What is Big Data Analytics?


A First Look at Big Data Analytics

Meet Zane. Zane has decided that he wants to go to college to get a degree so he can work with numbers and data. After speaking with his academic advisor, he decides to take a class that focuses on data. After just one short week in the class, Zane receives his first assignment. He has to write a paper about big data analytics which is the term used to describe the examination of large amounts of data to see what patterns or other useful information can be found. Come along as Zane learns all about the topic of his first paper.

Big Data Analytics Further Defined

Zane first learns that users of big data analytics not only look at data, but also collect it, organize it, and analyze it for relevant information. The aim is to find patterns, correlations, and information that can help a company make important decisions. Ultimately, the goal of big data analytics is to find all of the knowledge that the data can provide for a company. Scientists, modelers, and many others in the analytics field use big data analytics to sift through large amounts of data that can come from a variety of sources like transactions, web servers, social media, surveys, and even emails.

Importance of Big Data Analytics

So one question that comes to Zane’s mind is, why is big data analytics important? Why would a company use this technique? Well, companies need to make decisions. Making future decisions, finding new opportunities, making business moves, creating a more efficient operation, and even increasing the satisfaction of their customers are all decisions a company could make. Zane learns that big data analytics can help a company reduce costs by identifying more efficient ways of doing those activities.

For example, resorts and casinos use big data analytics to help them make fast decisions. Because we typically only stay at a resort or casino for a short time, it is important to be able to find any potential problems quickly so that the customer is satisfied and returns in the future.

Another example is the healthcare industry. There is a vast abundance of data in the healthcare industry, including patient records and insurance information. Because there is so much data, it can be difficult to manage. Big data analytics allows for a thorough look at the data and can lead to a faster diagnoses or treatment plan.

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