Big Data Storage and Data Virtualization

April 1, 2019

The big data concept has been adopted by all kinds of organizations. Data can be "big" because of its enormous volume, because it's not structured in the traditional way, or because it's streaming in with enormous quantities. The business advantages of big data systems are clear, they can improve, deepen, and strengthen an organization's analytical capabilities with relatively attractive infrastructure economics.Until now the data virtualization servers have focused on making big data processing easy. They can hide the complex and technical interfaces of big data storage technologies, such as Hadoop and NoSQL, and they can present big data as if it's stored in traditional SQL systems. This allows developers to use their existing skills and to deploy their traditional ETL, reporting, and analytical tools that all support SQL. Additionally, the products and existing skills can extend the data security mechanisms for accessing and processing big data across multiple big data systems. Butcwith scale and performance rising, making big data processing easy is not enough anymore. As such, the next challenge for data virtualization is parallel big data processing.

Spotlight

IQM Corporation

Founded in 2013, IQM has designed a leading programmatic political marketing platform. The company specializes in applying a spectrum of advanced technologies for microtargeting, including: (i) alternative and Big Data to identify “swing” voters and their “look-alikes”, (ii) semantic analysis to understand the nature and sentiment of news and political media potential voters consume, (iii) mindset analysis to discover their disposition toward candidates and issues.

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IQM Corporation

Founded in 2013, IQM has designed a leading programmatic political marketing platform. The company specializes in applying a spectrum of advanced technologies for microtargeting, including: (i) alternative and Big Data to identify “swing” voters and their “look-alikes”, (ii) semantic analysis to understand the nature and sentiment of news and political media potential voters consume, (iii) mindset analysis to discover their disposition toward candidates and issues.

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