are their replacements here?
In this webinar, we look at this foundational technology for modern Data Management and show how it evolved to meet the workloads of today, as well as when other platforms make sense for enterprise data.
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?
DAS Slides: Metadata Management From Technical Architecture & Business Techni...DATAVERSITY
Metadata provides context for the “who, what, when, where, and why” of data, and is of critical interest in today’s data-driven business environment. Since metadata is created and used by both business and IT, architectural and organizational techniques need to encompass a holistic approach across the organization to address all audiences. This webinar provides practical ways to manage metadata in your organization using both technical architecture and business techniques.
Data Architecture Best Practices for Today’s Rapidly Changing Data LandscapeDATAVERSITY
With the rise of the data-driven organization, the pace of innovation in data-centric technologies has been tremendous. New tools and techniques are emerging at an exponential rate, and it is difficult to keep track of the array of technological choices available to today’s data management professional.
At the same time, core fundamentals such as data quality and metadata management remain critical in order for organizations to obtain true business value from their data. This webinar will help demystify the options available: from data lake to data warehouse, to graph database, to NoSQL, and more, and how to integrate these new technologies with core architectural fundamentals that will help your organization benefit from the quick wins that are possible from these exciting technologies, while at the same time build a longer-term sustainable architecture that will support the inevitable change that will continue in the industry.
The last year has put a new lens on what speed to insights actually mean - day-old data became useless, and only in-the-moment-insights became relevant, pushing data and analytics teams to their breaking point. The results, everyone has fast forwarded in their transformation and modernization plans, and it's also made us look differently at dashboards and the type of information that we're getting the business. Join this live event and hear about the data teams ditching their dashboards to embrace modern cloud analytics.
Most organizations need to awaken to a sobering reality: their data maturity level is much lower than they realize. Organizational maturity is a journey requiring a balanced focus on both data and business process, with checkpoints along the way to ensure you’re on the right path. Ron Huizenga will discuss a continuous improvement approach that balances data and process alignment to achieve breakthrough results for data architecture and governance, using the Data Maturity Model as a benchmark.
Market / Competitive Intelligence Usage and AllocationIgnacio Feller
Market & Competitive Intelligence Usage and Allocation: Best practices in creating a communication and governance framework to ensure actionable intelligence across varied internal stakeholder groups - including executives, marketing, sales, product management, and investor relations - within complex organizations competing in rapidly changing markets.
Data Governance and Data Science to Improve Data QualityDATAVERSITY
Data Science uses systematic methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Data Science requires high-quality data that is trusted by the organization and data scientists. Many organizations focus their Data Governance programs on improving Data Quality results. These three concepts (governance, science, and quality) seem to be made for each other.
In this RWDG webinar, Bob Seiner and his special guest will discuss how the people focusing on Data Governance and Data Science must work together to improve the level of confidence the organization has in its most critical data assets. Heavy investments are being made in Data Science but not so much for Data Governance. Bob will talk about how Data Governance and Data Science must work together to improve Data Quality.
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
Slides: The Automated Business GlossaryDATAVERSITY
You can’t do business without being able to successfully extract insights from your organization’s data supply chain. You need a strong foundation for visibility and control of data. Flying by the seat of your pants, when it comes to analyzing your market, your performance, and your competitors’ performances, just doesn’t work.
In this webinar, we’ll examine the real-life daily struggles and frustrations plaguing the data supply chain and discuss how these struggles can be eliminated by automation of metadata operations such as data lineage, data discovery and business glossary.
When you attend this webinar, you will learn about:
• What data consumers are really spending their time on and why they are so frustrated
• The challenges of building a business glossary
• How to get started with an automated business glossary and why it’s critical for BI intelligence
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.
Data Architecture Strategies: Building an Enterprise Data Strategy – Where to...DATAVERSITY
The majority of successful organizations in today’s economy are data-driven, and innovative companies are looking at new ways to leverage data and information for strategic advantage. While the opportunities are vast, and the value has clearly been shown across a number of industries in using data to strategic advantage, the choices in technology can be overwhelming. From Big Data to Artificial Intelligence to Data Lakes and Warehouses, the industry is continually evolving to provide new and exciting technological solutions.
This webinar will help make sense of the various data architectures & technologies available, and how to leverage them for business value and success. A practical framework will be provided to generate “quick wins” for your organization, while at the same time building towards a longer-term sustainable architecture. Case studies will also be provided to show how successful organizations have successfully built a data strategies to support their business goals.
Join us as we launch our 2015 webinar series, ‘Metadata Matters’, with Martin Garland, President of Concept Searching, and expert guest speaker Doug Miles, Director of Market Intelligence at AIIM, as they explore the state of the market for unstructured content. Find out what your peers are doing, what’s on the horizon, and how other organizations are tackling and solving many of the same metadata challenges that you face.
Unstructured data is both a liability and an opportunity. With the uncontrollable rate of unstructured content growth, organizations are beginning to realize that the time has come to proactively manage content from inception to disposal. The real problem that disruptively impacts the management of unstructured data is metadata. This informative webinar will discuss the factors that prevent and enable organizations to leverage metadata to improve the bottom line.
Topics to be discussed include:
• Are organizations living with or fixing the problem of metadata, and what is Business Critical Metadata?
• What are the biggest challenges your peers are facing in applications such as enterprise search, records management, security, migration, content management, collaboration, social tagging, and text analytics?
• Has the cloud become a debilitating factor when managing metadata?
• How is Microsoft changing the role of SharePoint, and what’s the impact of Office 365, OneDrive for Business, and Delve in managing content as an integrated enterprise asset?
• What are sound strategies that successful organizations use?
• Why adding structure and application functionality with metadata assists in identifying and achieving business value
• When evaluating vendors and tools, what are some of the questions you should ask?
• Hear case studies on how organizations have solved their challenges from an enterprise and a departmental level
ADV Slides: Strategies for Fitting a Data Lake 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 2019.
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 “horses to courses,” and keep up users’ confidence in the Data Platforms.
As for platform, although Hadoop received the early majority of Data Lakes, organizations are now weighing in that the Data Lake will be built in Cloud object storage. We’ll discuss these options as well.
Get this data point for your Data Lake journey.
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
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.
Data-Ed Online: Unlock Business Value through Document & Content ManagementDATAVERSITY
Organizations must realize what it means to utilize document and content management in support of business strategy. The volume of unstructured data is growing at an enormous pace. While we are still far away from automated content comprehension, increasingly sophisticated technologies are extending our business and data management capabilities into more critical and regulated areas. This presentation provides you with an understanding of the dimensions of these new developments, including electronic and physical document monitoring, storage systems, content analysis and archive, retrieve and purge cycling.
Learning objectives include:
What is Document & Content Management and why is it important?
Planning and Implementing Document & Content Management
Document/Record Management Lifecycle
Levels of Control
Content management building blocks
Guiding principles & best practices
Understanding foundational document & content management concepts based on the Data Management Body of Knowledge (DMBOK)
How to utilize document & content management in support of business strategy
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.
Building an Effective Data & Analytics Operating Model A Data Modernization G...Mark Hewitt
This is the age of analytics—information resulting from the systematic analysis of data.
Insights gained from applying data and analytics to business allows large and small organizations across diverse industries—be it healthcare, retail, manufacturing, financial, or others—to identify new opportunities, improve core processes, enable continuous learning and differentiation, remain competitive, and thrive in an increasingly challenging business environment.
The key to building a data-driven practice is a Data and Analytics Operating Model (D&AOM) which enables the organization to establish standards for data governance, controls for data flows (both within and outside the organization), and adoption of appropriate technological innovations.
Success measures of a data initiative may include:
• Creating a competitive advantage by fulfilling unmet needs,
• Driving adoption and engagement of the digital experience platform (DXP),
• Delivering industry standard data and metrics, and
• Reducing the lift on service teams.
This green paper lays out the framework for building and customizing an effective data and analytics operating model.
ADV Slides: The Evolution of the Data Platform and What It Means to Enterpris...DATAVERSITY
Thirty years is a long time for a technology foundation to be as active as relational databases. Are their replacements here?
In this webinar, we look at this foundational technology for modern Data Management and show how it evolved to meet the workloads of today, as well as when other platforms make sense for enterprise data.
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?
DAS Slides: Metadata Management From Technical Architecture & Business Techni...DATAVERSITY
Metadata provides context for the “who, what, when, where, and why” of data, and is of critical interest in today’s data-driven business environment. Since metadata is created and used by both business and IT, architectural and organizational techniques need to encompass a holistic approach across the organization to address all audiences. This webinar provides practical ways to manage metadata in your organization using both technical architecture and business techniques.
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Optimizing Organizational Knowledge With Project Cortex & The Microsoft Digit...Richard Harbridge
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Based on significant improvements in artificial intelligence (AI), real behavior-based data based on the Microsoft Graph and Azure innovation such as improved language understanding, organizations today can provide contextual and dynamic topic cards, expertise mapping, pages, topic centers, and more. Powered by image tagging, form processing, document understanding, and machine teaching; organization content and documents are optimized for better compliance, processing, and discovery.
Join LiveTiles, along with Richard Harbridge, a Microsoft MVP and internationally recognized expert on Microsoft 365 and the Digital Workplace, who will share:
Best practices on modern knowledge management
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Speaker: Venkatesh Umaashankar
LinkedIn: https://www.linkedin.com/in/venkateshumaashankar/
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Why does a DS team need Full Stack Developer?
Who should lead the DS Team
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Evolution Of Airbnb’s DS Team
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Apple’s Acqui-hiring Strategy to build DS team
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The 14th Text Analytics Summit - June 15, 2015 in New York
Today, Businesses around the world are increasingly collecting tremendous amount of unstructured data in the form of text – from multiple channels such as product reviews, market research, customer care conversations, and social media. In this talk, we will share how LinkedIn has built a text-mining platform to derive insights and create value for our members from the massive amount of data we have within our ecosystem. We will cover the following topics in our talk:
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The talk will be appropriate for business leaders, researchers and practitioners.
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How to Create Controlled Vocabularies for Competitive Intelligence
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How to Create Controlled
Vocabularies for
Competitive Intelligence
A Complimentary Webinar from Aurora WDC
12:00 Noon Eastern /// Wednesday 18 March 2015
~ featuring ~
Justin Soles Michel BernaicheLisa Coady
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and dedicated to exploring how to apply intelligence methods to solve real-
world business problems.
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Justin Soles
Justin Soles is an experienced CI analyst (and sometimes CI programmer,
instructor and evangelist), as well as a seasoned knowledge taxonomist and
information architect. Justin’s CI-related work has included patent and IP analysis,
competitor profiling/tracking and dashboard development for senior
management, among other projects. During his Masters in Library & Information
Studies at McGill University, Justin participated in the consolidation of several
Astronomy vocabularies into a single thesaurus along with experts from Harvard
University, the Smithsonian, the University of Edinburgh and various prestigious
scientific journal publishers.
Lisa Coady
Lisa Coady has 10+ years as a strategic development officer in the non-profit
sector. Having recently completed a Masters in Library & Information
Studies, she is setting up an information management consultancy
specializing in developing controlled vocabularies, taxonomies and thesaurii
to drive and enhance CI efforts in both commercial and non-profit
organizations.
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Questions, Commentary & Content
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Agenda
► What is a Controlled Vocabulary (CV)?
► What’s the connection between CVs and CI?
► How do I create a CV for CI?
► What are some best practices/lessons
learned?
► Summary, Q&A and Discussion
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What is a Controlled Vocabulary?
► Some formal definitions:
► OECD: “…an established list of standardized
terminology for use in indexing and retrieval of
information.”
► Getty Institute: “…an organized arrangement of words
and phrases used to index content and/or to retrieve
content through browsing or searching.”
► SCIP: “… a standardized – yet dynamic – set of terms
and phrases authorized for use in an indexing system to
describe a subject area or Information domain.” (Vernon Prior)
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What does a CV look like?
List: Ungrouped set of
terms
Pepsi Subsidiaries:
- Tropicana Products, Inc.
- Frito Lay, Inc.
- Quaker Oats Ltd.
- The Gatorade Company
- Stokely Van-Camp, Ltd.
- Walkers Snack Foods Ltd.
- Green Hemlock
International, LLC
Hierarchy: Grouped set of
terms
Vehicles
► Land Vehicles
► 1-wheel vehicles
► Unicycle
► 2-wheel vehicles
► Bicycle
► Motorcycle
► 4-wheel vehicles
► Car
► Sports car
► Sedan
► SUV
► School bus
► Quad bike
► > 4 wheel vehicles
► Intercity bus
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What does a CV look like?
List: Ungrouped set of
terms
Pepsi Subsidiaries:
- Tropicana Products, Inc.
- Frito Lay, Inc.
- Quaker Oats Ltd.
- The Gatorade Company
- Stokely Van-Camp, Ltd.
- Walkers Snack Foods Ltd.
- Green Hemlock
International, LLC
Common types of lists used
in CVs:
►Glossary/Lexicon:
List of domain-related
terms, usually with
definitions & usage
►Name Authority File:
List of approved names
for a related set of
objects
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What does a CV look like?
Common types of
hierarchies used in CVs:
► Taxonomy: Hierarchy
showing the relationships
between terms
► Thesaurus: Taxonomy
with added context
(e.g. synonyms, preferred
terms, non-preferred
terms, scope notes)
Hierarchy: Grouped set of
terms
Vehicles
► Land Vehicles
► 1-wheel vehicles
► Unicycle
► 2-wheel vehicles
► Bicycle
► Motorcycle
► 4-wheel vehicles
► Car
► Sports car
► Sedan
► SUV
► School bus
► Quad bike
► > 4 wheel vehicles
► Intercity bus
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What kinds of (CI-related) information can you
organize with a CV?
Use a CV based on: To classify by/into: Example:
Document Type Document type of artifact
(beyond file type, date, etc.)
Type: Job Advertisement
Type: Press Release
Organizational Entity Publishing organization,
company, department, etc.
Entity: Human Resources
Entity: Marketing
Functional Process Process/Function to which
an artifact relates
Process: Staffing
Process: Promotion
Subject-based Subject area to which an
artifact pertains
Subject: Data Science
Subject: Donation to
University
Facet-based Different hierarchies, each
of which describes a
different aspect or piece of
information
Facet: Job Title - Data
Scientist, Skills – Hadoop, R
Languages – Python, PHP
Facet: Donation type -
Educational, Amount - $1M
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Where can CVs be used?
Back End: index & organize
- (Metadata) Tagging
- Textual analysis
- Document indexing
- Search engine
enhancement (result set
expansion via synonyms)
- Semantic/Contextual
understanding
(Ontology)
Front End: orient & inform
- Portal/Site organization &
navigation (Information
Architecture)
- Search engine
enhancement (auto-
complete, faceted search)
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How Controlled Vocabularies help the
Competitive Intelligence Cycle
1. Establish a common
terminology framework
for KITs/KIQs
2a. Identify search
keywords
2b. Organize &
store search
results consistently
3a. Improve
artifact findability
4. Enhance impact
of CI deliverable
5. Improve
findability of
deliverables
3b. Facilitate
comparisons &
correlations
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How to develop a Controlled Vocabulary
for CI?
Preliminary
Activities
Discover
BuildTest
Maintain
Define scope,
resources, budget
& timeline
Identify
sources &
collect terms
Create CV
(Some assembly
required)
Test CV
(Some reassembly
required!)
Add, edit &
retire terms
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Role of the Analyst
► Today’s solutions are successful in accessing business and
competitive data, and making it available to users, however,
.....today’s solutions are not so successful in directly linking
information to action, and deriving its corresponding value.
Dr. Craig Fleisher, presenting at SCIP African Summit Workshop @ UNISA
https://www.scip.org/re_pdfs/1415891934_pdf_SCIPAfricanSummitAnalysisMethodsWorkshpSessionSlidesbyDrCraigFleisherOct14.pdf
-------------------------------------------------------------------------------------------
The effective analyst bridges the gap between information and intelligence. (CF).
Controlled Vocabulary one of the analyst’s most valuable tools. In assigning data to
categories based on its attributes, you can make meaningful comparisons and draw
meaningful inferences within and about your domain (LC).
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How will we shape our Corporate
Social Responsibility strategy for
maximum effectiveness?
Scenario:
Using controlled vocabulary to drive a Corporate
Social Responsibility Analysis for a fuel extraction company
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Task: CSR assessment
► Task: perform a CSR assessment competitors
► Data-gathering
► Data analysis
► Development of a CSR framework for the company
► Assumptions:
► Distributed team
► (>1 person gathering, tagging, analyzing)
► Ongoing strategic priority (environment monitoring)
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►What is CSR?
► Corporate Social Responsibility (CSR) refers to voluntary activities undertaken by a
company to operate in an economic, social and environmentally sustainable manner.
( http://goo.gl/bTskh4 Foreign Affairs, Trade and Development Canada)
► Philanthropic or in-kind donations to social sectors, institutions, groups, causes
► Business Case
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Our “categorize to analyze” process
► Building a CV for business analyses is a data-
driven process
► Fundamental questions
► Collect sample data
► Scan and group according to shared attributes that
you assign through formal categorization
“categorize to analyze”
► Insights
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1. Fundamental questions
Scope
Analysis
► Who, what, where, when?
► KIQs
► Priority investment areas?
(where competitors are making CSR investments)
► Optimal funding mechanisms?
► Strategically aligned?
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2. Collect your data
Corp. Donor Recipient Year Amount CSR ”Instance" CSR Event Description
Company A XXX 2011 515,001 Lorem ipsum Name Lorem Ipsum Descripsum
Company A XXX 2011 1,000,000 Lorem ipsum Name Lorem Ipsum Descripsum
Company A XXX 2012 120,000 Lorem ipsum Name Lorem Ipsum Descripsum
Company A XXX 2013 475,975 Lorem ipsum Name Lorem Ipsum Descripsum
Company B XXX 2011 112,000 Lorem ipsum Name Lorem Ipsum Descripsum
Company B XXX 2013 1,000,000 Remote Medicine Technology for the
Medical School of University 2
Company B gives a one-time donation of $1M towards the
purchase of state-of-the-art medical visualization systems for the
medical school in University2. The donation is part of Company B's
commitment to support the training of the next generation of
health professionals, in the community in which it operates
Company B XXX 2010 2,100,000 Lorem ipsum Name Lorem Ipsum Descripsum
Company C XXX 2012 774,136 Lorem ipsum Name Lorem Ipsum Descripsum
Company C XXX 2014 1,200,000 Lorem ipsum Name Lorem Ipsum Descripsum
Company C XXX 2011 800,000 Lorem ipsum Name Lorem Ipsum Descripsum
Company C XXX 2012 50,000 Lorem ipsum Name Lorem Ipsum Descripsum
Company C XXX 2013 135,000 Lorem ipsum Name Lorem Ipsum Descripsum
Company C XXX 2011 2,000,000 Lorem ipsum Name Lorem Ipsum Descripsum
CSR DATA - TELLS US
WHAT?
Reflects our scope
It’s a faceted taxonomy;
We can group on attributes and
make discoveries, just not many.
The data is largely unstructured.
CSR DATA –
DERIVED FROM WHERE?
CSR records found in
sustainability reports; filings of
corporate charitable foundations;
donor and recipient websites
Sample of N=420 CSR data points from X fuel companies in North America over past 4 yrs.
And compile
DOESN’T YET
ANSWER MY KIQs
(Where are my
competitors are investing
in CSR)
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3. Do your CV work
Corp. Donor Year Amount CSR "Event" Funding Mechanism Investment Area Strat Alignment?
Company A 2011 515,001 Lorem ipsum Name
Company A 2011 1,000,000 Lorem ipsum Name
Company A 2012 120,000 Lorem ipsum Name
Company A 2013 475,975 Lorem ipsum Name
Company B 2011 112,000 Lorem ipsum Name
Company B 2013 1,000,000 Remote Medicine Technology for the
Medical School of University 2
Company B 2010 2,100,000 Lorem ipsum Name
Company C 2012 774,136 Lorem ipsum Name
Company C 2014 1,200,000 Lorem ipsum Name
Company C 2011 800,000 Lorem ipsum Name
Company C 2012 50,000 Lorem ipsum Name
Company C 2013 135,000 Lorem ipsum Name
Company C 2011 2,000,000 Lorem ipsum Name
INVESTMENT AREA?
FUNDING MECH?
ALIGNMENT?
Analysis
Formalize KIQs as facets
Begin developing CVs for facets
CV Terms? CV Terms? CV Terms?
Corp. Donor Year Amount CSR "Event" Funding Mechanism Investment Area Strat Alignment?
Company A 2011 515,001 Lorem ipsum Name Research Partnership Education/Innovation Yes
Company A 2011 1,000,000 Lorem ipsum Name Donation Community Development/Social Justice No
Company A 2012 120,000 Lorem ipsum Name In-Kind Contribution Community Development/Social Justice Yes
Company A 2013 475,975 Lorem ipsum Name Donation Environment/Preservation No
Company B 2011 112,000 Lorem ipsum Name Employee Matching Health/Foundation Support No
Company B 2013 1,000,000 Remote Medicine Technology for the
Medical School of University 2
Research Partnership Education/Innovation Yes
Company B 2010 2,100,000 Lorem ipsum Name In-Kind Contribution Education/Innovation Yes
Company C 2012 774,136 Lorem ipsum Name Donation Health/Special Projects No
Company C 2014 1,200,000 Lorem ipsum Name Donation Health/Scholarhips No
Company C 2011 800,000 Lorem ipsum Name Employee Matching No
Company C 2012 50,000 Lorem ipsum Name Research Partnership Environment/Awareness Yes
Company C 2013 135,000 Lorem ipsum Name Employee Matching Environment/Preservation Yes
Company C 2011 2,000,000 Lorem ipsum Name Donation Environment/Innovation Yes
Enhanced filtering, increased granularity,
combinatorial power!
A series of attribute lists including one
hierarchy
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Vocabulary challenge?
►Must always design with
end-user’s perceptions
and language in mind
►Finding the balance in
representing your
domain using structure,
vocab and clear
definitions
► Ensuring oversight and
change mgmt.
Definition reveals the challenges
A controlled vocabulary is a collection of
terms that are:
Accepted: The term adheres to
community practices and reflects
community understanding
Defined: Vocabulary is adequate to cover
the domain. The terms are precisely
characterized with definitions. Imperative
for user understanding and for analytic
rigour.
Managed: A body of experts will create
and maintain the controlled vocabulary,
including: periodic review, modification of
terms and quality assurance.
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Sometimes it seems “simple”
Make no assumptions!
• About language, perspective or understanding of scope
• Provide a dictionary where the scope and meaning of
each term can be found (link)
“Simple” attribute?
• The specific attribute you are describing with your CV is
shallow (flat list)
• Limited #terms, widely understood and used
Funding Mechanism
Philanthropic Donation
Matching Funds
In-Kind
Research Partnership
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Often, it’s more complex
Structural Considerations
consider the golden rules of IA (use hierarchy, limit the
number of options per level, bear granularity in mind)
Investment Area
Investment Area is a more complex facet
How should we represent it
Vocabulary Considerations
consult subject matter experts (domain language?)
do a “physical build” of your taxonomy (card sorting)
draft a preliminary taxo
Test with end users (sorting, web taxo, observation)
Expect that it will be a long and iterative process
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Build, test and tweak (facet, investment area)
Education
Scholarships
Education Foundation Support
Special Projects
Innovation
Health
Health Training Scholarships
Health Foundation Support
Special Projects
Innovation
Disaster Relief
National
International
Environment
Awareness
Preservation
Innovation
Community Development
Economic Development
Social Justice
Social Innovation
Arts, Culture and Leisure
Food and Agriculture
Safety
Scenario A:
Company E gives a one-time donation of $1.5 M to buy
state-of-the-art medical visualization systems for the
medical school in University2.
What top-level term? Clarify your rules
Scenario B:
Company D includes supplies fuel for more than 180
emergency response vehicles in the local community where
it is headquartered.
Where? New term?
Investment Area
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Don’t look for the “right” term, seek
consensus and shared understanding
► With that, you have the power of efficient
organization, enhanced retrieval and the ability
to derive insights from your data
► In our case study, this may include insights that
can be compiled in a CSR dashboard:
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Corporate CSR, by year and IA
0
2000000
4000000
6000000
8000000
10000000
12000000
14000000
2010 2011 2012 2013 2014 2015
CSR Allocation by Year and Investment Area
Community Development Culture, Arts and Leisure Education Environment Health Safety
I want to look at this only for
companies in my province. Filter
by location
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Who spends most?
0
2000000
4000000
6000000
8000000
10000000
12000000
Company A Company B Company C Company D Company E Company F Company G Company H
Total CSR Expenditure by Corporation
Total
I want to see the yearly trend.
Combine with year facet.
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Strategic Alignment
No
40%
Yes
60%
Is CSR Strategically Aligned?
I want to see if strategic
alignment varies over
investment area.
Combine.
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Thank you! Now how about a little Q&A?
Email: justin.soles@mail.mcgill.ca
The Intelligence Collaborative is the online learning and networking
community powered by Aurora WDC, our clients, partners and other friends
and dedicated to exploring how to apply intelligence methods to solve real-
world business problems.
Apply for a free 30-day trial membership at http://IntelCollab.com or learn
more about Aurora at http://AuroraWDC.com – see you next time!
Justin Soles
Lisa Coady
Email: lisa.coady@mail.mcgill.ca