Denodo Packed Lunch Series

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Big Insights from Your Big Data using Data Virtualization

Data lakes have grown to be a popular architecture that enables modern analytics and data science. However, complete replication of all corporate data into giant data lakes is unfeasible. Data volumes are too high, and replication to multiple systems creates brittle point-to-point connections. Out-of-synch data and uncontrolled replication leads to “data swamp” scenarios. On top of the physical data lake, a logical approach is more feasible: a logical layer that connects different systems (the data lake among them) and exposes them as one. The complexity of the back-end systems is hidden from...

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Accelerate Migration to the Cloud using Data Virtualization

Organizations are adopting cloud at a fast pace and migration of critical enterprise information resources could be a challenge when dealing with complex and big data landscape.

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Enabling Self-Service Analytics with Logical Data Warehouse

What makes data scientists happy? Of course data. They want it fast and flexible, and they want to do it themselves. But most classic data warehouses are not easy to deal with for agile data access.

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Data Virtualization: An Introduction

What started to evolve as the most agile and real-time enterprise data fabric, data virtualization is proving to go beyond its initial promise and is becoming one of the most important enterprise big data fabrics.

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Advanced Analytics and Machine Learning with Data Virtualization

Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. Platforms like Spark, and complex libraries for R, Python and Scala put advanced techniques at the fingertips of the data scientists. However, these data scientists spent most of their time looking for the right data and massaging it into a usable format. Data virtualization offers a new alternative to address these issues in a more efficient and agile way.Attend this webinar and learn:

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