Unraveling the Data Lake: MPP integration within a Logical Data Fabric

With the appearance of cloud object storage services like AWS S3 or Azure ADLS, the data lake has seen an upturn in usage as some of the challenges of the original idea were addressed. However, companies across the globe still find it challenging to adopt data lakes into the corporate data ecosystem. While almost infinite in storage, data retrieval from these sources and integration of the data with the corporate ecosystem is still an arduous task for data engineers.

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Design Guidelines for Data Mesh and Decentralized Data Organizations

In recent years, there has been a significant push towards decentralized data organizations where different domains are partially or fully responsible for exposing their own data for analytics.

Join us in this session with Daniel Tenreiro, Sales Engineer at Denodo, in which he will share important design guidelines and best practices that can be used to implement many of the decentralization principles, such as the ones defined by the popular data mesh paradigm, using the Denodo Platform, powered by data virtualization.

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Securitizing data using fine-grained privileges in multi-layered virtual models

Securitizing data is one of the most important tasks in an organization. Denodo can offer a wide range of data, gathering data from different sources, and delivering this data to many client applications and final users. When returning the data, Denodo provides several options to securitize the data, and just let the right users and client applications read this data. One of the options for achieving this purpose is using fine-grained privileges over the view.

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Surpassing Element by Element Access Control: Semantic-Based Security Policies

Security of data in an organization is becoming more and more important. With a plethora of tools for storing and accessing many different data sets, securing an organization's data assets can quickly become a daunting task. Not only will this be hard on database administrators and data engineers, but it could also lead to mistakes and in the worst case data breaches.

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Development Strategy and Best Practices with Denodo

Are you looking to define a development strategy for your organization based on the best practices? Thinking about how to establish a structure for your project? Are you modeling the metadata in the right way?

Join Varun Prasan Keshar (Data Engineer, Denodo) to get directions on how different development strategies can be implemented with Denodo along with the Best Practices.

This session would revolve around the following topics:

  • Organizing Projects with Denodo
  • Structuring the Metadata
  • View Development

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Denodo Solution Manager: Best Practices for Promotion

What is the best way to manage metadata promotion? How do organizations seamlessly promote the metadata, users, and their permissions? How can administrators guarantee the stability of the service in the event of failure?

Join us for this session with María Sordo, Technical Account Manager, Denodo, and get key insights on how to promote the metadata using Solution Manager and walk away with best practices and practical tips.

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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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