Data Science & Big Data Analytics

byWriter •September 13, 2022

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Data Science & Big Data Analytics Discovering, Analyzing, Visualizing and Presenting Data

Data Science & Big Data Analytics

Big Data Overview

Data is created constantly, and at an ever-increasing rate. Mobile phones, social media, imaging technologies to determine a medical diagnosis—all these and more create new data, and that must be stored somewhere for some purpose. Devices and sensors automatically generate diagnostic information that needs to be stored and processed in real time. Merely keeping up with this huge influx of data is difficult, but substantially more challenging is analyzing vast amounts of it, especially when it does not conform to traditional notions of data structure, to identify meaningful patterns and extract useful information. These challenges of the data deluge present the opportunity to transform business, government, science, and everyday life.

Several industries have led the way in developing their ability to gather and exploit data:

Credit card companies monitor every purchase their customers make and can identify fraudulent purchases with a high degree of accuracy using rules derived by processing billions of transactions.
Mobile phone companies analyze subscribers’ calling patterns to determine, for example, whether acaller’s frequent contacts are on a rival network. If that rival network is offering an attractive promotion that might cause the subscriber to defect, the mobile phone company can proactively offer the subscriber an incentive to remain in her contract.
For companies such as LinkedIn and Facebook, data itself is their primary product. The valuations of these companies are heavily derived from the data they gather and host, which contains more and more intrinsic value as the data grows.
Three attributes stand out as defining Big Data characteristics:

Huge volume of data: Rather than thousands or millions of rows, Big Data can be billions of rows andmillions of columns.
Complexity of data types and structures: Big Data reflects the variety of new data sources, formats, and structures, including digital traces being left on the web and other digital repositories for subsequent analysis.
Speed of new data creation and growth: Big Data can describe high velocity data, with rapid data ingestion and near real time analysis.