Accelerate your Data Science Ops using Denodo

Data Scientists are often in need of data from many datasets to get proper insights for their AI / ML needs. Even if they figure out the location of their datasets, accessing, transforming and having the ability to store in a single place for frequent access is often difficult and time intensive. With Denodo Platform, you can easily apply the transformations and then make it available for your end users. Additionally, you can also automate this process using our Scheduler jobs.

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Self Service Analytics enabled by Data Virtualization from Denodo

Self-service Analytics BI is often quoted by many - ie, allow users to discover and access data without having to ask IT to create a data mart, or by allowing users to directly export/copy the data from the data sources themselves into their analytics tools and systems.

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Maximizing Data Lake ROI with Data Virtualization: A Technical Demonstration

Companies with corporate data lakes also need a strategy for how to best integrate them with their overall data fabric. To take full advantage of a data lake, data architects must determine what data belongs in the Lake vs. other sources, how end users are going to find and connect to the data they need as well as the best way to leverage the processing power of the data lake. This webinar will provide you with a deep dive look at how the Denodo Platform for data virtualization enables companies to maximize their investment in their corporate data lake.

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Enabling Real-Time Analytics in Today's Complex Enterprise Data Environments

Achieving the goals of real time analytics in today's increasingly complex enterprise data environments poses numerous challenges. Most organizations today require efficient access to integrated data assets across a wide variety of on-prem and cloud data sources.

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Building a Consistent Hybrid Cloud Semantic Model In Denodo

Many businesses are moving to the Cloud. This process can take many years with data spanning On-Prem and Cloud. When Denodo needs to be deployed in a Hybrid Cloud Architecture, how should one implement that?

Join this session to get a deep dive look at how to create a shared Virtual Database that exposes a consistent Semantic Model using Denodo’s Interfaces. Both On Prem and Cloud will have their own Virtual Databases.

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Denodo: 3 Key Data Fabric Operational Features

In Gartner's 2020 research paper: Demystifying the Data Fabric, Gartner discusses that the core of the data fabric is able to consolidate many diverse data sources in an efficient manner by allowing trusted data to be delivered from all relevant data sources to all relevant data consumers through one common layer.

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Denodo Design Studio: Modeling and Creation of Data Services

Change is the only constant and it is very important for enterprises to keep up with the changing times in an agile fashion. To ensure faster time to market, quick business insights and rapid data driven decision making, it is important that the Data Delivery channel is optimized in the best way possible.

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Denodo’s Data Catalog: Accelerate AI/ML Modeling with Faster Access to Datasets

Data Scientists spend most of their time looking for the right data and massaging it into a usable format. How can the Denodo platform enable the data scientist and data engineer?

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