Slides: Using Analytics and Fraud Management To Increase Revenues and Differe...DATAVERSITY
Fraud has many costs to a business, not only in terms of real dollars lost, but also in draining company resources investigating and prosecuting fraud and in reputational damage. For these reasons alone, companies should put systems and processes in place to combat fraud.
However, there are other extremely compelling strategic reasons why companies should implement fraud solutions which can help them gain competitive advantage, grow market share, increase profits, develop differentiated products, and implement more targeted and advantageous customer pricing.
This webinar will review the multiple business benefits for analyzing and combating fraud and the different approaches and best practices to analyzing data for fraud prevention. We will also review several real-life case studies where companies have used fraud analytics to win in the marketplace. Lastly, we will review different technology architectures to enable optimal fraud analytics and prevention.
Your business has systems producing data. You need to get and analyse that data and report it to the right people at the right time so they can act on it. Maybe you also need to scale up your current BI, reduce costs and eliminate system bottlenecks. One thing is sure: Business Intelligence is now essential to company decision-making, it drives every business.
Some topics covered:
3 Fundamental barriers to BI.
BI Wins: Top 8 results we see from great BI.
Making your ROI case: Know your audience.
11 BI Goals to consider.
"If Business Intelligence distribution is the lifeblood of an enterprise, its absence is the equivalent of strangulation. It’s not just about producing the right stuff. It’s about getting that stuff to the right person at the right time."
ADV Slides: Strategies for Transitioning to a Cloud-First EnterpriseDATAVERSITY
A great comfort with cloud deployment has emerged. Businesses are migrating databases to the cloud or building databases there as a result of scale challenges with the on-premises model, the cloud becoming the “center of gravity”, on-premises databases reaching capacity or emerging uses cases that are specific to the cloud. But not all organizations! And some struggle mightily with the move!
Learn about the factors that impact organizations when shifting data and applications to the cloud. What must you consider as you move significant applications and data to the cloud? This webinar will cover the major decision points that management needs to consider when moving to the cloud.
These include changes to the software model, development and quality assurance, recovery outage, and disaster recovery as well as new concerns about query performance and service levels, data interchange in the cloud, safe harbor and cross-border restrictions, and security and privacy.
We’ll also cover the new models for capacity planning and growth and staff responsibilities, the need for increased organizational change management, and how to pick targets for the journey.
ADV Slides: Data Curation for Artificial Intelligence StrategiesDATAVERSITY
This webinar will focus on the promise AI holds for organizations in every industry and every size, and how to overcome some of the challenge today of how to prepare for AI in the organization and how to plan AI applications.
The foundation for AI is data. You must have enough data to analyze and build models. Your data determines the depth of AI you can achieve — for example, statistical modeling, machine learning, or deep learning — and its accuracy. The increased availability of data is the single biggest contributor to the uptake in AI where it is thriving. Indeed, data’s highest use in the organization soon will be training algorithms. AI is providing a powerful foundation for impending competitive advantage and business disruption.
Slides: Using Analytics and Fraud Management To Increase Revenues and Differe...DATAVERSITY
Fraud has many costs to a business, not only in terms of real dollars lost, but also in draining company resources investigating and prosecuting fraud and in reputational damage. For these reasons alone, companies should put systems and processes in place to combat fraud.
However, there are other extremely compelling strategic reasons why companies should implement fraud solutions which can help them gain competitive advantage, grow market share, increase profits, develop differentiated products, and implement more targeted and advantageous customer pricing.
This webinar will review the multiple business benefits for analyzing and combating fraud and the different approaches and best practices to analyzing data for fraud prevention. We will also review several real-life case studies where companies have used fraud analytics to win in the marketplace. Lastly, we will review different technology architectures to enable optimal fraud analytics and prevention.
Your business has systems producing data. You need to get and analyse that data and report it to the right people at the right time so they can act on it. Maybe you also need to scale up your current BI, reduce costs and eliminate system bottlenecks. One thing is sure: Business Intelligence is now essential to company decision-making, it drives every business.
Some topics covered:
3 Fundamental barriers to BI.
BI Wins: Top 8 results we see from great BI.
Making your ROI case: Know your audience.
11 BI Goals to consider.
"If Business Intelligence distribution is the lifeblood of an enterprise, its absence is the equivalent of strangulation. It’s not just about producing the right stuff. It’s about getting that stuff to the right person at the right time."
ADV Slides: Strategies for Transitioning to a Cloud-First EnterpriseDATAVERSITY
A great comfort with cloud deployment has emerged. Businesses are migrating databases to the cloud or building databases there as a result of scale challenges with the on-premises model, the cloud becoming the “center of gravity”, on-premises databases reaching capacity or emerging uses cases that are specific to the cloud. But not all organizations! And some struggle mightily with the move!
Learn about the factors that impact organizations when shifting data and applications to the cloud. What must you consider as you move significant applications and data to the cloud? This webinar will cover the major decision points that management needs to consider when moving to the cloud.
These include changes to the software model, development and quality assurance, recovery outage, and disaster recovery as well as new concerns about query performance and service levels, data interchange in the cloud, safe harbor and cross-border restrictions, and security and privacy.
We’ll also cover the new models for capacity planning and growth and staff responsibilities, the need for increased organizational change management, and how to pick targets for the journey.
ADV Slides: Data Curation for Artificial Intelligence StrategiesDATAVERSITY
This webinar will focus on the promise AI holds for organizations in every industry and every size, and how to overcome some of the challenge today of how to prepare for AI in the organization and how to plan AI applications.
The foundation for AI is data. You must have enough data to analyze and build models. Your data determines the depth of AI you can achieve — for example, statistical modeling, machine learning, or deep learning — and its accuracy. The increased availability of data is the single biggest contributor to the uptake in AI where it is thriving. Indeed, data’s highest use in the organization soon will be training algorithms. AI is providing a powerful foundation for impending competitive advantage and business disruption.
ADV Slides: Modern Analytic Data Architecture Maturity ModelingDATAVERSITY
Maturity frameworks have varying levels of Data Management maturity. Each level corresponds to not only increased data maturity, but also increased organizational maturity and bottom-line ROI. There are recommended targets to achieve an effective information management program. The speaker’s maturity framework sequences the information management activities for your consideration. It is based on real client roadmaps. This webinar promises to offer a wealth of ideas for key quick wins to benefit the organization’s information management program.
Attendees can self-assess their current information management capabilities as we go through data strategy, organization, architecture, and technology, yielding an overall view of the current level of information management maturity.
This webinar provides a foundation for enhancing current data and analytic capabilities and updating the strategy and plans for achievement of improved information management maturity, aligned with major initiatives.
Slides: Data Monetization — Demonstrating Quantifiable Financial Benefits fro...DATAVERSITY
Data monetization is a cross-functional discipline that draws from best practices in Enterprise Data Management (EDM), technology, legal engineering, and finance to leverage data to increase revenues, reduce costs, and manage risk. EDM programs have generally found it extremely difficult to get senior management buy-in the absence of regulatory pressures or the fear of a data breach. Data monetization is an approach to drive quantifiable business benefits from data and information. This bottom-line driven approach is key to generating business adoption with stakeholders.
This session will review the key aspects of data monetization:
• Introduction to Data Monetization
• Identify Stakeholders
• Build Inventory of Use Cases
• Develop Business Cases
• Execute Initiatives
• Realize Business Benefits
• Legal Engineering and Regulatory Compliance
• Data Marketplace
ADV Slides: The Data Needed to Evolve an Enterprise Artificial Intelligence S...DATAVERSITY
This webinar will focus on the promise AI holds for organizations in every industry and every size, and how to overcome some of the challenges today of how to prepare for AI in the organization and how to plan AI applications.
The foundation for AI is data. You must have enough data to analyze to build models. Your data determines the depth of AI you can achieve – for example, statistical modeling, machine learning, or deep learning – and its accuracy. The increased availability of data is the single biggest contributor to the uptake in AI where it is thriving. Indeed, data’s highest use in the organization soon will be training algorithms. AI is providing a powerful foundation for impending competitive advantage and business disruption.
ADV Slides: The Impact of Machine Learning on the Enterprise TodayDATAVERSITY
Despite the dramatic changes we have seen in business recently, another level of change looms.
We are headed toward a future permeated with artificial intelligence and machine learning (ML), where machines take on more of the work people have traditionally done, and then some. The potential for ML is enormous. We are at the dawn of a whole new era of intelligent devices that will revolutionize our business and personal worlds.
Corporations wishing to lead with AI/ML should make plans now to establish their initiatives and their technology framework and nurture the necessary skills.
Slides: Case Study — How J.B. Hunt is Driving Efficiency with AI and Real-Tim...DATAVERSITY
J.B. Hunt, one of the leading providers of transportation and logistics services in North America, recognizes the criticality of customer responsiveness, service quality, and operational efficiency for its success. However, with its data spread across multiple sources, including legacy mainframe systems, the organization was struggling to meet data requirements from multiple departments. They struggled to troubleshoot operational issues and respond to customers quickly.
Join this webinar to hear about the optimized solution J. B. Hunt implemented, which automates real-time data pipelines for a reliable cloud data lake and provides multiple user groups an in-the-moment view of data without overwhelming internal operational systems. Discover how J.B. Hunt now leverages a modernized data environment to accelerate data delivery and drive various AI and analytics initiatives such as real-time service-pricing, competitive counterbidding, and improving their customer experience.
Learn how you can:
• Ingest data in real-time from legacy mainframe systems, enterprise applications, and more
• Create a reliable cloud data lake to accelerate AI and Analytic Initiatives
• Catalog, prepare, and provision data to empower data consumers
• Drive operational efficiency and customer experience with AI-augmented insights
The last year has put a new lens on what speed to insights actually mean - day-old data became useless, and only in-the-moment-insights became relevant, pushing data and analytics teams to their breaking point. The results, everyone has fast forwarded in their transformation and modernization plans, and it's also made us look differently at dashboards and the type of information that we're getting the business. Join this live event and hear about the data teams ditching their dashboards to embrace modern cloud analytics.
Consumer insights and engagement: Delivering a differentiated brand experienc...IBM Analytics
Digital, social and mobile technologies have primed consumers to expect convenient, personalized interactions and fast, easy access to information. IBM Consumer Insights and Engagement integrates consumer data, analytics and marketing systems of engagement. For more information and to see how companies are using predictive
analytics to engage customers and drive results, visit: http://ibm.co/consumeranalytics
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.
You had a strategy. You were executing it. You were then side-swiped by COVID, spending countless cycles blocking and tackling. It is now time to step back onto your path.
CCG is holding a workshop to help you update your roadmap and get your team back on track and review how Microsoft Azure Solutions can be leveraged to build a strong foundation for governed data insights.
DAS Slides: Graph Databases — Practical Use CasesDATAVERSITY
Graph databases are seeing a spike in popularity as their value in leveraging large data sets for key areas such as fraud detection, marketing, and network optimization become increasingly apparent. With graph databases, it’s been said that ‘the data model and the metadata are the database’. What does this mean in a practical application, and how can this technology be optimized for maximum business value?
Slides: Powering a Sustainable Data Governance Program – Learnings & Best Pra...DATAVERSITY
This webinar will take you on the digital transformation journey of a traditional energy company that reinvented how it conducts business – from branding to customer engagement – with data as the conduit. There’s no doubt E.ON, based in Essen, Germany, has established one of the most comprehensive and successful data governance programs in modern business. In an interactive format, you’ll hear how E.ON launched data governance as a service from the inside out, including:
• Building a business case
• Evaluating supporting technology
• Developing policies and processes
• Involving and educating employees
• Ongoing evaluation and improvements
• Future implications
Don’t miss this opportunity to learn from a real-world data governance success. We promise it will recharge how you approach the practice and the role of data. It really does have the power to change things.
Data Centric Development: Supercharge your web & mobile application developmentBright North
Many businesses are finding that their web and mobile applications aren’t providing the long-term solution they were hoping for. As consumers provide more and more useful data, these digital platforms don’t allow businesses to take advantage of the huge opportunities that data presents.
Our new whitepaper details the practical steps you can take to supercharge your web and mobile application development and stay ahead of the data revolution.
Towards the Next Generation Financial Crimes Platform - How Data, Analytics, ...Molly Alexander
Towards the Next Generation Financial Crimes Platform - How Data, Analytics, & ML Are Transforming the Fight Against Fraud, AML & Cybersecurity -Nadeem Asghar
Learn the importance of Data Quality and the six key steps that you can take and put into process to help you realize tangible ROI on your data quality initiative.
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
Analytics is all about course correcting the future. While this starts with accurate predictions of the future, without resultant actions steering the future toward company goals, knowing that future is academic. Successful companies must be grounded in successful data-based prescription. In this webinar, William will present a data maturity model with a focus on how analytic competitors outdo the competition by looking forward to a data-influenced future.
Réinventez le Data Management avec la Data Virtualization de DenodoDenodo
Regardez la version complète du webinar à la demande ici: https://goo.gl/ZxRqmX
"D'ici à 2020, 50% des entreprises mettront en œuvre une forme de virtualisation des données comme une option pour l'intégration de données", selon le cabinet d’analystes Gartner. La virtualisation des données ou data virtualization est devenue une force motrice pour les entreprises pour la mise en œuvre d’une architecture de données d'entreprise agile, temps réel et flexible.
Au sommaire de ce webinar:
Denodo et son positionnement sur le marché de la Data Virtualization
Les principales fonctionnalités
Démo/vidéo
Les principaux cas d’usage. Présentation d'un cas client : comment Intel a repensé l’architecture de ses données avec la Data Virtualization
Les ressources
Questions/Réponses
ADV Slides: Modern Analytic Data Architecture Maturity ModelingDATAVERSITY
Maturity frameworks have varying levels of Data Management maturity. Each level corresponds to not only increased data maturity, but also increased organizational maturity and bottom-line ROI. There are recommended targets to achieve an effective information management program. The speaker’s maturity framework sequences the information management activities for your consideration. It is based on real client roadmaps. This webinar promises to offer a wealth of ideas for key quick wins to benefit the organization’s information management program.
Attendees can self-assess their current information management capabilities as we go through data strategy, organization, architecture, and technology, yielding an overall view of the current level of information management maturity.
This webinar provides a foundation for enhancing current data and analytic capabilities and updating the strategy and plans for achievement of improved information management maturity, aligned with major initiatives.
Slides: Data Monetization — Demonstrating Quantifiable Financial Benefits fro...DATAVERSITY
Data monetization is a cross-functional discipline that draws from best practices in Enterprise Data Management (EDM), technology, legal engineering, and finance to leverage data to increase revenues, reduce costs, and manage risk. EDM programs have generally found it extremely difficult to get senior management buy-in the absence of regulatory pressures or the fear of a data breach. Data monetization is an approach to drive quantifiable business benefits from data and information. This bottom-line driven approach is key to generating business adoption with stakeholders.
This session will review the key aspects of data monetization:
• Introduction to Data Monetization
• Identify Stakeholders
• Build Inventory of Use Cases
• Develop Business Cases
• Execute Initiatives
• Realize Business Benefits
• Legal Engineering and Regulatory Compliance
• Data Marketplace
ADV Slides: The Data Needed to Evolve an Enterprise Artificial Intelligence S...DATAVERSITY
This webinar will focus on the promise AI holds for organizations in every industry and every size, and how to overcome some of the challenges today of how to prepare for AI in the organization and how to plan AI applications.
The foundation for AI is data. You must have enough data to analyze to build models. Your data determines the depth of AI you can achieve – for example, statistical modeling, machine learning, or deep learning – and its accuracy. The increased availability of data is the single biggest contributor to the uptake in AI where it is thriving. Indeed, data’s highest use in the organization soon will be training algorithms. AI is providing a powerful foundation for impending competitive advantage and business disruption.
ADV Slides: The Impact of Machine Learning on the Enterprise TodayDATAVERSITY
Despite the dramatic changes we have seen in business recently, another level of change looms.
We are headed toward a future permeated with artificial intelligence and machine learning (ML), where machines take on more of the work people have traditionally done, and then some. The potential for ML is enormous. We are at the dawn of a whole new era of intelligent devices that will revolutionize our business and personal worlds.
Corporations wishing to lead with AI/ML should make plans now to establish their initiatives and their technology framework and nurture the necessary skills.
Slides: Case Study — How J.B. Hunt is Driving Efficiency with AI and Real-Tim...DATAVERSITY
J.B. Hunt, one of the leading providers of transportation and logistics services in North America, recognizes the criticality of customer responsiveness, service quality, and operational efficiency for its success. However, with its data spread across multiple sources, including legacy mainframe systems, the organization was struggling to meet data requirements from multiple departments. They struggled to troubleshoot operational issues and respond to customers quickly.
Join this webinar to hear about the optimized solution J. B. Hunt implemented, which automates real-time data pipelines for a reliable cloud data lake and provides multiple user groups an in-the-moment view of data without overwhelming internal operational systems. Discover how J.B. Hunt now leverages a modernized data environment to accelerate data delivery and drive various AI and analytics initiatives such as real-time service-pricing, competitive counterbidding, and improving their customer experience.
Learn how you can:
• Ingest data in real-time from legacy mainframe systems, enterprise applications, and more
• Create a reliable cloud data lake to accelerate AI and Analytic Initiatives
• Catalog, prepare, and provision data to empower data consumers
• Drive operational efficiency and customer experience with AI-augmented insights
The last year has put a new lens on what speed to insights actually mean - day-old data became useless, and only in-the-moment-insights became relevant, pushing data and analytics teams to their breaking point. The results, everyone has fast forwarded in their transformation and modernization plans, and it's also made us look differently at dashboards and the type of information that we're getting the business. Join this live event and hear about the data teams ditching their dashboards to embrace modern cloud analytics.
Consumer insights and engagement: Delivering a differentiated brand experienc...IBM Analytics
Digital, social and mobile technologies have primed consumers to expect convenient, personalized interactions and fast, easy access to information. IBM Consumer Insights and Engagement integrates consumer data, analytics and marketing systems of engagement. For more information and to see how companies are using predictive
analytics to engage customers and drive results, visit: http://ibm.co/consumeranalytics
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.
You had a strategy. You were executing it. You were then side-swiped by COVID, spending countless cycles blocking and tackling. It is now time to step back onto your path.
CCG is holding a workshop to help you update your roadmap and get your team back on track and review how Microsoft Azure Solutions can be leveraged to build a strong foundation for governed data insights.
DAS Slides: Graph Databases — Practical Use CasesDATAVERSITY
Graph databases are seeing a spike in popularity as their value in leveraging large data sets for key areas such as fraud detection, marketing, and network optimization become increasingly apparent. With graph databases, it’s been said that ‘the data model and the metadata are the database’. What does this mean in a practical application, and how can this technology be optimized for maximum business value?
Slides: Powering a Sustainable Data Governance Program – Learnings & Best Pra...DATAVERSITY
This webinar will take you on the digital transformation journey of a traditional energy company that reinvented how it conducts business – from branding to customer engagement – with data as the conduit. There’s no doubt E.ON, based in Essen, Germany, has established one of the most comprehensive and successful data governance programs in modern business. In an interactive format, you’ll hear how E.ON launched data governance as a service from the inside out, including:
• Building a business case
• Evaluating supporting technology
• Developing policies and processes
• Involving and educating employees
• Ongoing evaluation and improvements
• Future implications
Don’t miss this opportunity to learn from a real-world data governance success. We promise it will recharge how you approach the practice and the role of data. It really does have the power to change things.
Data Centric Development: Supercharge your web & mobile application developmentBright North
Many businesses are finding that their web and mobile applications aren’t providing the long-term solution they were hoping for. As consumers provide more and more useful data, these digital platforms don’t allow businesses to take advantage of the huge opportunities that data presents.
Our new whitepaper details the practical steps you can take to supercharge your web and mobile application development and stay ahead of the data revolution.
Towards the Next Generation Financial Crimes Platform - How Data, Analytics, ...Molly Alexander
Towards the Next Generation Financial Crimes Platform - How Data, Analytics, & ML Are Transforming the Fight Against Fraud, AML & Cybersecurity -Nadeem Asghar
Learn the importance of Data Quality and the six key steps that you can take and put into process to help you realize tangible ROI on your data quality initiative.
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
Analytics is all about course correcting the future. While this starts with accurate predictions of the future, without resultant actions steering the future toward company goals, knowing that future is academic. Successful companies must be grounded in successful data-based prescription. In this webinar, William will present a data maturity model with a focus on how analytic competitors outdo the competition by looking forward to a data-influenced future.
Réinventez le Data Management avec la Data Virtualization de DenodoDenodo
Regardez la version complète du webinar à la demande ici: https://goo.gl/ZxRqmX
"D'ici à 2020, 50% des entreprises mettront en œuvre une forme de virtualisation des données comme une option pour l'intégration de données", selon le cabinet d’analystes Gartner. La virtualisation des données ou data virtualization est devenue une force motrice pour les entreprises pour la mise en œuvre d’une architecture de données d'entreprise agile, temps réel et flexible.
Au sommaire de ce webinar:
Denodo et son positionnement sur le marché de la Data Virtualization
Les principales fonctionnalités
Démo/vidéo
Les principaux cas d’usage. Présentation d'un cas client : comment Intel a repensé l’architecture de ses données avec la Data Virtualization
Les ressources
Questions/Réponses
The Power of a Complete 360° View of the Customer - Digital Transformation fo...Denodo
Watch here: https://bit.ly/2N9eNaN
Join the experts from Mastek and Denodo to hear how your company can place a single secure virtual layer between all disparate data sources, including both on-premise and in the cloud, to solve current organizational challenges. Such challenges include connecting, integrating, and governing data to prevent your enterprise architecture footprint from becoming untenable and laborious. It is not uncommon for an organization to have 50 to 100+ data sources, applications, and solutions, and the ability to tie them together for actionable insights, is undoubtedly a competitive advantage.
Learn how data virtualization can benefit organizations with the following:
- Accelerated data projects - timelines of 6-12 months reduced to 3-6 months with data virtualization
- Real-time integration and data access, with 80% reduction in development resources
- Self-Service, security & governance in one single integrated platform - savings of 30% in IT operational costs
- Faster business decisions - BI and reporting information delivered 10 times faster using data services
- With data virtualization, businesses can create a complete view of the customer, product, or supplier in only a matter of weeks!
Join Mike (Graz) Graziano, Senior Vice President of Global Alliances and Mike Cristancho, Director, Solutions Consulting from Mastek along with Paul Moxon, SVP of Data Architectures and Chief Evangelist at Denodo.
Four Key Considerations for your Big Data Analytics StrategyArcadia Data
Learn 4 of the key things to consider as you create your big data analytics strategy from John Meyers (Enterprise Management Associates) and Steve Wooledge (Arcadia Data).
Entry Points – How to Get Rolling with Big Data AnalyticsInside Analysis
The Briefing Room with Robin Bloor and IBM
Live Webcast Sept. 24, 2013
Watch the archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?AT=pb&SP=EC&rID=7501927&rKey=664935ceb7de1aec
Where to begin? That question remains prominent for many organizations who are trying to leverage the value of big data analytics. Most sources of big data are quite different than traditional enterprise data systems. This requires new skill sets, both for the granular integration work, as well as the strategic business perspective required to design useful solutions.
Register for this episode of The Briefing Room to hear veteran Analyst Dr. Robin Bloor as he explains the pain points associated with modern data volumes and types. He will be briefed by Rick Clements of IBM, who will tout IBM's big data platform, specifically InfoSphere BigInsights, InfoSphere Streams and InfoSphere Data Explorer. He will also present specific use cases that demonstrate how IT and the line of business can springboard over existing challenges, gain insight and improve operational performance.
Visit InsideAnalysis.com for more information
2020 Cloudera Data Impact Awards FinalistsCloudera, Inc.
Cloudera is proud to present the 2020 Data Impact Awards Finalists. This annual program recognizes organizations running the Cloudera platform for the applications they've built and the impact their data projects have on their organizations, their industries, and the world. Nominations were evaluated by a panel of independent thought-leaders and expert industry analysts, who then selected the finalists and winners. Winners exemplify the most-cutting edge data projects and represent innovation and leadership in their respective industries.
It seems that everyone is talking about Big Data these days. As the Industrial Internet evolves and continues to feed the Big Data machine, companies are finding it more and more critical to develop strategies for turning data into information and information in intelligence. There’s certainly not a shortage of technologies in the marketplace to start playing with the petabytes of data coming from within and outside of the enterprise.
This is the powerpoint presentation used by our guest speaker Barbara (Barb) Kruetzkamp, IT Leader in Data Management at GE Aviation, to discuss approaches and frameworks to enhance business intelligence capabilities by linking industrial and enterprise (internal) data. We also compared traditional vs. transformational IT execution models, and how to put data first.
Barb was born and raised in Cincinnati, Ohio. She attended Thomas More College in Kentucky, graduating with a B.A. in Computer Science and Business Administration. She built technical depth leading infrastructure architecture, then as a Chief Enterprise Architect at GE Corporate. Barb returned to GE Aviation in 2014 to lead the master data management initiative. Barb enjoys volunteering with the developmentally disabled, STEM and high school band students. She also likes to cook, jazzercise, and travel abroad. Her 3 kids keep life active and fun.
Leap to Next Generation Data Management with Denodo 7.0Denodo
Watch Mike's keynote presentation from Fast Data Strategy Virtual Summit here: https://goo.gl/cC3bCq
Mike Ferguson is an independent analyst and the Managing Director for Intelligent Business Strategies. In this session, he will be discussing how Denodo Platform 7.0 enables and redefines data management for the next generation.
Attend this session to discover:
• Perspectives from independent industry analyst Mike Ferguson
• Why data virtualization is gaining momentum
• How Denodo Platform 7.0 enables next generation data management
Turning Big Data into Better Business OutcomesCisco Canada
The big data era is upon us as organizations are awash in social, mobile and machine-generated data. Opportunity abounds. But competition threatens. Further this high volume, data-at-the-edge environment challenges centralized data warehouse approaches typical with BI and Analytics today. Data virtualization provides a more agile, leave-the-data-where-it-lies way to fulfill BI and Analytic needs and achieve key business outcomes.
Building the Information Governance Business Case Within Your CompanyAIIM International
Information Governance is a critical component in today’s business world to ensure that ALL information is visible, organized, and compliant. This solution can help your business to gain a competitive edge through the strategic and economic use of information. Despite the critical need, many companies still struggle to get funding and buy-in from upper management to move initiatives forward. This presentation will highlight key focus points for IG advocates to get internal stakeholders on board.
Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...Denodo
This content was presented during the Smart Data Summit Dubai 2015 in the UAE on May 25, 2015, by Jesus Barrasa, Senior Solutions Architect at Denodo Technologies.
In the era of Big Data, IoT, Cloud and Social Media, Information Architects are forced to rethink how to tackle data management and integration in the enterprise. Traditional approaches based on data replication and rigid information models lack the flexibility to deal with this new hybrid reality. New data sources and an increasing variety of consuming applications, like mobile apps and SaaS, add more complexity to the problem of delivering the right data, in the right format, and at the right time to the business. Data Virtualization emerges in this new scenario as the key enabler of agile, maintainable and future-proof data architectures.
Analytics plays a critical role in supporting strategic business initiatives. Despite the apparent value of providing the data infrastructure for these initiatives, many executives question the economic feasibility of business intelligence and analytics. This requires information professionals to calculate and present the 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 IT professionals research, measure, and present the economic value of a proposed or existing analytics initiative. The session will provide practical advice about how to calculate ROI, the formulas in use, and how to collect necessary information.
Open Source and the New Economics of IT - Ingres CIO Doug HarrAlfresco Software
http://blogs.alfresco.com/wp/webcasts
Open source ECM is proven to :
* Lower Total Cost of Ownership
* Eliminate licensing fees and vendor lock-in
* Deliver faster proofs-of-concept
* Provide a complete solution for managing all enterprise content
Many companies are already leveraging open source ECM to take control of their ever growing business content at a fraction of the cost of proprietary ECM market solutions and without the danger of vendor lock-in.
The Ingres ECM Bundle for Alfresco enables innovative document management, team collaboration, and knowledge management applications.
Basing the ECM solution on Ingres Database guarantees unique high availability features that make compliance with auditing requirements an easier task, and cost much less.
Ingres CIO Doug Harr shares examples on how he uses content management solutions from Alfresco.
He also discusses the significant trends affecting the IT market today.
Embracing The New Economics of IT by adopting open source ECM will help companies to:
* better maintain their systems during the economic downturn,
* keep essential projects alive, and
* pursue innovation that can help guarantee a competitive advantage when conditions improve.
Open Source and the New Economics of IT - Ingres CIO Doug Harr
Swoc21 Feb08 Amig
1. SWOC DAMA 2008 Showcase at American Modern Insurance February 21, 2008
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15. Enterprise Data Warehouse The data warehouse will support: Loss Cost Analysis Retention Analysis modernLINK Reporting Profitability Analysis Data Warehouse Underwriting Analysis Product Pricing Analysis Financial Analysis
16. Data Warehouse Value MH Loss Cost SB Loss Cost MC Loss Cost Retention UVRC Pricing / GLM Loss Triangles modernLINK MH PIF mLINK vs. Legacy Retro Studies Mapping Renewal Reporting FID MSB CAT Analysis Cancellation Reporting Address Data Agency Profile Analysis Claims Liability Partner Experience Reporting
17. Data Warehouse Statistics 1997 policies used to seed warehouse: ~700,000 Total policies Jan 1998 thru Jun 2007 Total units Jan 1998 thru Jun 2007 Average Number of Coverages per policy: 5 Average number of policies in-force per month: 800,000 Average number of claims per month: 8,000
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23. Enterprise Data Model Quotes/Policies Claims Coverages Accidents/Violations Homes/Vehicles UW rules Makes/Models Geography Address Insureds Operators Lienholders Claimants Things Places People
24. Jump Start Enterprise Data Model Acord Standards Generic Model based on Insurance Industry Practices Transform AMIG Specific Requirements Integrated View: Common Data Definitions Across business Manufactured Home Site Built Motorcycle Motor Home Travel Trailer Classic Auto FID Commercial AMIG Enterprise Data Model
47. SWOC DAMA 2008 Showcase at American Modern Insurance February 21, 2008
Editor's Notes
Sandy to provide slides on KMA..
Sandy to provide slides on KMA..
Web-enable American Modern’s Insurance offerings; promote them through a ubiquitous, user-friendly, easy to use business offering and processing model. Enable new capabilities and processes through “Legacy” replacement for: Product Development Rating, Pricing and Underwriting Policy Administration Processing Partner Relationship Management Customer Management Develop a Knowledge Management Architecture to support the initiatives named above
The anticipated returns of this business case are as follows: 20% annual increases in directly-attributed new business 37% of Policy and Partner Administration moved from existing customer care functions directly to point of service functions 25% improvement in current Product Review and Management cycle time 21% improvement in Product Filings cycle time 2% reduction in total loss ratio directly attributed to modernLINK initiative These returns would yield a significant recurring annual benefit through additional premium, increased profit, and decreased expenses. Almost 50% of these benefits would be attained through better knowledge/data management, richer data segmentation, and improved data and risk selection. John Hayden, President and CEO, American Modern states: We must have accurate data about the risks we insure today if we are to ever be successful in establishing The Right Rate for Every Risk we choose to insure in the future. These returns would yield significant recurring annual benefits through additional premium, increased profit, and decreased expenses. Almost 50% of these benefits would be attained through better knowledge/data management, richer data segmentation, and improved data and risk selection.
These returns would yield a significant recurring annual benefit through additional premium, increased profit, and decreased expenses. Almost 50% of these benefits would be attained through better knowledge/data management, richer data segmentation, and improved data and risk selection. John Hayden, President and CEO, American Modern states: We must have accurate data about the risks we insure today if we are to ever be successful in establishing The Right Rate for Every Risk we choose to insure in the future. These returns would yield significant recurring annual benefits through additional premium, increased profit, and decreased expenses. Almost 50% of these benefits would be attained through better knowledge/data management, richer data segmentation, and improved data and risk selection.
As part of the Enterprise Architecture Transformation initiative, American Modern created a roadmap to develop: This Knowledge Management architecture would provide the company with the ability to monitor, measure, and analyze existing business, refine and improve current practices, and identify new opportunities.
Now in its seventh year, the Knowledge Management architecture has delivered significant results. Today, our business units can make informed business decisions, respond quickly to new business initiatives, and create new opportunities because of the tools and information provided. They are moving from data collectors to data consumers. Business users have information delivered to their desktops in the form of reports, analytic cubes, and maps. This new ability to ask “why ,” instead of “ wha t,” will enable American Modern to transform itself into a learning organization.
Here is what they say:
Not only have we received internal recognition, but external as well
• IBM RS6000 AIX processors • EMC data storage • Oracle DBMS • COGNOS for reporting utilizing query, report, mapping and analytical tools • Websphere Portal • LDAP for single sign-on
The business units within American Modern have wholeheartedly embraced the Enterprise Data Warehouse. It has even taken on a life of its own – it appears to be able to do almost anything For the first time, they have been able to get a holistic view of information in one place. In addition, American Modern is ready to embark on its next phase of delivering information to its external business partners using the same architecture.