Strategies for Fitting a Data Lake into a Modern Data Architecture

Whether to take data ingestion cycles off the ETL tool and the Data Warehouse or to facilitate competitive Data Science and building algorithms in the organization, the Data Lake a place for unmodeled and vast data will be provisioned widely in 2019. Though it doesn’t have to be complicated, the Data Lake has a few key design points that are critical, and it does need to follow some principles for success. Avoid building the Data Swamp, but not the Data Lake! The tool ecosystem is building up around the Data Lake and soon many will have a robust Lake and Data Warehouse. We will discuss policy to keep them straight, send “horses to courses,” and keep up users’ confidence in the Data Platforms.
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Spotlight

OTHER ON-DEMAND WEBINARS

Journey to the Cloud, Self-Service BI, and Data Lakes with Data Virtualization

denodo

Denodo DataFest, the premier agile data management and analytics conference, returned once again to New York and London in 2018. Our annual user conference brings together industry analysts, subject matter experts, business leaders, data management leaders to discuss data strategies to enable a successful journey to the cloud, self-service BI, and data lakes with data virtualization. The event invited attendees to watch demos, hear customer success stories, and educate themselves on the best practice implementations of data virtualization.
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Moving from centralized data platform to a federated data mesh

In this webinar, we will cover the pros and cons of building a centralized data lake vs federated data mesh. Traditionally data warehouses are built on the premise of centralized data. This requires team, process and tool alignment which adds significant complexity and layers of process. Oftentimes the internal conflicts lead to subpar data management and quickly fragments to siloed data processing and insights. We will provide our unbiased view on building federated data mesh and the benefits of building an operational metrics layer.
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Implementing Oracle Database-as-a-Service for Cloud-Like Agility

Robin Systems, Inc

A growing number of organizations are turning to Docker containers to help solve really big application requirements. Among the biggest out there are those imposed by Oracle and Oracle RAC. What if you could deploy Oracle or Oracle RAC as a stateless cloud-native workload in your environment? Transform a complex process into one with an App Store-like experience.
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Cloud Data Strategies for Mission-Critical, Distributed Applications

When organizations need to move quickly to launch new, digitally transformed applications that rely on terabytes (if not petabytes) of data, they cannot afford to wait for legacy database management systems to catch up. Cloud computing platforms give organizations the ability to stand up systems quickly, but if the data layer cannot offer the linear scalability, low latency, high availability, performance, fault tolerance, security, and agility needed for today’s 24/7 applications, organizations will never realize their objectives.
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