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In our series on The Yosemite Project, we explore RDF as a data standard for health data. In this installment, we will hear from Rafael Richards, Physician Informatician, Office of Informatics and Analytics in the Veterans Health Administration (VHA), about “Transformations for Integrating VA data with FHIR in RDF.” The VistA EHR has its own data model and vocabularies for representing healthcare data. This webinar describes how SPARQL Inference Notation (SPIN) can be used to translate VistA data to the data represented used by FHIR, an emerging interchange standard.
Yosemite Project - Part 3 - Transformations for Integrating VA data with FHIR...
Yosemite Project - Part 3 - Transformations for Integrating VA data with FHIR...
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In our series on The Yosemite Project, we explore RDF as a data standard for health data. In this presentation, we will discuss with Claude Nanjo, a Software Architect at Cognitive Medical Systems, ways to expose clinical knowledge as OWL and RDF resources on the Web in order to promote greater convergence in the representation of health knowledge in the longer term. We will also explore how one might rally and coordinate the community to seed the Web with a core set of high-value resources and technologies that could greatly enhance health interoperability.
Yosemite part-4 webinar-final
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Our speaker, Joshua Mandel, will provide a lightning tour of Fast Healthcare Interoperability Resources (FHIR), an emerging clinical data standard, with a focus on its resource-oriented approach, and a discussion of how FHIR intersects with the Semantic Web. We'll look at how FHIR represents links between entities; how FHIR represents concepts from standards-based vocabularies; and how a set of FHIR instance data can be represented in RDF.
Introduction-and-RDF-Representation-of-FHIR-for-Clinical-Data
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How do you accelerate data warehousing to meet the demands of the data-driven economy? Semantic technology provides an agile platform to bring data together, focus on data that matters and ultimately derive a target data model that can be easily extended. This webinar will present a semantically-based data federation case study and highlight the semantic components that facilitate agile data federation in the enterprise.
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In this presentation, our speaker, Dr. Michel Dumontier, will explore the use of Semantic Web technologies to reduce the overwhelming burden of integrating clinical data with public biomedical data, and enabling a new generation of translational research and their clinical application.
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Let’s face it, developing and implementing an Enterprise Data Governance program can be very frustrating. Issues can pop up quite unexpectedly. Support ebbs and flows for seemingly illogical reasons. And, acceptance and adoption seem to be hit or miss. So, how can practitioners ensure their program will be as successful as possible? This webinar is designed to help practitioners understand the Four Critical Success Factors necessary for developing and sustaining an effective Data Governance program, as identified by Joy Medved based on her 20+ years as an international data consultant. Joy will provide an overview of the Four Critical Success Factors, as well as share Common Program Barriers she has experienced that lead to success breakdown. Joy will also help practitioners learn how to identify if one or more of these critical success factors is plaguing your program, and which barriers might be at fault. Rounding out the topic, Joy will share her Key Program Components, designed to help ensure successful Data Governance development and implementation. Some of the topics discussed in this webinar include: The Four Critical Success Factors for developing and implementing a DG program Common Program Barriers that may be hampering your ability to drive a successful program How to identify which barriers might be plaguing your program efforts Key Program Components to help ensure a successful DG program
Enterprise Data World: Data Governance - The Four Critical Success Factors
Enterprise Data World: Data Governance - The Four Critical Success Factors
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Data architecture is foundational to an information-based operational environment. Without proper structure and efficiency in organization, data assets cannot be utilized to their full potential, which in turn harms bottom-line business value. When designed well and used effectively, however, a strong data architecture can be referenced to inform, clarify, understand, and resolve aspects of a variety of business problems commonly encountered in organizations. The goal of this webinar is not to instruct you in being an outright data architect, but rather to enable you to envision a number of uses for data architectures that will maximize your organization’s competitive advantage. With that being said, we will: - Discuss data architecture’s guiding principles and best practices - Demonstrate how to utilize data architecture to address a broad variety of organizational challenges and support your overall business strategy - Illustrate how best to understand foundational data architecture concepts based on the DAMA International Guide to Data Management Body of Knowledge (DAMA DMBOK)
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In our series on The Yosemite Project, we explore RDF as a data standard for health data. In this installment, we will hear from Rafael Richards, Physician Informatician, Office of Informatics and Analytics in the Veterans Health Administration (VHA), about “Transformations for Integrating VA data with FHIR in RDF.” The VistA EHR has its own data model and vocabularies for representing healthcare data. This webinar describes how SPARQL Inference Notation (SPIN) can be used to translate VistA data to the data represented used by FHIR, an emerging interchange standard.
Yosemite Project - Part 3 - Transformations for Integrating VA data with FHIR...
Yosemite Project - Part 3 - Transformations for Integrating VA data with FHIR...
DATAVERSITY
In our series on The Yosemite Project, we explore RDF as a data standard for health data. In this presentation, we will discuss with Claude Nanjo, a Software Architect at Cognitive Medical Systems, ways to expose clinical knowledge as OWL and RDF resources on the Web in order to promote greater convergence in the representation of health knowledge in the longer term. We will also explore how one might rally and coordinate the community to seed the Web with a core set of high-value resources and technologies that could greatly enhance health interoperability.
Yosemite part-4 webinar-final
Yosemite part-4 webinar-final
DATAVERSITY
Our speaker, Joshua Mandel, will provide a lightning tour of Fast Healthcare Interoperability Resources (FHIR), an emerging clinical data standard, with a focus on its resource-oriented approach, and a discussion of how FHIR intersects with the Semantic Web. We'll look at how FHIR represents links between entities; how FHIR represents concepts from standards-based vocabularies; and how a set of FHIR instance data can be represented in RDF.
Introduction-and-RDF-Representation-of-FHIR-for-Clinical-Data
Introduction-and-RDF-Representation-of-FHIR-for-Clinical-Data
DATAVERSITY
How do you accelerate data warehousing to meet the demands of the data-driven economy? Semantic technology provides an agile platform to bring data together, focus on data that matters and ultimately derive a target data model that can be easily extended. This webinar will present a semantically-based data federation case study and highlight the semantic components that facilitate agile data federation in the enterprise.
Using Semantic Technology to Drive Agile Analytics - SLIDES
Using Semantic Technology to Drive Agile Analytics - SLIDES
DATAVERSITY
In this presentation, our speaker, Dr. Michel Dumontier, will explore the use of Semantic Web technologies to reduce the overwhelming burden of integrating clinical data with public biomedical data, and enabling a new generation of translational research and their clinical application.
WEBINAR: The Yosemite Project PART 6 -- Data-Driven Biomedical Research with ...
WEBINAR: The Yosemite Project PART 6 -- Data-Driven Biomedical Research with ...
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Let’s face it, developing and implementing an Enterprise Data Governance program can be very frustrating. Issues can pop up quite unexpectedly. Support ebbs and flows for seemingly illogical reasons. And, acceptance and adoption seem to be hit or miss. So, how can practitioners ensure their program will be as successful as possible? This webinar is designed to help practitioners understand the Four Critical Success Factors necessary for developing and sustaining an effective Data Governance program, as identified by Joy Medved based on her 20+ years as an international data consultant. Joy will provide an overview of the Four Critical Success Factors, as well as share Common Program Barriers she has experienced that lead to success breakdown. Joy will also help practitioners learn how to identify if one or more of these critical success factors is plaguing your program, and which barriers might be at fault. Rounding out the topic, Joy will share her Key Program Components, designed to help ensure successful Data Governance development and implementation. Some of the topics discussed in this webinar include: The Four Critical Success Factors for developing and implementing a DG program Common Program Barriers that may be hampering your ability to drive a successful program How to identify which barriers might be plaguing your program efforts Key Program Components to help ensure a successful DG program
Enterprise Data World: Data Governance - The Four Critical Success Factors
Enterprise Data World: Data Governance - The Four Critical Success Factors
DATAVERSITY
Data architecture is foundational to an information-based operational environment. Without proper structure and efficiency in organization, data assets cannot be utilized to their full potential, which in turn harms bottom-line business value. When designed well and used effectively, however, a strong data architecture can be referenced to inform, clarify, understand, and resolve aspects of a variety of business problems commonly encountered in organizations. The goal of this webinar is not to instruct you in being an outright data architect, but rather to enable you to envision a number of uses for data architectures that will maximize your organization’s competitive advantage. With that being said, we will: - Discuss data architecture’s guiding principles and best practices - Demonstrate how to utilize data architecture to address a broad variety of organizational challenges and support your overall business strategy - Illustrate how best to understand foundational data architecture concepts based on the DAMA International Guide to Data Management Body of Knowledge (DAMA DMBOK)
Data-Ed Slides: Data Architecture Strategies - Constructing Your Data Garden
Data-Ed Slides: Data Architecture Strategies - Constructing Your Data Garden
DATAVERSITY
Non-Invasive Data Governance is summarized as the practice of formalizing accountability for data and the application of governance to process. Non-Invasive Data Governance describes how data governance is applied to the organization rather than being forced into the environment. A NIDG framework will be introduced in this webinar. In this month’s installment of the RWDG webinar series, Bob Seiner will present a new data governance framework that addresses the core components of data governance for each level of the organization. The resulting framework can be used for all approaches to data governance. In this webinar Bob will discuss: - The five core components of a data governance effort - The five levels where the core components will be addressed - Detailed explanation of each component for each level - A diagram to complete the framework for your organization - A framework comparison across approaches
RWDG Webinar: The New Non-Invasive Data Governance Framework
RWDG Webinar: The New Non-Invasive Data Governance Framework
DATAVERSITY
Having trouble making your information management (IM)/data governance (DG) changes stick? How many times have you gone through this process? Successful data governance means changes to your information management culture. Changing that culture means that you are asking people to think and behave differently about how data is created, accessed and used. If the results are to be sustainable, successful IM/DG change requires an organized and systematic way to manage those changes. In preparation for their EDW15 tutorial, Kelle O’Neal and Pam Thomas will discuss the most significant obstacles to successful IM/DG change, and the key factors to working through those obstacles to achieve business benefit.
EDW Webinar: Managing Change for Successful Data Governance
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How to get your MDM program up & running” This session will deliver a Master Data Management primer to introduce: Master vs Reference data Multi vs Single domain MDM solutions A MDM reference architecture and MDM implementation architectures This will be illustrated with a real world example from describing how to identify & justify the appropriate data subjects areas that are right for mastering and how to align an MDM initiative with in-flight business initiatives and make the business case.
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Google “citizen data scientist” today and you will see about 1M results. That number is data. It may be interesting, but it is meaningless without context. Sometimes it appears that we are drowning in data from systems and sensors but starving for insights. We definitely produce more of the former than the latter, which has created demand for more powerful tools to simplify the process and lower the skills requirement for analysis. As vendors build systems to meet this demand, we hear about the coming ”democratization” of big data as more people at varying levels within organizations are empowered to find meaning and improve their own performance with data-driven insights. This is a good thing, but it does require caution. To paraphrase Col Jessup in A Few Good Men: You want answers? You can’t handle the data. In this webinar, we will survey emerging approaches to simplifying analysis, and discuss the benefits, dangers, and skills required for individuals and organizations to thrive in the brave new world of analytics everywhere, for everyone.
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Having trouble making your information management (IM)/data governance (DG) changes stick? How many times have you gone through this process? Successful data governance means changes to your information management culture. Changing that culture means that you are asking people to think and behave differently about how data is created, accessed and used. If the results are to be sustainable, successful IM/DG change requires an organized and systematic way to manage those changes. In preparation for their EDW15 tutorial, Kelle O’Neal and Pam Thomas will discuss the most significant obstacles to successful IM/DG change, and the key factors to working through those obstacles to achieve business benefit.
EDW Webinar: Managing Change for Successful Data Governance
EDW Webinar: Managing Change for Successful Data Governance
DATAVERSITY
How to get your MDM program up & running” This session will deliver a Master Data Management primer to introduce: Master vs Reference data Multi vs Single domain MDM solutions A MDM reference architecture and MDM implementation architectures This will be illustrated with a real world example from describing how to identify & justify the appropriate data subjects areas that are right for mastering and how to align an MDM initiative with in-flight business initiatives and make the business case.
Enterprise Data World Webinar: How to Get Your MDM Program Up & Running
Enterprise Data World Webinar: How to Get Your MDM Program Up & Running
DATAVERSITY
Artificial General Intelligence (AGI) - or strong AI - refers to a domain-independent, machine-based system that approaches or exceeds human performance on any and all cognitive tasks. Estimates for the arrival of true AGI solutions range from last week (as in, we have one!) to decades, to infinity and beyond. As the general study of cybernetic systems and modern AI and cognitive computing capture the imagination of civic and business leaders, and fans of science fiction, it is important to be able to distinguish between progress and smoke & mirrors. This webinar will present an overview of approaches to AGI, examples of promising research and commercial AGI activities, and show participants how to critically evaluate academic and vendor claims.
Smart Data Webinar: Artificial General Intelligence - When Can I Get It?
Smart Data Webinar: Artificial General Intelligence - When Can I Get It?
DATAVERSITY
Business Intelligence (BI) is a valuable way to use information to show the overall health and performance of the organization. At its core is quality, well-structured data that allows for successful reporting and analytics. A data model helps provide both the business definitions as well as the structural optimization needed for successful BI implementations. Join this webinar to see how a data model underpins business intelligence and analytics in today’s organization.
LDM Webinar: Data Modeling & Business Intelligence
LDM Webinar: Data Modeling & Business Intelligence
DATAVERSITY
Developing and implementing a master record and reference data through a best practice approach and lessons learned for your organization’s data business needs. The ability to leverage the immense data available across an organization has become paramount for continued growth and success. Companies need accessible and reliable information to make more informed and effective business decisions across channels while continuing to provide quality service to their customers. Many companies recognize the need to develop a Master Data Program, as part of an overall Data Strategy initiative, to consistently manage the quality, data interoperability, accessibility, and availability of core data (e.g., customer, product). Determining where to start, finding business opportunities, defining what master data management means in your organization, and addressing the cultural and political realities are all critical to make your master data program successful and valuable. This seminar will present real world approaches used for successfully implementing a Master Data Domain and program from several organization cases including Walgreens.
Enterprise Data World Webinar: Mastering & Referencing Data for the Enterprise
Enterprise Data World Webinar: Mastering & Referencing Data for the Enterprise
DATAVERSITY
Analysts in the line of business deal with a myriad of time-consuming data preparation and analytic challenges that often require IT or DBA intervention to deliver a requested dataset. Others have taught themselves “enough SQL to be dangerous”, learning the necessary code to extract the data needed to answer their business question. Self-service data analytics empowers these business analysts to take control of the entire analytics process, delivering the necessary results for better business decisions. Join us to learn how self-service data analytics allows analysts to: - Utilize a drag-and-drop workflow for data and analytic processes without writing code - Minimize data movement and ensure data integrity through in-database capabilities - Easily work across relational and non-relational databases to deliver faster business results Self-service data analytics delivers a repeatable process that is transparent to not only business analysts, but also SQL coders and decision makers across the organization.
Focus on Your Analysis, Not Your SQL Code
Focus on Your Analysis, Not Your SQL Code
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Interoperability of electronic healthcare information remains an enormous challenge in spite of 100+ available healthcare information standards. This webinar explains the Yosemite Project, whose mission is to achieve semantic interoperability of all structured healthcare information through RDF as a common semantic foundation. It explains the rationale and technical strategy of the Yosemite Project, and describes how RDF and related standards address a two-pronged strategy for semantic interoperability: facilitating collaborative standards convergence whenever possible, and crowd-sourced data translations when necessary.
WEBINAR: The Yosemite Project: An RDF Roadmap for Healthcare Information Inte...
WEBINAR: The Yosemite Project: An RDF Roadmap for Healthcare Information Inte...
DATAVERSITY
Data analysis can be divided into descriptive, prescriptive and predictive analytics. Descriptive analytics aims to help uncover valuable insight from the data being analyzed. Prescriptive analytics suggests conclusions or actions that may be taken based on the analysis. Predictive analytics focuses on the application of statistical models to help forecast the behavior of people and markets. This webinar will compare and contrast these different data analysis activities and cover: - Statistical Analysis – forming a hypothesis, identifying appropriate sources and proving / disproving the hypothesis - Descriptive Data Analytics – finding patterns - Predictive Analytics – creating models of behavior - Prescriptive Analytics – acting on insight - How the analytic environment differs for each
DI&A Slides: Descriptive, Prescriptive, and Predictive Analytics
DI&A Slides: Descriptive, Prescriptive, and Predictive Analytics
DATAVERSITY
Google “citizen data scientist” today and you will see about 1M results. That number is data. It may be interesting, but it is meaningless without context. Sometimes it appears that we are drowning in data from systems and sensors but starving for insights. We definitely produce more of the former than the latter, which has created demand for more powerful tools to simplify the process and lower the skills requirement for analysis. As vendors build systems to meet this demand, we hear about the coming ”democratization” of big data as more people at varying levels within organizations are empowered to find meaning and improve their own performance with data-driven insights. This is a good thing, but it does require caution. To paraphrase Col Jessup in A Few Good Men: You want answers? You can’t handle the data. In this webinar, we will survey emerging approaches to simplifying analysis, and discuss the benefits, dangers, and skills required for individuals and organizations to thrive in the brave new world of analytics everywhere, for everyone.
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EDW Webinar: Managing Change for Successful Data Governance
EDW Webinar: Managing Change for Successful Data Governance
Enterprise Data World Webinar: How to Get Your MDM Program Up & Running
Enterprise Data World Webinar: How to Get Your MDM Program Up & Running
Smart Data Webinar: Artificial General Intelligence - When Can I Get It?
Smart Data Webinar: Artificial General Intelligence - When Can I Get It?
LDM Webinar: Data Modeling & Business Intelligence
LDM Webinar: Data Modeling & Business Intelligence
Enterprise Data World Webinar: Mastering & Referencing Data for the Enterprise
Enterprise Data World Webinar: Mastering & Referencing Data for the Enterprise
Focus on Your Analysis, Not Your SQL Code
Focus on Your Analysis, Not Your SQL Code
WEBINAR: The Yosemite Project: An RDF Roadmap for Healthcare Information Inte...
WEBINAR: The Yosemite Project: An RDF Roadmap for Healthcare Information Inte...
DI&A Slides: Descriptive, Prescriptive, and Predictive Analytics
DI&A Slides: Descriptive, Prescriptive, and Predictive Analytics
Smart Data Slides: Data Science and Business Analysis - A Look at Best Practi...
Smart Data Slides: Data Science and Business Analysis - A Look at Best Practi...
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Social Minds
Talk given at Big Design Conference 2016 in Addison, TX
When Content is Bae
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James Cabrera
Many CDOs and Data Scientists came into being as part of a Big Data program. In many shops Big Data is the core driver for better Data Governance (DG) and Data Management (DM), and the sole evidence of the value of DM and DG. Big Data is also leaving the “hype cycle” and becoming embedded as part of the DM tool kit. This webinar will review what is working and what is not working in the Big Data realm. John and Kelle will not only address the technology progress, but also the organizational and management lessons learned, and will present what works and what does not. In this webinar we will cover: The state of Hadoop, MapReduce and the other “old” big data technologies New technologies and approaches An overview of organization and management of big data functions
Big Data Strategies – Organizational Structure and Technology
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DATAVERSITY
Cumul.io's goal is to bring Data Visualization & Analytics into the hands of marketing analysts, sales analysts and other business people who love numbers and decisions, but who don't like IT. It's time to let the Business Analyst into the Data Lab. Watch our talk at Data Innovation Summit 2016 at AXA Bank, Brussels.
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Haroen Vermylen
Join us May 16-19 in Orlando for ASUG Annual Conference - meet your ASUG Volunteers in person; co-located with SAPPHIRENOW
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Slides from a presentation by Dale Sinclair from AECOM at the Empowering you in a BIM world event from NBS in June 2016.
Moving Faster in a Digital World | Empowering you in a BIM world
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The NBS
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Anil Maharjan
Social Media
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Ola Hashim
Presentation by Lisa Battle at the UXPA2016 conference in Seattle, WA, on June 3, 2016. Many SaaS and enterprise applications today provide dashboards giving users an overview of how their business is performing and summarizing the work that needs to be done. Dashboards present a great opportunity to improve user experience by providing quick answers to users’ common questions, but they are also full of potential pitfalls for design. As UX design consultants, we are frequently asked to design (or redesign) dashboards for applications, and through that experience we have established best practices for dashboard design. We will discuss our approach to ensuring a good user experience for dashboards, focusing on 8 principles of UX design that are particularly relevant and illustrating them with real project examples.
Designing Great Dashboards for SaaS and Enterprise Applications
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Design for Context
Many SaaS and enterprise applications today provide dashboards giving users an overview of how their business is performing and summarizing the work that needs to be done. Dashboards present a great opportunity to improve user experience by providing quick answers to users’ common questions, but they are also full of potential pitfalls for design. As UX design consultants, we are frequently asked to design (or redesign) dashboards for applications, and through that experience we have established best practices for dashboard design. We will discuss our approach to ensuring a good user experience for dashboards, focusing on 9 principles of UX design that are particularly relevant and illustrating them with real project examples.
Designing Great Dashboards for SaaS and Enterprise Applications
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UXPA International
Contact CubeInsights at Info@CubeInsights.com for more information about SAP Big Data solutions and Analytics.
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cubeinsights
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Supply Chains To Admire 2016 Results
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McCoy & Partners' SAP TechEd TakeAway 2016
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Sven van Leuken, Bsc, PMP
presented at SharePoint TechFest Houston 2016
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CPA ONE 2016 - Big data: big decisions or big fallacy
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Oltre le conversazioni 2.0 - Roialty.com ad #ISBF16
Oltre le conversazioni 2.0 - Roialty.com ad #ISBF16
When Content is Bae
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Big Data Strategies – Organizational Structure and Technology
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Making Data Visualization & Analytics accessible to Business Users
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SQL Server 2016 Discovery Day - Data Visualization using R and Power BI
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making_social_media_work_for_your_athletic_department_walrich_garvis.pdf
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Designing Great Dashboards for SaaS and Enterprise Applications
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SAP HANA Retail RDS - Social Media & COPA - Advanced Analytics
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Organizations today need a broad set of enterprise data cloud services with key data functionality to modernize applications and utilize machine learning. They need a comprehensive platform designed to address multi-faceted needs by offering multi-function data management and analytics to solve the enterprise’s most pressing data and analytic challenges in a streamlined fashion. In this research-based session, I’ll discuss what the components are in multiple modern enterprise analytics stacks (i.e., dedicated compute, storage, data integration, streaming, etc.) and focus on total cost of ownership. A complete machine learning infrastructure cost for the first modern use case at a midsize to large enterprise will be anywhere from $3 million to $22 million. Get this data point as you take the next steps on your journey into the highest spend and return item for most companies in the next several years.
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...
DATAVERSITY
Do you ever wonder how data-driven organizations fuel analytics, improve customer experience, and accelerate business productivity? They are successful by governing and mastering data effectively so they can get trusted data to those who need it faster. Efficient data discovery, mastering and democratization is critical for swiftly linking accurate data with business consumers. When business teams can quickly and easily locate, interpret, trust, and apply data assets to support sound business judgment, it takes less time to see value. Join data mastering and data governance experts from Informatica—plus a real-world organization empowering trusted data for analytics—for a lively panel discussion. You’ll hear more about how a single cloud-native approach can help global businesses in any economy create more value—faster, more reliably, and with more confidence—by making data management and governance easier to implement.
Data at the Speed of Business with Data Mastering and Governance
Data at the Speed of Business with Data Mastering and Governance
DATAVERSITY
What is data literacy? Which organizations, and which workers in those organizations, need to be data-literate? There are seemingly hundreds of definitions of data literacy, along with almost as many opinions about how to achieve it. In a broader perspective, companies must consider whether data literacy is an isolated goal or one component of a broader learning strategy to address skill deficits. How does data literacy compare to other types of skills or “literacy” such as business acumen? This session will position data literacy in the context of other worker skills as a framework for understanding how and where it fits and how to advocate for its importance.
Exploring Levels of Data Literacy
Exploring Levels of Data Literacy
DATAVERSITY
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 Goals
Building a Data Strategy – Practical Steps for Aligning with Business Goals
DATAVERSITY
Uncover how your business can save money and find new revenue streams. Driving profitability is a top priority for companies globally, especially in uncertain economic times. It's imperative that companies reimagine growth strategies and improve process efficiencies to help cut costs and drive revenue – but how? By leveraging data-driven strategies layered with artificial intelligence, companies can achieve untapped potential and help their businesses save money and drive profitability. In this webinar, you'll learn: - How your company can leverage data and AI to reduce spending and costs - Ways you can monetize data and AI and uncover new growth strategies - How different companies have implemented these strategies to achieve cost optimization benefits
Make Data Work for You
Make Data Work for You
DATAVERSITY
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data. Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewards’ daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.
Data Catalogs Are the Answer – What is the Question?
Data Catalogs Are the Answer – What is the Question?
DATAVERSITY
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data. Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewards’ daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization. In this webinar, Bob will focus on: -Selecting the appropriate metadata to govern -The business and technical value of a data catalog -Building the catalog into people’s routines -Positioning the data catalog for success -Questions the data catalog can answer
Data Catalogs Are the Answer – What Is the Question?
Data Catalogs Are the Answer – What Is the Question?
DATAVERSITY
Because every organization produces and propagates data as part of their day-to-day operations, data trends are becoming more and more important in the mainstream business world’s consciousness. For many organizations in various industries, though, comprehension of this development begins and ends with buzzwords: “Big Data,” “NoSQL,” “Data Scientist,” and so on. Few realize that all solutions to their business problems, regardless of platform or relevant technology, rely to a critical extent on the data model supporting them. As such, data modeling is not an optional task for an organization’s data effort, but rather a vital activity that facilitates the solutions driving your business. Since quality engineering/architecture work products do not happen accidentally, the more your organization depends on automation, the more important the data models driving the engineering and architecture activities of your organization. This webinar illustrates data modeling as a key activity upon which so much technology and business investment depends. Specific learning objectives include: - Understanding what types of challenges require data modeling to be part of the solution - How automation requires standardization on derivable via data modeling techniques - Why only a working partnership between data and the business can produce useful outcomes
Data Modeling Fundamentals
Data Modeling Fundamentals
DATAVERSITY
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.
Showing ROI for Your Analytic Project
Showing ROI for Your Analytic Project
DATAVERSITY
Data Mesh is a trending approach to building a decentralized data architecture by leveraging a domain-oriented, self-service design. However, the pure definition of Data Mesh lacks a center of excellence or central data team and doesn’t address the need for a common approach for sharing data products across teams. The semantic layer is emerging as a key component to supporting a Hub and Spoke style of organizing data teams by introducing data model sharing, collaboration, and distributed ownership controls. This session will explain how data teams can define common models and definitions with a semantic layer to decentralize analytics product creation using a Hub and Spoke architecture. Attend this session to learn about: - The role of a Data Mesh in the modern cloud architecture. - How a semantic layer can serve as the binding agent to support decentralization. - How to drive self service with consistency and control.
How a Semantic Layer Makes Data Mesh Work at Scale
How a Semantic Layer Makes Data Mesh Work at Scale
DATAVERSITY
Enterprise data literacy. A worthy objective? Certainly! A realistic goal? That remains to be seen. As companies consider investing in data literacy education, questions arise about its value and purpose. While the destination – having a data-fluent workforce – is attractive, we wonder how (and if) we can get there. Kicking off this webinar series, we begin with a panel discussion to explore the landscape of literacy, including expert positions and results from focus groups: - why it matters, - what it means, - what gets in the way, - who needs it (and how much they need), - what companies believe it will accomplish. In this engaging discussion about literacy, we will set the stage for future webinars to answer specific questions and feature successful literacy efforts.
Is Enterprise Data Literacy Possible?
Is Enterprise Data Literacy Possible?
DATAVERSITY
Change is hard, especially in response to negative stimuli or what is perceived as negative stimuli. So organizations need to reframe how they think about data privacy, security and governance, treating them as value centers to 1) ensure enterprise data can flow where it needs to, 2) prevent – not just react – to internal and external threats, and 3) comply with data privacy and security regulations. Working together, these roles can accelerate faster access to approved, relevant and higher quality data – and that means more successful use cases, faster speed to insights, and better business outcomes. However, both new information and tools are required to make the shift from defense to offense, reducing data drama while increasing its value. Join us for this panel discussion with experts in these fields as they discuss: - Recent research about where data privacy, security and governance stand - The most valuable enterprise data use cases - The common obstacles to data value creation - New approaches to data privacy, security and governance - Their advice on how to shift from a reactive to resilient mindset/culture/organization You’ll be educated, entertained and inspired by this panel and their expertise in using the data trifecta to innovate more often, operate more efficiently, and differentiate more strategically.
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...
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.
Emerging Trends in Data Architecture – What’s the Next Big Thing?
Emerging Trends in Data Architecture – What’s the Next Big Thing?
DATAVERSITY
As DATAVERSITY’s RWDG series hurdles into our 12th year, this webinar takes a quick look behind us, evaluates the present, and predicts the future of Data Governance. Based on webinar numbers, hot Data Governance topics have evolved over the years from policies and best practices, roles and tools, data catalogs and frameworks, to supporting data mesh and fabric, artificial intelligence, virtualization, literacy, and metadata governance. Join Bob Seiner as he reflects on the past and what has and has not worked, while sharing examples of enterprise successes and struggles. In this webinar, Bob will challenge the audience to stay a step ahead by learning from the past and blazing a new trail into the future of Data Governance. In this webinar, Bob will focus on: - Data Governance’s past, present, and future - How trials and tribulations evolve to success - Leveraging lessons learned to improve productivity - The great Data Governance tool explosion - The future of Data Governance
Data Governance Trends - A Look Backwards and Forwards
Data Governance Trends - A Look Backwards and Forwards
DATAVERSITY
Would you share your bank account information on social media? How about shouting your social security number on the New York City subway? We didn’t think so either – that’s why data governance is consistently top of mind. In this webinar, we’ll discuss the common Cloud data governance best practices – and how to apply them today. Join us to uncover Google Cloud’s investment in data governance and learn practical and doable methods around key management and confidential computing. Hear real customer experiences and leave with insights that you can share with your team. Let’s get solving. Topics that you will hear addressed in this webinar: - Understanding the basics of Cloud Incident Response (IR) and anticipated data governance trends - Best practices for key management and apply data governance to your day-to-day - The next wave of Confidential Computing and how to get started, including a demo
Data Governance Trends and Best Practices To Implement Today
Data Governance Trends and Best Practices To Implement Today
DATAVERSITY
It is a fascinating, explosive time for enterprise analytics. It is from the position of analytics leadership that the enterprise mission will be executed and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data, and projects that will deliver analytics. After all, no matter what business you’re in, you’re in the business of analytics. The coming years will be full of big changes in enterprise analytics and data architecture. William will kick off the fifth year of the Advanced Analytics series with a discussion of the trends winning organizations should build into their plans, expectations, vision, and awareness now.
2023 Trends in Enterprise Analytics
2023 Trends in Enterprise Analytics
DATAVERSITY
Too often I hear the question “Can you help me with our data strategy?” Unfortunately, for most, this is the wrong request because it focuses on the least valuable component: the data strategy itself. A more useful request is: “Can you help me apply data strategically?” Yes, at early maturity phases the process of developing strategic thinking about data is more important than the actual product! Trying to write a good (must less perfect) data strategy on the first attempt is generally not productive –particularly given the widespread acceptance of Mike Tyson’s truism: “Everybody has a plan until they get punched in the face.” This program refocuses efforts on learning how to iteratively improve the way data is strategically applied. This will permit data-based strategy components to keep up with agile, evolving organizational strategies. It also contributes to three primary organizational data goals. Learn how to improve the following: - Your organization’s data - The way your people use data - The way your people use data to achieve your organizational strategy This will help in ways never imagined. Data are your sole non-depletable, non-degradable, durable strategic assets, and they are pervasively shared across every organizational area. Addressing existing challenges programmatically includes overcoming necessary but insufficient prerequisites and developing a disciplined, repeatable means of improving business objectives. This process (based on the theory of constraints) is where the strategic data work really occurs as organizations identify prioritized areas where better assets, literacy, and support (data strategy components) can help an organization better achieve specific strategic objectives. Then the process becomes lather, rinse, and repeat. Several complementary concepts are also covered, including: - A cohesive argument for why data strategy is necessary for effective data governance - An overview of prerequisites for effective strategic use of data strategy, as well as common pitfalls - A repeatable process for identifying and removing data constraints - The importance of balancing business operation and innovation
Data Strategy Best Practices
Data Strategy Best Practices
DATAVERSITY
The question is asked all the time: “What part of the organization should own your Data Governance program?” The typical answers are “the business” and “IT (information technology).” Another answer to that question is “Yes.” The program must be owned and reside somewhere in the organization. You may ask yourself if there is a correct answer to the question. Join this new RWDG webinar with Bob Seiner where Bob will answer the question that is the title of this webinar. Determining ownership of Data Governance is a vital first step. Figuring out the appropriate part of the organization to manage the program is an important second step. This webinar will help you address these questions and more. In this session Bob will share: - What is meant by “the business” when it comes to owning Data Governance - Why some people say that Data Governance in IT is destined to fail - Examples of IT positioned Data Governance success - Considerations for answering the question in your organization - The final answer to the question of who should own Data Governance
Who Should Own Data Governance – IT or Business?
Who Should Own Data Governance – IT or Business?
DATAVERSITY
It is clear that Data Management best practices exist and so does a useful process for improving existing Data Management practices. The question arises: Since we understand the goal, how does one design a process for Data Management goal achievement? This program describes what must be done at the programmatic level to achieve better data use and a way to implement this as part of your data program. The approach combines DMBoK content and CMMI/DMM processes – permitting organizations with the opportunity to benefit from the best of both. It also permits organizations to understand: - Their current Data Management practices - Strengths that should be leveraged - Remediation opportunities
Data Management Best Practices
Data Management Best Practices
DATAVERSITY
MLOps is a practice for collaboration between Data Science and operations to manage the production machine learning (ML) lifecycles. As an amalgamation of “machine learning” and “operations,” MLOps applies DevOps principles to ML delivery, enabling the delivery of ML-based innovation at scale to result in: Faster time to market of ML-based solutions More rapid rate of experimentation, driving innovation Assurance of quality, trustworthiness, and ethical AI MLOps is essential for scaling ML. Without it, enterprises risk struggling with costly overhead and stalled progress. Several vendors have emerged with offerings to support MLOps: the major offerings are Microsoft Azure ML and Google Vertex AI. We looked at these offerings from the perspective of enterprise features and time-to-value.
MLOps – Applying DevOps to Competitive Advantage
MLOps – Applying DevOps to Competitive Advantage
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Organisational success today depends on effective communication and collaboration with individuals from cultures with varying beliefs and practices. Indeed, with the workforce increasingly comprised of people of varying cultural backgrounds, leaders must now prioritise the significance of cultural competence in the workplace. Ensuring cultural competence at every level of your organisation cannot be understated. While cultural disparities can manifest in different ways, as a leader, you must build deep and nuanced cultural competence skills and education to accurately spot, address and alleviate the various scenarios that can arise. Failing to recognise the importance of cultural competence or not acting to improve it can lead to cultural negligence. There are a few things to consider to ensure your organisation is on the right track. In this deck, you'll understand the importance of building cultural competence in the workplace. You'll also learn • The three (3) dimensions of Cultural Competence in the workplace • Key strategies to build a culturally competent workforce • Major benefits you stand to gain by having a culturally competent team.
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Covid has drastically changed the way people work. Nowadays, many individuals can work wherever and whenever they prefer. However, this shift requires a different strategy for securing your environment. By adopting the Zero Trust principles, based on the 'Never Trust, Always Verify' mindset, you can mitigate these new risks. This session will delve into the concept and provide examples of how various HCL products can fit into this framework, particularly when it comes to building a central user repository and securing your email message flow.
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