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Data Analytics In Wireless And Mobile Communications

T H.
19/02/2018 0 0

Before jumping into the SEA of Data Analytics, let us first understand the difference between Data, Information and need for Data Analytics in Wireless and Mobile Communications.

1. What is Data? What is Information? What causes confusion between the two?

It is a general notion that the terms "data" and "information" are interchangeable and mean the same thing. However, there is a distinct difference between the two words. Data can be any character, text, words, number, pictures, sound, or video and, if not put into context, means little or nothing to a human. However, information is useful and usually formatted in a manner that allows it to be understood by a human

2. What is Data Analytics?

Data analytics (DA) Analytics is the discovery, interpretation, and communication of meaningful patterns in data. It is the process of examining data sets in order to draw conclusions about the information they contain, increasingly with the aid of specialized systems and software.

3. What is Wireless and mobile communication?

a. Wireless Communication: Wireless communication, or sometimes simply wireless, is the transfer of information or power between two or more points that are not connected physically. The most common wireless technologies use is radio waves.

b. Mobile communications: Mobile Communications is the use of mobile phone (an electronic device) for telecommunications over a cellular network of specialized base stations known as cell sites. Mobile Communications offers full Duplex Communication and transfer of link when the user moves from one cell site to another

4. Usage of Data Analytics in Wireless and Mobile Communications:

Mobile Data Analytics (MDA) deals with Data Analytics, particularly Big Data Analytics on-resource-constrained mobile devices. The proliferation of mobile X (commerce, advertisements, learning, crowd sensing, social networks, and gaming) and the Internet of Things has created significant business opportunities that necessitate the adoption of state-of-the-art mobile data processing and analytics solutions.

Such solutions rely heavily on advanced machine learning algorithms to leverage real-time actionable insights, leading to data-driven decision making that can significantly enhance the quality of decisions and user experience. However, although machine learning has advanced significantly over the past decade to perform fast data processing and analytics in stationary computers, leveraging such advancements for resource-constrained, battery-operated mobile devices is a nontrivial task.

Mobile X demands real-time, context-aware data analytics that can be performed by limited mobile processing resources.

All these forms of data are used for various kinds of activities from various applications.

As the usage of technology is increasing day by day, the formation data is also increasing eventually, by which it has become difficult for storing and retrieving data of this quantum.

In order to overcome these problems, we have been continuously developing new data analysis applications such as Like SQL, Python, R-Programing etc. The latest Data-Analytics application is Hadoop-Big Data.

In similar lines to the exponential increase in number of DAA (Data Analytics Applications), there is increase in the complexity of issues being faced. Some of these issues challenge the need for creation of new Analytics Applications and Antivirus. Applications of this magnitude pose a threat to the following, which impact day-to-day activities to a large extent.

  1. Security of data
  2. Only chance of limited data usage by the consumer.
  3. Automatics detection and diagnosis of errors or bugs while performing.

Hence, further research and development of Data Analytics Applications to Wireless & Mobile Communications while addressing the above mentioned issues is very essential for development of Digital Communications towards further progress of the Sector.

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