Problems Of Using Big Data Help Us Understand What Customers Want?

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

Despite the potential challenges, it is still believed that big data is the new way of the world, and that businesses should aim to overcome these challenges. The first typical challenge small businesses will face is finding “talented people who know big data and analytics” (Taylor, 2012, para. 6). Unfortunately, since small business owners tend to not be familiar with big data, then they will be challenged to know how to use it. Big businesses have the money, reputation, and influence to hire people who are very knowledgeable with big data. Also, if the storeowner is technologically challenged, it’ll be even harder for him/her to know how big data can help him or even what big data is in order to go out and look for someone to help his/her store with big data. Even if the storeowner is comfortable with technology and is familiar with big data, the storeowner could be averse to change, and that would be another reason why using big data would be a challenge for this category. The storeowner who is used to doing things a certain way will not be eager to start using big data to improve his business. S/he will probably think that if the business is doing well, then they don’t need to change. This will prevent them from increasing profits and will stagnant them from keeping with current times and current technology. For

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

Business thrive when they have the most accurate, up-to-date, and relevant information at their disposal. This information can be used for a plethora of pertinent markers in small and large businesses, relating to accounting, investments, consumer activity, and much more. Big data is a term used to describe the extremely large amounts of data that floods a business every day. For decades, big data has been a growing field, facing controversy on many levels, but as of late, it has been a major innovator in the challenge of making businesses more sustainable. Big data is often scrutinized for its over-generalization and inability to display meaningful results at times. When applied correctly, data analysis can bring earth-altering information to the table.

Big data affects in a different way depending on how privacy, security and welfare influence to the customers. There are different types of consumers depending on

Not only the development of Big Data brings big opportunities, but it also brings big

Big Data can analyze a customer’s purchases, profile information, and make an accurate prediction on what his/her interests will be. Big Data has the potential to be the phenomenal tool of the future. It can accurately predict what a customer wants and show advertisements that he or she is actually interested in; It can be installed in smart cars, where an automatic distress call is sent when an unlucky individual is in a car accident; It can be uploaded to devices that closely monitor people’s health and report any irregularities to their doctor.4

The amount of data in our world has been rapidly increasing and analyzing these large data sets, or big data, has become crucial for businesses in increasing their success. Many businesses use big data to model their business structures, control processes, and run the business. The availability of this data leads to a more accurate analysis of the target market. More accurate analyses lead to more confident decision making and better decisions means greater operational efficiencies, cost reductions and reduced risk. There are many ways in which big data can be successfully implemented in an organization. Big data allows businesses to segment their target market, creating more precisely tailored products and services. Big data is also used to conduct controlled experiments to make better management decisions. Finally, big data can unlock value by making the captured information transparent and usable at much higher frequency (Manyika, “Big data: The next frontier for innovation, competition, and productivity”).

Big Data is defined as data sets that are so large that they defy conventional applications, frameworks and methods for analyzing them. The proliferation of Big Data is attributable to the amount of data companies across all industries are capturing on transactions with suppliers, customers, distribution channels and services organizations over years of activity. Big Data, by its very nature of spanning a multitude of databases and conventional data storage platforms within organizations, becomes difficult to capture, store, search and complete analytics on. For the manager in an organization who has these conventional methods of data search, analytics and visualization available to them, Big Data can quickly become overwhelming given the limited scope of tools available and the sheer amount of data available (Jacobs, 2009). For the manager attempting to gain greater insights into their organization's processes, strategies and overall performance, Big Data can quickly becoming overwhelming. The intent of this analysis is to provide guidance to managers on how they can better manage Big Data to provide the maximum analytical insight and intelligence about their organizations.

Wolfsen (2013) asserts that it will attract more customers as customers would like to get their service done in less time. To minimize the time of customers spending on purchasing, one of the most efficient way is through big data. Matthew (2014) suggested that the technology of big

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.

The term big data came into the picture to refer the big volumes of information’s both the companies and governments are storing. The data may be where we live, where we go, what we buy and what we say etc. all will be recorded and stored forever. More than 90% of data is generated in the past 2 years only and this volume is increasing day by day and doubling for every two years. In this world, the organizations are using the data generated by us and no one knows what they are doing with the collected data. Big data is defined as a lot of structured and unstructured data from different sources, such as E-commerce websites, online transactions, social networks, medical records, internet search indexes, banking and financial services, scientific searches, weblogs, and document searches and so on. Big data also can be described by four V’s: Volume, Velocity, Variety and finally Value.

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.

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.

In today’s world, the amount of unstructured data collected is humungous. This unstructured data is of no use if it is not properly processed, analyzed and evaluated. Using this data for the betterment of mankind is what most of the largest companies like Google, Facebook, Amazon, Netflix and much more are targeting. Big data is a term for datasets which are so large and complex that traditional database systems such as MS SQL, MySQL, etc., are incapable of handling them. It is not the amount of data that is important, but what organizations do with data that matters the most. Data can be mapped to useful information which can be further utilized for analyzing and drawing insights that lead to better management practices and strategic