The Big Data Essay

Big data and its definition has changed over the years. In a 2011 research project by MGI and Mckinsey’s Business’ defined big data as

Big Data is the act of compiling large sets of data based on a single individual or groups. Everyone encounters data in their daily life--you are experiencing it when you log onto a social media account, when you stream entertainment online, or even when you are online shopping. When you do any of these things you are leaving behind a digital trace that can be accessed by just about anyone. In “Six Provocations for Big Data,” danah boyd and Kate Crawford raise questions regarding the nature of Big Data. What is considered public information? What is the ethical way to go about retrieving data from online sources? Is Big Data more harmful or helpful? How often do you encounter Big Data, or data in general? What is the relationship between data

Data is a forever growing thing and is not looking to slow down anytime soon. With that be said, companies must be able to manage data for their day to day operations as well as for predicting future trend. Now there are many tools for managing data and extremely high cost for managing it as well. One of the costs for managing data is data security, but this paper will touch on that topic in, but not as much as other topics. Also, this paper will demonstrate various business cases to serve as testimonial for just how useful big data management it in to day society.

In a fast paced, business ordinated technological world the overall welfare of a company is tied to the success or failure to make the tough decisions. On one instance a company’s CEO might be able to make the choices based on experience, advice, or simple gut instinct. However, this is not the only skill one needs. There is a great deal of information to be found in being able to see investments in data and analytics. These decisions are based off of big data. Big data is a catch-phrase, used to describe a massive volume of both structured and unstructured data that is too large to process using traditional database and software techniques. The volume of data is in most cases is too big, moves too fast or it exceed the processing capacity the company has. Despite these potential drawbacks, big data contains the potential to help companies by improving operations and making faster, more intelligent decisions. This can be broken into three key parts, knowledge, data, and information.

Big Data is garnering great recognition for its data-driven decision making methodology. Right from data acquisition where there is a flood of data available, we need to make effective decisions about usage of data. Privacy, scalability, complexity and timeliness are the problems that hinder the progress of Big Data.

Now that we have figured out how to harvest the free and ubiquitous big data, the next huge challenge is to figure out how to analyze and display the information in a useful and meaningful way. The big question today is how you present big data in a way that human beings can quickly understand and make decision. Most big corporations and government entities are drowning in a pool of their own data, because they lack the corresponding manpower to understand the data and extract meaningful knowledge out of it (Bizer, Boncz, Brodie, & Erling, 2012).

Big data is not as new as many people believe it to be. It is actually a concept that has been around for almost a century. It is just the “same old data marketers have always used, and it’s not all that big, and it’s something we should be embracing, not fearing” (Arthur). In 1944, Fremont Rider “predicted that the amount of data in the world would increase exponentially” (Hopp). Rider was right on target with his prediction seventy years ago. Data has grown much greater than he probably could have ever imagined back then.

The ever-increasing advancements in technology, and the way in which we are aiding in the creation of more and more data every day, there’s an idealism that we analyse this information to provide meaningful results, whether it be in our jobs or to support our businesses. The benefits of using and supporting big data will lead to a greater competitive advantage and “will become the basis of competition and growth for individual firms, enhancing productivity and creating significant value for the world economy by reducing waste and increasing the quality of products and services” (McGuire, Manyika and Chui, 2012), now and in the future. However, there is also some issues that may arise that businesses will need to address, particularly in privacy and security, in which risk management strategies will need to be implemented.

The guarantee of information driven choice making is presently being perceived extensively, and there is developing excitement for the thought of ``Big Data. ' ' While the guarantee of Big Data is genuine for instance, it is assessed that Google alone contributed 54 billion dollars to the US economy in 2009 - there is right now a wide crevice between its potential and its acknowledgment. Heterogeneity, scale, convenience, intricacy, and protection issues with Big Data block progress at all periods of the pipeline that can make esteem from information. The estimation of information blasts when it can be connected with other information, subsequently information combination is a noteworthy maker of quality. Since most information is directly produced in advance today, we have the open door and the test both to impact the creation to encourage later linkage and to naturally interface already made information. We trust that fitting interest in Big Data will prompt another rush of central mechanical advances that will be epitomized in the following eras of Big Data administration and investigation stages, items, and frameworks. The interest in Big Data, legitimately coordinated, can result in major investigative advances, as well as establish the framework for the up and coming era of advances in science, solution, and business.

We live in the times of Big Data, with the number of people connected to multiple devices and sensors all with digital networks and individual data that can now be largely collected and analysed to understand the important phenomena Big Data. In the retail market, individual purchase histories are used by recommendation tools to learn trends and patterns. Performing analytics on private data is clearly beneficial, such as early detection of disease and recommendation services. However, user concerns rise from a privacy perspective, with sharing an increasing amount of information regarding their health, location, service usage, and online activities. [4]

Big data is an extensive collection of structured and unstructured data. It is a modern day technology which is applied to store, manage and analyze data that are not possible to manage, store and analyze by using the commonly used software or tools. Since all of our daily tasks are overtaken by the modern technologies and all the businesses and organizations are using internet system to operate, the production of data has increased significantly in past

ig data is a large amount of data, structured as well as unstructured, that records or entails information about business on a daily basis (“Big data: What,” n.d.). This huge amount of data contains information about different aspects but not all this information is important to us, therefore, mining for information through such a large amount of data is a very important step. Most of the time, the magnanimity of such data is so much that it is difficult to process it using conventional database and software programs (Beal, 2016). In this age of modernization, the fame and popularity of the term “Big Data” is constantly increasing. Owing to its renown and eminence, Oxford English Dictionary added it in 2013 and it also appeared in Merriam-Webster’s Collegiate Dictionary (Dutcher, 2014).

Big data is a vast amount of information, both structured and unstructured, unstructured is information that is not simple to interpret by traditional databases and structured information is the opposite, which is not too difficult to interpret data made form text or image. Structured or unstructured, the main business of big data is categorized

Big Data: As the name proposes that it is "Enormous". Every one of us are acquainted with GB (Giga Bytes) and TB (Tera Bytes). Both of these terms are utilized regularly, regarding memory sizes. Not many know about Peta Bytes (PB) and Exa Bytes (EB). 1 EB is equal to 10^6 TBs (1 million TBs / 1 Billion of GBs). The measure of Big Data begins at the point, where a typical man 's reasoning stops. Every day, nearly 3 EBs of data is continuously produced and one of the main Market Research firm has affirmed that 1200 EB of information was created in 2012 alone. This information needs to be tamed from the viewpoint of Economics and need to be

This article discusses firms that are at the leading edge of developing a big data analytic capability. Business firms and other types of organizations are feverishly exploring ways of taking advantage of the big data phenomenon. Big data is increasingly the cornerstone on which policy making is based. Firms that are currently enjoying the most success in this area are able to use big data not only to improve their existing businesses but to create new businesses as well. This transformation process results in power shifting to analytic experts and in decisions being made in real time. This set of symposium articles, authors examines the promise and problems of big data from a variety of perspectives.