3 Key Points About Big Data Analytics

Last week the WNCG (Wireless Networking Communications Group) of the University of Texas hosted its annual Wireless Summit, aka Texas Wireless Summit. This year’s focus was “Disrupting Wireless through Big Data Analytics.” The academic discussion is something the wizards at Empirix are experts on, so we were excited to be sponsoring the event.

Read: Dear Network: Don’t Drown Me in Data; Inform Me with Intelligence

Big data is transforming the way decisions are being made throughout the organization. It was fascinating to hear attendees talking about how they saw Big Data affecting the future of wireless networks. The conversations touched on the cultural shifts needed to fully adapt the use of data, as well as the tasks of normalizing the volumes of data.

Key Takeaways From the Big Data Discussion

Three key points from the summit are as follows:

  • Data needs to be refined and then refined some more. It needs to become so granular that we can predict network performance and get an idea about which subscribers might be impacted or churn out. Additionally, we will be able to predict their behaviors and the behaviors of the people they may interact with.
  • Machines “talking” to machines is evolving at breakneck speeds. Specifically, the transportation industry will likely be transformed by the way machines communicate with other machines (known as machine to machine – or M2M – technology). Consider a moving object like a car being driven different distances by different drivers to different places. Then include other details, like whether or not a policeperson is there. All of these details drive the data in different ways.
  • Integrating/interoperable data formatting that can be used by the different machines is critical. This is going to be central in making big data environments efficient. Moreover, it will facilitate even more productivity as we define even more ways to use the data available to make decisions.

In order to be efficient and productive, we have to sort out the noise and harvest the most relevant, or “right,” data. Having the right data will allow humans and machines to work together in harmony and ultimately make our experiences in this world better. This is data science, and it’s cool.

Read: Big Data – or The Right Data?

Connecting the Dots

Bridging existing data points and components in the wireless network with the interaction of the subscribers is no small challenge. As I left Texas (where nothing is small, especially not the data), it was good to reconfirm that, in the realm of construction of data structures and analytics engines, Empirix is definitely on the cutting edge. It was also great to facilitate discussion about Big Data and how it will affect the industry, as well as to have an impact on the processes that go into evolving data science.

How do you see Big Data affecting the wireless community? Let me know in the comments below.

Would you like to read a number of Big Data use cases to better understand why it’s important to analyze large volumes of data, look at a variety of data, use near or real time analysis of data, and perform complex operations on data like pattern matching, learning from many events, etc.? Read Big Data LTE.

Contact Empirix today to uncover new ways for mobile operators
to analyze subscriber behavior, by application, in real-time to successfully
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Written by Jason Miller – Jason on Twitter | Posts by Jason
Jason is Empirix’s expert on predictive analytics, big data, and cutting edge technologies like WebRTC and VoLTE. He has lived on both the customer and the vendor side of things so he has a unique perspective of the market. In his free time he also coaches Little League.

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