Business Intelligence Journal Of Big Data

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

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

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 big data analytics is not only limited to the information technology department this kind of belief makes most of the supply chain mangers to ignore the economic value of the data which have been collected. The main things that most of the supply chain mangers should know is that they should have a large access of data which only have the economic value. They also should protect that data they have so that the data cannot be viewed by their competitors since their competitors will know the economic value of the data they have collected. Another very important aspect that most of the suppliers should know about large data which they have collected is how to creatively use the data to make decisions which will make their work easier. This is because most of the mangers have access to these data but they do not use the data to help them in making major decisions.

Our conclusion that big data will help marketing and advertising departments is based on the gathered information from many secondary sources. These secondary sources are almost all scholarly.

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.

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.

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 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 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.

Big Data has taken the business world by storm. By 2020, it is expected that the amount of digital information in existence will have grown from 3.2 zettabytes in 2014 to 40 zettabytes. Companies are doing all they can to capture this digital information and turn it into actionable insights. Currently, the total amount of data being captured and stored by industry is doubling every 1.2 years. Therefore, companies must find increasingly efficient solutions to store and analyze this incredible amount of 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 a new innovation. Processing big data and converting it into useful information can result in many benefits to a company such as increase its profitability, improve their business practice. Companies do spend lots of resources to harness this new technology. “Google Spent $7.3 Billion on its Data Centers in 2013. (Miller, 2013)” Big Data is regularly being generated by our activities such as surfing internet, using social media, blogs etc. Every digital process leaves a trail of information about consumers and their behaviour. These consumer behaviour and purchasing patterns can be used to visualize information. The big companies use big data to improve their customer’s

The big data techniques allow the provision of the quality and dignified products to the customers. The data and information obtained regarding a given client provide the particular taste and preference of the individual clients. The information obtained enables the banking institution to focus on specific services and the products demanded by their client. The dedicated service to the specific clients attracts the clients and improves the friendship relation between the client and the bank.