Introduction
Big data, defined as “a popular term used to describe the exponential growth and availability of data”(What is Big Data? , n. d. ), has attracted considerable interest in many fields as it promises to offer a level of analytic detail that has not been reached so far. Whilst it is often promoted as the solution to many marketing problems, it has some significant disadvantages. Cost, data selection, problems relating to the interpretation of the data and difficulties deciding how to apply the new knowledge to existing products and product design are all important problems.
Situation There is a line chart above from Google Trends which illustrates the searching record (Big Data) from 2005 to 2015.As can be seen, Big Data has
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Probably, Big Data can be the future of marketing. However, there are some problems in using Big Data because of these characteristics. If the enterprises do not know how to address problems, the investment will be wasted while enterprises still search around in the haystack for the needle. Therefore, some problems will be illustrated followed by the solutions for Big Data.
Problems
Firstly, the main problem is deciding which data should be selected. The data, explaining customers’ desires and needs, is important to be collected while most of the enterprises are confusing about what data they should concentrate on. A recent Gartner report (2014) stresses that 64% of firms raced to plan or launch a Big Data project, though they did not have enough professional knowledge yet. To understand what customers need through Big Data possibly turns into the core of companies’ target. The large data volumes and different varieties of data lead to data complexity.
Secondly, the result predicted by Big Data probably may not be true at last. (MARCUS, & DAVIS. 2014).This phenomenon happen frequently in many companies. Take Google Flu Trends as an example, they predicted that the Disease Control and Protection Center was not able to control the spread of flu quickly and effectively as time went on. Later, this conclusion was proved wrong. Hence, it means that future prediction contains inconsistencies compared with reality.
What is big data and how is it defined in today’s modern world? In 2001 Doug Laney Articulated what Big Data meant and this has become the industry standard for the idea. (SAS, 1) More accurately he described the three main attributes that defined Big Data. Laney articulated this idea during a period when Big Data was in its infancy. The amount of Data that could be stored did not allow for the level of analysis that is now common practice fourteen years later. This level of analysis is both changing the way we do business and changing the way we save lives. The amount of data collected from social media alone has completely revolutionized the marketing world allowing for targeted marketing campaigns at certain demographics. Laney described big data in three ways. (SAS, 1)
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
The emergence of big data has provided different avenues for organizations to use data to improve different aspects of their respective operations. Be it customer service, research and development, or market position, Big Data has the potential to be a significant driving force in all these areas. However, there’s still a significant gap between the ability of Big Data to produce insightful analytical information based on real-time data and the ability of organizations to capture and utilize this readily available tool. This is, in part, due to the fact that the systems and processes necessary to fully maximize the usefulness of Big Data is currently lacking in most organizations. This lack of a conducive habitat for Big Data is further magnified in new organizations without any knowledge of Big Data. For organizations that have that have little to no knowledge of Big Data, there must be a thorough assessment of the benefits of big data and how they could improve the organizations overall place in the market. There also needs to be steps taken towards the design of frameworks that will enable the organization to better capture and utilize Big Data.
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.
The industry is inundated with articles on big data. Big data news is no longer confined to the technical web pages. You can read about big data in the mainstream business publications such as Forbes and The Economist. Each week the media reports on breakthroughs, startups, funding and customer use cases. No matter your source for information on big data, one thing they all have in common is that the amount of information an organization will manage is only going to increase; this is what’s driving the ‘big data’ movement.
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
Big data refers to the data sets whose size is bigger than traditional data base tools and contains the ability to acquire, store, manage and analyze data (Watson, H.J., & O. Marjanovic, 2013). Big data often has the following four characteristics, that is to say, it has a vast volume of data, fast transferring and dynamic system of data, a variety types of data and huge value of data. As the development of big data is faster and faster, the use of it also becomes broader and boarder, like researching on customers’ preference, taking it on military use and so on. This essay will mainly discuss the influences big data has on consumers.
The continuous flow of data and information flooding our lives in conjunction with further increases in technology, has created a world of endless possibilities in this day and age. The impact and influences that have been created through big data will shape our lives not only today, but well into the future. This report examines the benefits of big data and the impact it has currently having in our lives as we speak. It also explores the correlation between the lack of knowledge, security and privacy issues we are facing with big data concepts and principles today, and where we will see big data systems in the future.
Big data is a popular term used to describe the exponential growth and availability of data, both structured and unstructured. And big data may be as important to business – and society – as the Internet has become. Why? More data may lead to more accurate analyses. More accurate analyses may lead to more confident decision making. And better decisions can mean greater operational efficiencies.
Big Data has developed over the years new and more complex methods that allows them to see market evolution, their position on the market, the efficiency of offering their services. For being able to accomplish that, a huge volume of data is needed in order to be mined so that it can generate valuable insights.
Additionally, social networking website Facebook, stores approximately 40 billion photos in total. (“Data, data everywhere”, 2010) Besides enormous data that generated from daily operational company transactions and social networks, the price drop of the data storage is also a strong factor triggering the fever of “Big Data”. For example, Google Drive - a cloud based data storage service – had a price drop of approximately 80% from March 2014. This price drop is considered a marketing approach to attract more computer users to adopt Google’s cloud service, which provides a more convenient and efficient way to access and store daily-used files. Although emerge of enormous data provides us opportunities to conduct further investigation and benchmarking, valuable information are not fully extracted and the potential power of using “Big Data” is undermined. In order to achieve thoroughly extraction of useful information from databases, many professionals in the academic field devoted into the study of data analysis and identified two of the most important drawbacks of traditional data analysis, which lacks of predictability and is less flexible in scalability.
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.
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.