Big Data Is Not Without Its Own Problems

Big Data is an expansive phrase for data sets so called big, large or complex that they are very difficult to process using traditional data processing applications. Challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and information privacy. In common usage, the term big data has largely come to refer simply to the use of predictive analytics. Big data is a set of techniques and technologies that need or require new forms of integration to expose large invisible values from large datasets that are diverse, complex, and of a massive scale. When big data is effectively and efficiently captured, processed, and analyzed, companies

The promise of data-driven decision-making is now being recognized broadly, and there is growing enthusiasm for the notion of ``Big Data.’’ While the promise of Big Data is real -- for example, it is estimated that Google alone contributed 54 billion dollars to the US economy in 2009 -- there is currently a wide gap between its potential and its realization.

What is Big Data? Big Data is the mass collection of user data by mathematical algorithms, databases, data mining, and the use of datasets that were once believed to be static and unusable. Big Data’s history goes way back “…70 years to the first attempts to quantify the growth rate in the volume of data, or what has popularly been known as the “information explosion” (Press, Gil).” Researchers had predicted the massive growth of information and how our ability to collect and store it would need to continue to grow as well.

Today we live in an era of tremendous technological change. Our life just a few years changed the Internet, wireless technologies, mobile devices and cloud computing. It changes the way companies build the architecture of IT systems that support their business. This changes the role of the CIO in the company and determines the degree of penetration of new technologies in every aspect of operations.

Even as organizations are embarking on big data initiatives, many still have several vision and

Abstract—The important goal of this paper is to provide an overview on the concepts of big data analysis. Furthermore the growing emergence and importance of qualitative data analysis in the field of business intelligence and data science is broadly explained .It also marks out effective tools and techniques used to obtain prominent qualitative analytic results on the global level. Moreover we have concluded on the basis of comparison of the tools depending on various factors and parameters by representing it on a tabular manner.

"Such ‘Data Explosions ' has led to one of the most challenging research issues of the current Information and Communication Technology (ICT) era: how to effectively and optimally manage such large amount of data and identify new ways to analyze large amounts of data for unlocking information. The issue is also known as the ‘Big Data ' problem, which is defined as the practice of collecting complex data sets so large that it becomes difficult to analyze and interpret manually or using on-hand data management applications. From the perspective of real-world applications, the Big Data problem has also become a common phenomenon in domain of science, medicine, engineering, and commerce"

Big Data is all around us, from creating our anniversary videos on Facebook and giving Netflix recommendations to utilizing all cellphones as weather stations to improve predictions (source 4) and combining it with machine learning for interesting insights. (source 5) All this data needs to be processed, creating a multitude of jobs in the data science field. Companies with products relying heavily in internet are investing heavily in Big Data, companies such as Uber, Spotify, Google and IBM to name a

Big Data is now going to be the mainstream, as a result various new technologies have come into the market. The table below is an overview of them:

Big Data has gained massive importance in IT and Business today. A report recently published state that use of big data by a retailer could increase its operating margin by more than 60 percent and it also states that US health care sector could make more than $300 billion profit with the use of big data. There are many other sectors that could profit largely by proper analysis and usage of big data.

According to a report from The International Business Machines Corporation, known as IBM, 90% of the data in the world has been generated in the last two years. Frank J. Ohlhorst (2013) explains how the concept of collecting data for use in business is not new, but the scale of data that has been collected recently is so large that it has been termed Big Data (p. 1). Company executives who choose to ignore Big Data are denying their companies an advantage over their competitors. Big Data analysis is fundamental for all fields of work; it provides an insight to large amounts of data that will answer questions and make discoveries to improve efficiency in all areas of the world.

Big data is defined as “large data sets or to systems and solutions developed to manage such large accumulations of data, as well as for the branch of computing devoted to this development.” (“Big Data”) This definition of big data was not added to the dictionary until 2014. The next big thing in business analytics is a relatively new, yet, explosive business practice known as data mining: the collection and analysis of big data. (Fayyad) These large, seemingly random, sets of data are condensed and analyzed for patterns and trends by people with a very broad set of skills. These people are known as data scientists and are considered unicorns in today’s job market.

Big Data is changing the way business decisions are made. It is no longer a passing fad and if companies are not extracting insights from the data collected, they will be left behind by their competition.

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

Management of Big Data is useful with how one handles the information. Ways to use the stored information include, but not limited to, reduction of costs, time reductions, and making smart decisions based on data results. [1]