Packed Lunch Webinar Series

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The Role of Data Virtualization in an API Economy

How data virtualization works as a service container, as a source for microservices and as an API gateway.

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From Single Purpose to Multi Purpose Data Lakes - Broadening End Users

Historically data lakes have been created as centralized physical data storage platform for data scientists to analyze data. But lately the explosion of big data, data privacy rules, departmental restrictions among many other things have made the centralized data repository approach less feasible. In his recent whitepaper, renowned analyst Rick F. Van Der Lans talks about why decentralized multi purpose data lakes are the future of data analysis for a broad range of business users.Please attend this session to learn:

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Self-Service Analytics with Guard Rails

Self-service BI promises to remove the bottleneck that exists between IT and business users. The truth is, if data is handed over to a wide range of data consumers without proper guardrails in place, it can result in data anarchy. Attend this session to learn why data virtualization: Is a must for implementing the right self-service BI Makes self-service BI useful for every business user Accelerates any self-service BI initiativeVisit the Packed Lunch Webinar Series page for details on all the sessions.

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Big Data Fabric: A Necessity For Any Successful Big Data Initiative

The best of breed big data fabrics should deliver actionable insights to the business users with minimal effort, provide end-to-end security to the entire enterprise data platform and provide real-time data integration, while delivering self-service data platform to business users.While big data initiatives have become necessary for any business to generate actionable insights, big data fabric has become a necessity for any successful big data initiative. The best of breed big data fabrics should deliver actionable insights to the business users with minimal effort, provide end-to-end...

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A Successful Journey to the Cloud

By 2020, a corporate "no-cloud" policy will be as rare as a "no-internet" policy is today, according to Gartner, Inc. While cloud makes enterprises more flexible and agile, various cloud adoption scenarios such as hybrid cloud, infrastructure modernization and cloud based analytics present a few challenges of their own.Attend this session to learn:Challenges involved with various cloud adoption scenariosHow data virtualization solves cloud adoption challenges while centralizing data governance and security mechanismHow companies are using data virtualization to tackle complex modern customer...

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Self-Service Information Consumption Using Data Catalog

Denodo 7.0 information self-service tool will offer data analysts, business users and app developers searching and browsing capability of data and metadata in a business friendly manner for self-service exploration and analytics.Market research shows that around 70% of the self-service initiatives fare “average” or below. Denodo 7.0 information self-service tool will offer data analysts, business users and app developers searching and browsing capability of data and metadata in a business friendly manner for self-service exploration and analytics.Attend this session to learn:

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In Memory Parallel Processing for Big Data Scenarios

As data volume and variety grows exponentially, Denodo Platform 7.0 will offer in-memory massive parallel processing (MPP) capability for the most advanced query optimization in the market.Denodo Platform offers one of the most sought after data fabric capabilities through data discovery, preparation, curation and integration across the broadest range of data sources. As data volume and variety grows exponentially, Denodo Platform 7.0 will offer in-memory massive parallel processing (MPP) capability for the most advanced query optimization in the market.Attend this session to learn:How Denodo...

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Evolving From Monolithic to Distributed Architecture Patterns in the Cloud

Gartner states in its Predicts 2018: Data Management Strategies Continue to Shift Toward Distributed,“As data management activities are becoming more widespread in both distributed processing use cases, like IoT, and demands for new types of data, emerging roles such as data scientists or data engineers are expected to be driving the new data management requirements in the coming two years. These trends indicate that both the collection of data as well as the need to connect to data are rapidly becoming the new normal, and that the days of a single data store with all the data of interest —...

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3 Reasons Data Virtualization Matters in Your Portfolio

Real-Time Analytics for Big Data, Cloud & Self-Service BIPrivacy, regulations, and the need for real-time decisions are challenging organizations’ legacy information strategy. This webinar will include an expert panel discussion on logical data warehouse, universal semantic layer, and real-time analytics.The world of data is only becoming distributed. Privacy, regulations, and the need for real-time decisions are challenging organizations’ legacy information strategy. This webinar will include an expert panel discussion on logical data warehouse, universal semantic layer, and real-time...

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Parallel In-Memory Processing and Data Virtualization Redefine Analytics Architectures

The tide is changing for analytics architectures. Traditional approaches, from the data warehouse to the data lake, implicitly assume that all relevant data can be stored in a single, centralized repository. But this approach is slow and expensive, and sometimes not even feasible.

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