Data is now not only considered as an Asset for Competitive Advantage; but now a Strategic Asset for Competitive Survival. ..
The Chief Data Officer will lead the transformation of the Business Data Environment to enable DataOps. . .
Leveraging DataOps will enable the timely creation of “Data Products” for the Enterprise. .
Today's Chief Data Officer: 3 Types of CDOs, Key Challenges, and Opportunitie...Scott Richardson
In this presentation we examine the 3 types of Chief Data Officers that are common in the industry today. We discuss their responsibilities, key challenges, and present ideas for having an meaningful impact. A great overview of the CDO role and how this executive position can contribute to the success of your business.
Chief Data Officer: Overcoming Data Silos for True Business ValueCraig Milroy
Existing data silos are commonly viewed as a technology problem due to architecture, software, and hardware problems; however this problem cannot be solved by technology alone. Business engagement and support in conjunction with an enterprise approach for data availability, data sharing, and data usage are required to address the proliferation of data silos within an organization.
Data silos are created out of necessity to solve specific business problems in absence of formal enterprise architecture, data handling policies, data governance and other data-centric oversight challenges within an organization.
Customer, marketing, compliance, risk, finance and other corporate functions generate volumes of overlapping data, often with minimal consideration or understanding of tomorrow’s data volume growth.
Business’ that understand the opportunities within concepts such as Internet of Things, mobile, location, context, as well as the introduction of other unstructured open data sets, have an ability to create a competitive advantage within their target market.
These businesses are building out the office of the Chief Data Officer (CDO) to enable an effective business technology response.
Data Architecture Strategies: Data Architecture for Digital TransformationDATAVERSITY
MDM, data quality, data architecture, and more. At the same time, combining these foundational data management approaches with other innovative techniques can help drive organizational change as well as technological transformation. This webinar will provide practical steps for creating a data foundation for effective digital transformation.
Activate Data Governance Using the Data CatalogDATAVERSITY
Data Governance programs depend on the activation of data stewards that are held formally accountable for how they manage data. The data catalog is a critical tool to enable your stewards to contribute and interact with an inventory of metadata about the data definition, production, and usage. This interaction is active Data Governance in the truest sense of the word.
In this RWDG webinar, Bob Seiner will share tips and techniques focused on activating your data stewards through a data catalog. Data Governance programs that involve stewards in daily activities are more likely to demonstrate value from their data-intensive investments.
Bob will address the following in this webinar:
- A comparison of active and passive Data Governance
- What it means to have an active Data Governance program
- How a data catalog tool can be used to activate data stewards
- The role a data catalog plays in Data Governance
- The metadata in the data catalog will not govern itself
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace, from digital transformation to marketing, customer centricity, population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
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.
Today's Chief Data Officer: 3 Types of CDOs, Key Challenges, and Opportunitie...Scott Richardson
In this presentation we examine the 3 types of Chief Data Officers that are common in the industry today. We discuss their responsibilities, key challenges, and present ideas for having an meaningful impact. A great overview of the CDO role and how this executive position can contribute to the success of your business.
Chief Data Officer: Overcoming Data Silos for True Business ValueCraig Milroy
Existing data silos are commonly viewed as a technology problem due to architecture, software, and hardware problems; however this problem cannot be solved by technology alone. Business engagement and support in conjunction with an enterprise approach for data availability, data sharing, and data usage are required to address the proliferation of data silos within an organization.
Data silos are created out of necessity to solve specific business problems in absence of formal enterprise architecture, data handling policies, data governance and other data-centric oversight challenges within an organization.
Customer, marketing, compliance, risk, finance and other corporate functions generate volumes of overlapping data, often with minimal consideration or understanding of tomorrow’s data volume growth.
Business’ that understand the opportunities within concepts such as Internet of Things, mobile, location, context, as well as the introduction of other unstructured open data sets, have an ability to create a competitive advantage within their target market.
These businesses are building out the office of the Chief Data Officer (CDO) to enable an effective business technology response.
Data Architecture Strategies: Data Architecture for Digital TransformationDATAVERSITY
MDM, data quality, data architecture, and more. At the same time, combining these foundational data management approaches with other innovative techniques can help drive organizational change as well as technological transformation. This webinar will provide practical steps for creating a data foundation for effective digital transformation.
Activate Data Governance Using the Data CatalogDATAVERSITY
Data Governance programs depend on the activation of data stewards that are held formally accountable for how they manage data. The data catalog is a critical tool to enable your stewards to contribute and interact with an inventory of metadata about the data definition, production, and usage. This interaction is active Data Governance in the truest sense of the word.
In this RWDG webinar, Bob Seiner will share tips and techniques focused on activating your data stewards through a data catalog. Data Governance programs that involve stewards in daily activities are more likely to demonstrate value from their data-intensive investments.
Bob will address the following in this webinar:
- A comparison of active and passive Data Governance
- What it means to have an active Data Governance program
- How a data catalog tool can be used to activate data stewards
- The role a data catalog plays in Data Governance
- The metadata in the data catalog will not govern itself
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace, from digital transformation to marketing, customer centricity, population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
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.
Building a Data Strategy Your C-Suite Will SupportReid Colson
Being a data leader in any industry is an advantage that creates measurable financial benefits. Many studies have shown this – I’ve seen them from Bain, McKinsey, MIT and more. Since most firms are measured on profit, getting good at making data driven decisions is a key to being competitive. You can't get there without a plan. That is where a data strategy comes in.
In speaking with ~300 firms who indicated that their organizations were effective in using data and analytics, McKinsey found that construction of a data strategy was the number one contributing factor to their success. Being good at using data to drive decisions creates a meaningful profit advantage and those who are leaders indicated that the number one driver of their success was their data strategy.
This presentation will cover what a data strategy is, how to construct one, and how to get buy in from your executive team. The author is a former Fortune 500 Chief Data Officer and has held senior data roles at Capital One and Markel.
Here are a few helpful links for your data journey:
Free Data Investment ROI Template:
https://www.udig.com/digging-in/roi-calculator-for-it-projects/
Real world data use cases:
https://www.udig.com/our-work/?category=data
Contact Me:
https://www.udig.com/contact/
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.
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.
Business Intelligence & Data Analytics– An Architected ApproachDATAVERSITY
Business intelligence (BI) and data analytics are increasing in popularity as more organizations are looking to become more data-driven. Many tools have powerful visualization techniques that can create dynamic displays of critical information. To ensure that the data displayed on these visualizations is accurate and timely, a strong Data Architecture is needed. Join this webinar to understand how to create a robust Data Architecture for BI and data analytics that takes both business and technology needs into consideration.
Improving Data Literacy Around Data ArchitectureDATAVERSITY
Data Literacy is an increasing concern, as organizations look to become more data-driven. As the rise of the citizen data scientist and self-service data analytics becomes increasingly common, the need for business users to understand core Data Management fundamentals is more important than ever. At the same time, technical roles need a strong foundation in Data Architecture principles and best practices. Join this webinar to understand the key components of Data Literacy, and practical ways to implement a Data Literacy program in your organization.
Data Mesh in Practice: How Europe’s Leading Online Platform for Fashion Goes ...Databricks
The Data Lake paradigm is often considered the scalable successor of the more curated Data Warehouse approach when it comes to democratization of data. However, many who went out to build a centralized Data Lake came out with a data swamp of unclear responsibilities, a lack of data ownership, and sub-par data availability.
Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
Digital Transformation is a top priority for many organizations, and a successful digital journey requires a strong data foundation. Creating this digital transformation requires a number of core data management capabilities such as MDM, 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.
Recommended for CDOs and all Data & Analytics Managers
The past 2 years have had a huge impact on organizations journeys to become data driven. Existing data architectures were disrupted; rigid structures and processes were questioned, and many data strategies were re-written.
On the one hand, the global pandemic emphasized the need for organizations to raise the bar, implement strategies, improve data literacy and culture, increase investments in data and analytics, and explore AI opportunities.
On the other, it also presented new challenges such as: the war for data talent and the wide literacy gap. Inadequate structures as well as outdated processes were exposed. Major changes in the data landscape (Data Fabric, Data Mesh, Transition to Data Clouds) will further disrupt existing data architectures and enhance the need for a new adaptive architecture and organization.
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...DATAVERSITY
A solid data architecture is critical to the success of any data initiative. But what is meant by “data architecture”? Throughout the industry, there are many different “flavors” of data architecture, each with its own unique value and use cases for describing key aspects of the data landscape. Join this webinar to demystify the various architecture styles and understand how they can add value to your organization.
Enabling a Data Mesh Architecture with Data VirtualizationDenodo
Watch full webinar here: https://bit.ly/3rwWhyv
The Data Mesh architectural design was first proposed in 2019 by Zhamak Dehghani, principal technology consultant at Thoughtworks, a technology company that is closely associated with the development of distributed agile methodology. A data mesh is a distributed, de-centralized data infrastructure in which multiple autonomous domains manage and expose their own data, called “data products,” to the rest of the organization.
Organizations leverage data mesh architecture when they experience shortcomings in highly centralized architectures, such as the lack domain-specific expertise in data teams, the inflexibility of centralized data repositories in meeting the specific needs of different departments within large organizations, and the slow nature of centralized data infrastructures in provisioning data and responding to changes.
In this session, Pablo Alvarez, Global Director of Product Management at Denodo, explains how data virtualization is your best bet for implementing an effective data mesh architecture.
You will learn:
- How data mesh architecture not only enables better performance and agility, but also self-service data access
- The requirements for “data products” in the data mesh world, and how data virtualization supports them
- How data virtualization enables domains in a data mesh to be truly autonomous
- Why a data lake is not automatically a data mesh
- How to implement a simple, functional data mesh architecture using data virtualization
This introduction to data governance presentation covers the inter-related DM foundational disciplines (Data Integration / DWH, Business Intelligence and Data Governance). Some of the pitfalls and success factors for data governance.
• IM Foundational Disciplines
• Cross-functional Workflow Exchange
• Key Objectives of the Data Governance Framework
• Components of a Data Governance Framework
• Key Roles in Data Governance
• Data Governance Committee (DGC)
• 4 Data Governance Policy Areas
• 3 Challenges to Implementing Data Governance
• Data Governance Success Factors
Analytics play a critical role in supporting strategic business initiatives. Despite the obvious value to analytic professionals of providing the analytics for these initiatives, many executives question the economic return of analytics as well as data lakes, machine learning, master data management, and the like.
Technology professionals need to calculate and present business value in terms business executives can understand. Unfortunately, most IT professionals lack the knowledge required to develop comprehensive cost-benefit analyses and return on investment (ROI) measurements.
This session provides a framework to help technology professionals research, measure, and present the economic value of a proposed or existing analytics initiative, no matter the form that the business benefit arises. The session will provide practical advice about how to calculate ROI and the formulas, and how to collect the necessary information.
Presentation on Data Mesh: The paradigm shift is a new type of eco-system architecture, which is a shift left towards a modern distributed architecture in which it allows domain-specific data and views “data-as-a-product,” enabling each domain to handle its own data pipelines.
Chief Data Officer (CDO) Organization RolesDave Getty
If your Company wants to treat Data as an Asset, it needs a Chief Data Officer to initiate significant changes in the Roles and Responsibilities of the Data Governance, IT Data Management and Business Analyst Data Scientist organizations. This presentation describes how the resulting organizations might look and behave.
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: 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 from digital transformation, to marketing, to customer centricity, population health, and more. This webinar will help de-mystify data strategy and data architecture and will provide concrete, practical ways to get started.
How to Build & Sustain a Data Governance Operating Model DATUM LLC
Learn how to execute a data governance strategy through creation of a successful business case and operating model.
Originally presented to an audience of 400+ at the Master Data Management & Data Governance Summit.
Visit www.datumstrategy.com for more!
To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...Jochem van Grondelle
Recently the concept of a ‘data mesh’ was introduced by Zhamak Deghani to solve architectural and organizational challenges with getting value from data at scale more logically and efficiently, built around four principles:
* Domain-oriented decentralized data ownership
* Data as a product
* Self-serve data infrastructure as a platform
* Federated computational governance
This presentation will initially deep-dive into the ‘data mesh’ and how it fundamentally differs from the typical data lake architectures used today. Subsequently, it describes OLX Europe’s current data platform state aimed partially towards a more decentralized data architecture, covering its analytical data platform, data infrastructure, data discovery, and data privacy.
Finally, it will see to what extent the main principles around the ‘data mesh’ can be applied to a future vision for our data platform and what advantages and challenges implementing such a vision can bring for OLX and other companies.
For more information on data mesh principles, check out the original article by Zhamak: https://martinfowler.com/articles/data-mesh-principles.html.
My Robot Can Learn -Using Reinforcement Learning to Teach my RobotRising Media Ltd.
Nowadays, everybody is following the hype around machine learning in general and around deep learning (DL), in particular. We are trying to use it for predicting unexpected down-times of machines, or to discover anomalies in data streams observing machines. What is usually missing is the magic. Most often DL is supervised, which means that someone is labelling some data which gets fed into some algorithm. But as an alternative, there is a new star at the horizon: Reinforcement Learning (RL). This is a concept using an agent and an incentive system to train an agent. By taking the incentives the agent can learn and improve his behavior. As a result, this is a self-learning system and only requires some simple rules. The combination of RL and DL eventually takes us to something we could consider as artificial intelligence. With AlphaGo we have seen how the combination of RL and DL can win a Go tournament. This is a very promising step in an interesting direction. This talk will provide an introduction into reinforcement learning. It shows how reinforcement learning and deep learning can be combined towards an AI system by providing some insights into existing projects. Starting with annotated data and using DL, it is possible to create a base model. This model gets refined with RL mechanisms. Finally, this talk will show how this approaches can be used to map it to Internet of Things and Industry 4.0 scenarios, such as a self-learning robot.
Building a Data Strategy Your C-Suite Will SupportReid Colson
Being a data leader in any industry is an advantage that creates measurable financial benefits. Many studies have shown this – I’ve seen them from Bain, McKinsey, MIT and more. Since most firms are measured on profit, getting good at making data driven decisions is a key to being competitive. You can't get there without a plan. That is where a data strategy comes in.
In speaking with ~300 firms who indicated that their organizations were effective in using data and analytics, McKinsey found that construction of a data strategy was the number one contributing factor to their success. Being good at using data to drive decisions creates a meaningful profit advantage and those who are leaders indicated that the number one driver of their success was their data strategy.
This presentation will cover what a data strategy is, how to construct one, and how to get buy in from your executive team. The author is a former Fortune 500 Chief Data Officer and has held senior data roles at Capital One and Markel.
Here are a few helpful links for your data journey:
Free Data Investment ROI Template:
https://www.udig.com/digging-in/roi-calculator-for-it-projects/
Real world data use cases:
https://www.udig.com/our-work/?category=data
Contact Me:
https://www.udig.com/contact/
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.
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.
Business Intelligence & Data Analytics– An Architected ApproachDATAVERSITY
Business intelligence (BI) and data analytics are increasing in popularity as more organizations are looking to become more data-driven. Many tools have powerful visualization techniques that can create dynamic displays of critical information. To ensure that the data displayed on these visualizations is accurate and timely, a strong Data Architecture is needed. Join this webinar to understand how to create a robust Data Architecture for BI and data analytics that takes both business and technology needs into consideration.
Improving Data Literacy Around Data ArchitectureDATAVERSITY
Data Literacy is an increasing concern, as organizations look to become more data-driven. As the rise of the citizen data scientist and self-service data analytics becomes increasingly common, the need for business users to understand core Data Management fundamentals is more important than ever. At the same time, technical roles need a strong foundation in Data Architecture principles and best practices. Join this webinar to understand the key components of Data Literacy, and practical ways to implement a Data Literacy program in your organization.
Data Mesh in Practice: How Europe’s Leading Online Platform for Fashion Goes ...Databricks
The Data Lake paradigm is often considered the scalable successor of the more curated Data Warehouse approach when it comes to democratization of data. However, many who went out to build a centralized Data Lake came out with a data swamp of unclear responsibilities, a lack of data ownership, and sub-par data availability.
Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
Digital Transformation is a top priority for many organizations, and a successful digital journey requires a strong data foundation. Creating this digital transformation requires a number of core data management capabilities such as MDM, 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.
Recommended for CDOs and all Data & Analytics Managers
The past 2 years have had a huge impact on organizations journeys to become data driven. Existing data architectures were disrupted; rigid structures and processes were questioned, and many data strategies were re-written.
On the one hand, the global pandemic emphasized the need for organizations to raise the bar, implement strategies, improve data literacy and culture, increase investments in data and analytics, and explore AI opportunities.
On the other, it also presented new challenges such as: the war for data talent and the wide literacy gap. Inadequate structures as well as outdated processes were exposed. Major changes in the data landscape (Data Fabric, Data Mesh, Transition to Data Clouds) will further disrupt existing data architectures and enhance the need for a new adaptive architecture and organization.
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...DATAVERSITY
A solid data architecture is critical to the success of any data initiative. But what is meant by “data architecture”? Throughout the industry, there are many different “flavors” of data architecture, each with its own unique value and use cases for describing key aspects of the data landscape. Join this webinar to demystify the various architecture styles and understand how they can add value to your organization.
Enabling a Data Mesh Architecture with Data VirtualizationDenodo
Watch full webinar here: https://bit.ly/3rwWhyv
The Data Mesh architectural design was first proposed in 2019 by Zhamak Dehghani, principal technology consultant at Thoughtworks, a technology company that is closely associated with the development of distributed agile methodology. A data mesh is a distributed, de-centralized data infrastructure in which multiple autonomous domains manage and expose their own data, called “data products,” to the rest of the organization.
Organizations leverage data mesh architecture when they experience shortcomings in highly centralized architectures, such as the lack domain-specific expertise in data teams, the inflexibility of centralized data repositories in meeting the specific needs of different departments within large organizations, and the slow nature of centralized data infrastructures in provisioning data and responding to changes.
In this session, Pablo Alvarez, Global Director of Product Management at Denodo, explains how data virtualization is your best bet for implementing an effective data mesh architecture.
You will learn:
- How data mesh architecture not only enables better performance and agility, but also self-service data access
- The requirements for “data products” in the data mesh world, and how data virtualization supports them
- How data virtualization enables domains in a data mesh to be truly autonomous
- Why a data lake is not automatically a data mesh
- How to implement a simple, functional data mesh architecture using data virtualization
This introduction to data governance presentation covers the inter-related DM foundational disciplines (Data Integration / DWH, Business Intelligence and Data Governance). Some of the pitfalls and success factors for data governance.
• IM Foundational Disciplines
• Cross-functional Workflow Exchange
• Key Objectives of the Data Governance Framework
• Components of a Data Governance Framework
• Key Roles in Data Governance
• Data Governance Committee (DGC)
• 4 Data Governance Policy Areas
• 3 Challenges to Implementing Data Governance
• Data Governance Success Factors
Analytics play a critical role in supporting strategic business initiatives. Despite the obvious value to analytic professionals of providing the analytics for these initiatives, many executives question the economic return of analytics as well as data lakes, machine learning, master data management, and the like.
Technology professionals need to calculate and present business value in terms business executives can understand. Unfortunately, most IT professionals lack the knowledge required to develop comprehensive cost-benefit analyses and return on investment (ROI) measurements.
This session provides a framework to help technology professionals research, measure, and present the economic value of a proposed or existing analytics initiative, no matter the form that the business benefit arises. The session will provide practical advice about how to calculate ROI and the formulas, and how to collect the necessary information.
Presentation on Data Mesh: The paradigm shift is a new type of eco-system architecture, which is a shift left towards a modern distributed architecture in which it allows domain-specific data and views “data-as-a-product,” enabling each domain to handle its own data pipelines.
Chief Data Officer (CDO) Organization RolesDave Getty
If your Company wants to treat Data as an Asset, it needs a Chief Data Officer to initiate significant changes in the Roles and Responsibilities of the Data Governance, IT Data Management and Business Analyst Data Scientist organizations. This presentation describes how the resulting organizations might look and behave.
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: 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 from digital transformation, to marketing, to customer centricity, population health, and more. This webinar will help de-mystify data strategy and data architecture and will provide concrete, practical ways to get started.
How to Build & Sustain a Data Governance Operating Model DATUM LLC
Learn how to execute a data governance strategy through creation of a successful business case and operating model.
Originally presented to an audience of 400+ at the Master Data Management & Data Governance Summit.
Visit www.datumstrategy.com for more!
To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...Jochem van Grondelle
Recently the concept of a ‘data mesh’ was introduced by Zhamak Deghani to solve architectural and organizational challenges with getting value from data at scale more logically and efficiently, built around four principles:
* Domain-oriented decentralized data ownership
* Data as a product
* Self-serve data infrastructure as a platform
* Federated computational governance
This presentation will initially deep-dive into the ‘data mesh’ and how it fundamentally differs from the typical data lake architectures used today. Subsequently, it describes OLX Europe’s current data platform state aimed partially towards a more decentralized data architecture, covering its analytical data platform, data infrastructure, data discovery, and data privacy.
Finally, it will see to what extent the main principles around the ‘data mesh’ can be applied to a future vision for our data platform and what advantages and challenges implementing such a vision can bring for OLX and other companies.
For more information on data mesh principles, check out the original article by Zhamak: https://martinfowler.com/articles/data-mesh-principles.html.
My Robot Can Learn -Using Reinforcement Learning to Teach my RobotRising Media Ltd.
Nowadays, everybody is following the hype around machine learning in general and around deep learning (DL), in particular. We are trying to use it for predicting unexpected down-times of machines, or to discover anomalies in data streams observing machines. What is usually missing is the magic. Most often DL is supervised, which means that someone is labelling some data which gets fed into some algorithm. But as an alternative, there is a new star at the horizon: Reinforcement Learning (RL). This is a concept using an agent and an incentive system to train an agent. By taking the incentives the agent can learn and improve his behavior. As a result, this is a self-learning system and only requires some simple rules. The combination of RL and DL eventually takes us to something we could consider as artificial intelligence. With AlphaGo we have seen how the combination of RL and DL can win a Go tournament. This is a very promising step in an interesting direction. This talk will provide an introduction into reinforcement learning. It shows how reinforcement learning and deep learning can be combined towards an AI system by providing some insights into existing projects. Starting with annotated data and using DL, it is possible to create a base model. This model gets refined with RL mechanisms. Finally, this talk will show how this approaches can be used to map it to Internet of Things and Industry 4.0 scenarios, such as a self-learning robot.
Predictive Analytics World for Business Germany 2017Rising Media Ltd.
Predictive Analytics World for Business is the leading provider of independent specialized conferences in applied predictive analytics. Users, decision makers and experts in predictive analytics will meet in Berlin in order to discover the latest findings and progress, to exchange among specialists and in person and to be inspired by the success stories.
Cloud Native Computing Foundation (CNCF) is founded for a microservice based new computing paradigm. Fujitsu joined CNCF since last December expecting to establish a new open standard platform. In this session, we'd like to share idea behind our participation and technical topics we're now investigating.
This presentation was delivered at LinuxCon Japan 2016 by Hiroyuki Kamezawa and Wolfgang Ries.
Predictive Analytics World for Business Deutschland 2017Rising Media Ltd.
Die Predictive Analytics World for Business ist die führende anbieter-unabhängige Fachkonferenz für anwendungsorientierte Predictive Analytics. Anwender, Entscheider und Experten von Predictive Analytics treffen sich am 13 bis 14. November in Berlin, um sich über die neuesten Erkenntnisse und Fortschritte zu informieren, sich untereinander fachlich und persönlich auszutauschen und sich von den Erfolgen inspirieren zu lassen.
The Chief Data Officer and the Organizational JourneyCraig Milroy
The Chief Data Officer and the Organizational Journey.
Where does the role of the Chief Data Officer start and how does the role evolve within the organization as business value is realized.
Artificial Intelligence (AI) services on the AWS cloud bring deep learning (DL) technologies like natural language understanding (NLU), automatic speech recognition (ASR), image recognition and computer vision (CV), text-to-speech (TTS), and machine learning (ML) within reach of every developer. In this session, you will be introduced to several new AI services: Amazon Lex, to build sophisticated text and voice chatbots; Amazon Rekognition, for deep learning-based image recognition; and Amazon Polly, for turning text into lifelike speech. The opportunities to apply one or more of these DL services are nearly boundless and this session will provide a number of examples and use cases to help you get started.
Industrial Analytics and Predictive Maintenance 2017 - 2022Rising Media Ltd.
In this session we will present the results of two recent, international studies on the state of data analytics in industrial settings. You will get insights from an in-depth industry survey of 151 analytics professionals and decision-makers in industrial companies, providing a deep-dive into strategies, project types, cost structures and skill-demand in IoT-based analytics. In addition we will present a survey focusing on predictive analytics covering the market potential and expected development until 2022.
IoT and AI Services in Healthcare | AWS Public Sector Summit 2017Amazon Web Services
In this session we will overview the latest AWS Artificial Intelligence (AI) and Internet of Things (IoT) services and show examples of how these services are enabling transformative new capabilities in health care. Join us in exploring various architectures and discussing the art of the possible in how AI and IoT services can be applied in different scenarios. Listen to the inspiring story of how one AWS-savvy father is using Amazon Polly, Lex, and IoT buttons to create a verbal assistant for his autistic son. We’ll also hear how the American Heart Association is leveraging Amazon Alexa and Lex chat bots as part of a new initiative to engage communities and individuals through innovative new feature offerings. Learn More: https://aws.amazon.com/government-education/
Brutally, "at the edge of crime", simplified overview of the Wardley Maps technique integrated with Lean Startup and Strategic Domain-Driven Design. Presented at A2B Accelerator, Jerusalem on April 20 2017.
Alignment: Office of the Chief Data Officer & BCBS 239Craig Milroy
Alignment: Office of the Chief Data Officer & BCBS 239. Alignment overview between OCDO framework and Principles for Effective Risk Data Aggregation and Risk Reporting.
Slides: Empowering Data Consumers to Deliver Business ValueDATAVERSITY
Today, the role of Chief Data Officers and their teams has expanded from risk and compliance-based activities to delivering business value through trusted data. With the exponential growth in data and data consumers throughout an organization, ensuring that everyone gets the information that they need — and that it can be relied upon — is no small feat. CDOs need to rely on modern Data Governance leaders to discover where all of the data lives, define the context, measure the quality, ensure privacy, and then democratize data to empower the rest of the organization. Join us for this informative webinar as we highlight the challenges of today’s data leaders, how they can democratize trusted, secure data, and ultimately discover how to deliver business value.
5 Reasons Why Unified Marketing is Not a MythTealium
We explain the historic challenges of data integration and integrated marketing and how market trends and technology advancements have made it possible to to achieve a unified view of the customer and highly orchestrated marketing interactions.
Decentralizing Analytics - A Strategy for Organizing Effective Analytics TeamsKen Raetz
Building an Organization for Functional Analytics
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Many organizations are struggling to figure out how to move ahead with strategic use of data and insights to grow their business. A solid Analytics Strategy seems to elude them. Should they focus on a modern data warehouse in the cloud? Do they have “Big Data”? What about reporting and self-service analytics? How do they deliver information to their customers and suppliers? Which tools are right for them?
In this presentation, Ken Raetz will address each of these concerns, outlining a simple, yet functional strategy to building a team and growing the use of analytics in their organization. You will learn:
1. Why centralizing analytics in IT doesn’t work.
2. The roles IT and business play in analytics
3. Selecting tools and processes for analytics
4. Building highly functional teams
5. Partnering with outside vendors to augment team and accelerate early work
6. Analytics Adoption – How to ensure the strategy of analytics continues forward in the years to come
Data Insights and Analytics Webinar: CDO vs. CAO - What’s the Difference?DATAVERSITY
At one time, there were well-stated distinctions between the Chief Data Officer and Chief Analytics Officer roles. But not today. In some organizations, this role confusion actually causes serious concerns.
John and Kelle will revisit the definitions, suggest where lack of clarity first began, and discuss how best to manage the role distinctions going forward.
This webinar will address:
Differences in the CAO and CDO roles
CDOs who aren’t responsible for all organizational data
Why role clarity matters
Organizational success without one or both roles
Curated an great dialogue with the AITP San Diego organization in May 2015 on the importance of DevOps to all organizations taking the Digital Enterprise journey.
Arthur C. Nielsen, the founder of ACNielsen said, “The price of light is less than the cost of darkness.” This is becoming even more important in the day and age of IoT devices and ubiquitous internet connectivity. The amount of data that is at the fingertips of our companies’ decision makers is colossal. Yet very few business leaders and their direct teams can analyze their data by themselves to uncover insights that will improve our products and services to delight their customers and grow their business.
With the rise of low-code/no-code tools, cloud infrastructure, and the convergence of AI and BI, the democratization of analytics can accelerate the time to answer a question while improving its relevancy.
In this presentation, we will cover the 12 critical capabilities to succeed in enabling self-service analytics and augmenting data literacy across the enterprise.
Breakthrough experiments in data science: Practical lessons for successAmanda Sirianni
Leading firms are integrating data science capabilities within their organizations to capture the untapped potential of data science as a source for competitive advantage. Yet, many enterprises are challenged to successfully integrate these capabilities for sustained value and to measure its worth for the organization. This analytics study conducted by the IBM Center for Applied Insights uses practical advice from those seeing the benefits to establish a proven success formula for integrating a data science capability within your organization.
To learn more: www.ibm.com/ibmcai/data-science
Using Google Cloud for Marketing Analytics: How the7stars, the UK’s largest i...Matillion
the7Stars, the leading UK Digital Marketing agency, has global clients ranging from Nintendo to Suzuki to Iceland. With growing data volumes, the7Stars faced the challenge of centralizing all their customers’ marketing data for quick and easy analysis.
In this joint webinar, you will hear about how the7Stars are using Google BigQuery as their data warehouse collating data from many different sources, allowing them to grow their business and attract new customers. the7Stars is also using Matillion ETL to combine the data from different sources and load it all into BigQuery enabling agile and responsive market analysis giving their clients a competitive edge, while saving time and money.
In this webinar learn:
- the7Stars’ data journey for maximizing value
- Google BigQuery, BigQuery Data Transfer Service and best practices for marketing analytics
- How to collect data from different sources and streamline transformations and queries in Google BigQuery with Matillion ETL
- Benefits being actualized by 7 Stars, such as saving time/money and growing their customer base
Watch the full webinar: https://youtu.be/8VEHf_wAXao
Teaching organizations to fish in a data-rich future: Stories from data leadersAmanda Sirianni
Many organizations are still early in their journey to set up and optimize their analytics function and related capabilities. However, those that are investing in highly skilled data leaders are seeing the business benefits. To learn more, the IBM Center for Applied Insights spoke with some of these leaders.
Through their stories, we discovered the analytics challenges that businesses face across industries and sectors, and how today’s data leaders confront and eventually overcome those challenges. See how these leaders were able to deliver outcomes that far outweighed their early struggles. To learn more: www.ibm.com/ibmcai/cdostudy
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
Integrating CA Project & Portfolio Management (CA PPM) to an agile management application is a growing need throughout the PPM community. Whether you are using Rally, Version One or, even, Jira, the needs are the same: to gain a unified perspective on resources, projects and budgets. Attendees in this course will learn about CA PPM agile integrations and how to gain visibility across the organization.
For more information, please visit http://cainc.to/Nv2VOe
Similar to Chief Data Officer: DataOps - Transformation of the Business Data Environment (20)
DRAFT: Extend Industry Well-Architected Frameworks to focus on Data and business outcomes. Addition of Data to the cloud framework will resolve fragmented approaches that customers are struggling with respect to data placement within various cloud providers.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
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During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar