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Sessions
Panel: Data Science: How Data Science and Data Virtualization can Help Mitigate the Coronavirus Pandemic
The whole world has been ravaged by the pandemic. As the world fights to return to normal, new information is needed on when it is safe for to go work, schools, restaurants, etc. In this vibrant panel discussion, the participants will discuss how data science and data virtualization can help with restoring confidence and health.
Data Science: Enabling Advanced Analytics for Data Scientists
Data Scientists build models to unearth associations among different data points that can deliver vital business insights to effect better decisions. In this presentation, the Denodo partner will elaborate how data scientists can use data virtualization for advanced analytics to effect better decisions.
Denodo Data Innovation Award - Customer Use Case Competition
Panasonic created a logical data fabric to turn connected car data into actionable insights for shorter freeway travel time, shorter emergency response time, accelerated pace towards zero fatalities etc. Listen to this session to learn how Panasonic created a cloud-based connected vehicle platform to develop services and applications for its customers and partner ecosystem, for a data driven future.
Panel: Cloud Marketplaces: How to Get Started?
Buying from cloud marketplaces can seem easy, but in practice they are not. In this session, the panelists will debunk the mystery of how to get started on cloud marketplaces, what aspects to consider when buying, and many more.
Panel: Logical Data Fabric: How Do Business Users Use It?
Ok, now we have a Logical Data Fabric, from a technology perspective. But what will the business users use it for? How exactly will they use it? These panel experts will draw upon their experiences from customer implementations to provide tangible suggestions.
Logical Data Fabric: Maturing Implementation from Small to Big
Implementing a Logical Data Fabric is not a one-shot deal. It is a journey. How do you start small, demonstrate ROI, and then expand to additional use cases? This presentation will provide practical tips on how to start and later expand Logical Data Fabric implementation.
Logical Data Fabric: A Realistic Customer Architecture
On the surface, a logical data fabric architecture appears to be simple for all your enterprise data needs, but behind the simplicity is a complex medley of disparate data sources that are unified by the fabric. Data Architect at Nationwide Insurance will present how they used the fabric to simplify a complex IT architecture.
Panel: Cloud Data Integration: Hybrid/Multicloud Strategies
Many companies transcend the hybrid world these days on their way to a multicloud solution. How did they do it? What worked and what did not? This panel will explore those questions and give pointed advice on effective strategies that you can use to spur your cloud journey.
Panel: Logical Data Fabric: Which Business Challenges does it Solve?
So, you now understand what a logical data fabric is, but what can you use it for? What are the key business challenges that can be quickly and better solved using the logical data fabric? Hear the experts offer their insights.
Logical Data Fabric: Implementation Best Practices
Ok, now we have a Logical Data Fabric, from a technology perspective. But what will the business users use it for? How exactly will they use it? These panel experts will draw upon their experiences from customer implementations to provide tangible suggestions.
Logical Data Fabric: A Customer Case Study
Now you have some idea about logical data fabric. But you may be wondering how does it look like in real life implementation, from a Denodo customer's perspective. Jim Boesger, Data Architect from Progressive Insurance, will walk you through how their logical data fabric evolved over time.
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Panel: AI/ML: Why is AI/ML the Future of Data Integration/Management?
Over the last 20 years, data integration and mangement has grown to include many different capabilities, but it has now become a burden for the users, who are spending enormous amount of time to accomplish data tasks. In this panel, the experts will present how users can overcome legacy data integration challenges using AI/ML.