Data Virtualization

Showing 71 - 80 of 207 pages tagged with: Data Virtualization

Myth Busters III: I’m Building a Data Lake, So I Don’t Need Data Virtualization

So you’re building a data lake to solve your big data challenges. A data lake will allow you to keep all of your raw, detailed data in a single, consolidated repository; therefore, your problem is solved. Or is it? Is it really that easy?Data lakes have their use and purpose, and we’re not here to argue that. However, data lakes on their own are constrained by factors such as duplication of data and therefore higher costs, governance limitations, and the risk of becoming another data silo.With the addition of data virtualization, a physical data lake, can turn into a virtual or logical data...

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Trustworthy Analytics and Machine Learning with Data Virtualization (EMEA)

Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. For these projects to be successful, data scientists, business analysts, and other personnel need access to data from across the enterprise. However, gaining access to all of the data in an integrated central repository has been a challenge, resulting in up to 80% of the project time being spent on data acquisition and preparation tasks.Data virtualization enables many organizations today to gain data insights from multiple, distributed data sources...

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How Data Virtualization Puts Machine Learning into Production (APAC)

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 spend 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 session to learn how companies can use data virtualization to:Create a logical...

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A Successful Data Strategy for Insurers in Volatile Times (ASEAN)

Data is an insurer’s most valuable asset. Capitalizing on all of that stored and incoming data to draw valuable insights for business decisions is what ultimately makes a competitive difference.But, insurers face challenges when it comes to modernizing and digitizing their data architectures. Most organizations rely on traditional systems and data integration processes that are time consuming and slow. In addition, as many adopt cloud strategies, these traditional approaches fill the cloud modernization process with downtime and end user frustration.This is why insurers need a flexible and...

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Accelerate Migration to the Cloud using Data Virtualization (APAC)

Organizations are adopting cloud at a fast pace and migration of critical enterprise information resources could be a challenge when dealing with a complex and big data landscape. Building the right data services architecture can help alleviate the pain points, whereby data virtualization comes to the rescue by enabling the companies to gain maximum benefits from cloud initiatives in form of agility, cost savings, and more.In this webinar, you'll learn:How Denodo Platform's multi-location architecture can simplify and accelerate cloud migration.Best practices of deploying the Denodo Platform...

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Mesa Redonda: Cómo acelerar las iniciativas de Big Data con Data Fabric (Spanish)

Según Forrester, el Data Fabric ofrece una vista completa, unificada y confiable de los datos de negocio, mediante la integración de fuentes de datos de una manera automática, inteligente y segura que puede procesar grandes volúmenes de información. Analizamos junto con Kellogg Company, L’oréal, Chubb, Campofrio y El Corte Inglés las claves para que un proyecto de Big Data sea realmente efectivo.Descubre cómo:Asegurar el auto-servicio en una plataforma de Big Data y garantizar el gobierno de los datos.Facilitar la reutilización, exploración y descubrimiento de datos para usuarios.Gestionar...

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Data Virtualization for Business Consumption (Australia)

A successful data virtualization initiative bridges the gap between two very different perspectives of data management: IT and business. However, most of the emphasis in these initiatives is put on the IT side, modeling, performance, security, etc. Business users are often left with a large library of data sets, hard to use and navigate.Denodo’s data catalog has been designed to cover the needs of those users and simplify the use and understanding of the virtual layer from the business perspective. It provides the extra capabilities required for self-service initiatives to succeed, while...

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Data Virtualization for Business Consumption (New Zealand)

A successful data virtualization initiative bridges the gap between two very different perspectives of data management: IT and business. However, most of the emphasis in these initiatives is put on the IT side, modeling, performance, security, etc. Business users are often left with a large library of data sets, hard to use and navigate.Denodo’s data catalog has been designed to cover the needs of those users and simplify the use and understanding of the virtual layer from the business perspective. It provides the extra capabilities required for self-service initiatives to succeed, while...

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Data Virtualization for Data Architects (Australia)

Success or failure in the digital age will be determined by how effectively organisations manage their data. The speed, diversity and volume of data present today can overwhelm older data architectures, leaving business leaders lacking the insight and operational agility needed to respond to market opportunity or competitive challenges.With the pace of today’s business, modernisation of a data architecture must be seamless, and ideally, built on existing capabilities. This webinar explores how data virtualization can help provide a seamless evolution to the capabilities of an existing data...

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Data Virtualization for Data Architects (New Zealand)

Success or failure in the digital age will be determined by how effectively organisations manage their data. The speed, diversity and volume of data present today can overwhelm older data architectures, leaving business leaders lacking the insight and operational agility needed to respond to market opportunity or competitive challenges.With the pace of today’s business, modernisation of a data architecture must be seamless, and ideally, built on existing capabilities. This webinar explores how data virtualization can help provide a seamless evolution to the capabilities of an existing data...

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