Big Data Analytics

Showing 1 - 7 of 7 pages tagged with: Big Data Analytics

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

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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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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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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CIO priorities and Data Virtualization: Balancing the Yin and Yang of the IT (APAC)

Today’s CIOs carry a paradoxical responsibility of balancing the yin and yang of the Business – IT interface. That is, "Backroom IT’s quest for Stability" with the “Frontline Business’ need for Agility".A paradox that is no longer optional, but is essential. A paradox that defines the business competitiveness, business survival, and business sustainability. Also enables the visibility to the fuzzy future.“Trusted Data Foundation with Data Virtualization” provides a powerful ammunition in the hands of the CIO, to effectively balance these Yin and Yang at the speed of the business. In a trusted...

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Advanced Analytics and Machine Learning with Data Virtualization (Middle East)

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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Myth Busters I: Can data virtualization uphold performance with complex queries?

In the first webinar of the series, we bust the 'performance' myth.“What about performance?” is usually the first question that we get when talking to people about data virtualization. After all, the data virtualization layer sits between you and your data, so how does this affect the performance of your queries? Sometimes the myth is perpetuated by people with alternative solutions… the ‘Put all your data in our Cloud and everything will be fine. Data virtualization? Nah, you don’t need that! It can't handle big queries anyway,’ type of thing.Watch this webinar to look at the basis of the '...

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