Wednesday , 18 July 2018
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IDG Contributor Network: Big Data will enable better network and application intelligence in 5G

We are fortunate to live in an exciting time where multiple technological leaps are occurring. Specifically, I am thinking of the mobile industry transition from 4G to 5G, and the cross-industry IT paradigm shift to the Big Data approach. The 5G standards community is already planning to support the collection and transmission of massive amounts of data. This is one of its key requirements pillars in the area of supporting the IoT. What is left, however, is for the 5G community to ensure that the other component of Big Data, namely support for network and application intelligence, is also baked into the 5G architecture. Otherwise, 5G may become simply a pipe for Big Data passing between devices and the cloud infrastructure.

What is Big Data?

Big Data, of course, refers to data sets that are so large and complex that traditional database systems cannot handle them. Big Data also encompasses the techniques for data acquisition, storage, processing, analysis, querying and visualization. Basically, the ability to digest vast amounts of unstructured data in an automated fashion to derive useful insights and to drive automated feedback actions.

The simplest example of a traditional database tool is an Excel spreadsheet, which can interestingly handle up to one million rows and runs on your laptop. At the other end of the traditional database technology spectrum is Oracle DB, which runs on distributed grid computers and can scale to handle hundreds of millions of records. We can intuitively grasp that an Excel spreadsheet cannot handle Big Data, but why couldn’t we scale the underlying grid computer network running Oracle DB to handle Big Data?

The answer to this question lies in the fact that Oracle DB requires all its input data to be structured to fit into pre-defined alphanumerical records. However, in many cases, Big Data is composed of semi-structured or completely unstructured data (e.g., a mixture of text, videos, pictures, and sensor data) which cannot fit into the structure of traditional database systems. This is what makes Big Data systems different. This is where the application of new analysis techniques like machine learning is necessary. These methods allow computers to analyze and make decisions without being explicitly programmed for any particular structure of data.

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