Big Data

“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.” (SAS, 1)

They used facts and arguments from various sources, such as studies and authors. As they are introducing the topic, they use the ideas of Lev Manovich to justify their argument that the name “Big Data” can be misleading. Manovich observed that Big Data has been used to refer to data sets large enough to require supercomputers, yet large amounts of data can now be analyzed on much simpler computers. Boyd and Crawford contend that the value of the industry does not simply come from the large data sets, but the “patterns that can be derived by making connections between pieces of data…” By relating Manovich’s idea, their argument made more sense. As computers become more advanced, bigger data sets look much simpler. But the connections Big Data makes are still valuable, no matter how advanced computers

The increasingly popular terms “big data” and “predictive analytics” have become so widely discussed that, in many ways, they lack a cogent meaning – even within the financial industry. The Capstone team used the literature review as an opportunity to scan the field for defining characteristics, resulting in a suggested guide for how the Federation should articulate these concepts. Generally speaking, big data is about the growing availability of data, as well as the tools needed to analyze the information. Predictive analytics refers to the analysis of big data which can help uncover patterns, correlations and trends that were otherwise unknown to the organization. Predictive analytics is also known as

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

There is at least one field that is largely underutilizing big data and big analytics. This field is small business. Small businesses provide more than half of the jobs in the U.S. (Baldwin, 2015, para. 1), and yet, many of these businesses do not take advantage of the information that big data and big analytics can provide them. There are many ways big data and analytics can increase profits for small businesses, as long as these small businesses identify the opportunities that allow big data to work for them and as long as they work through the challenges that discourage small businesses from utilizing big data and analytics. This paper will discuss these opportunities and challenges in detail.

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

As a large, multi-national financial institution, BAC / ML is at the forefront of the analytical revolution. In an interview with PriceWaterhouseCoopers (PWC) , Brian Moynihan discusses how technology can improve operational efficiency. This is a point that Davenport & Harris make in “Competing on Analytics” - that in today’s market, efficient and effective execution are one of the strategies that can pay off in separating a company from its competition. Mr. Moynihan further speaks to how big data analysis is one of the tools that can provide the intelligence needed to achieve some of their strategic goals. As one of the world’s largest banks, BAC/ML certainly has the funds and resources to bring this intelligence to bear - provided that

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.

Over the past two years there have been a lot of conversations about the era of big data. There have been numerous hearings in Congress and federal agencies, countless news stories, and multiple reports from the White House. Most of the public discourse has been around commercial and corporate uses of big data to make decisions that could be personally intrusive, harm or discriminate against individuals. The Wall Street Journal ran a report about pricing by Staples.com, in which the company’s algorithm was changing its pricing online after estimating a user’s location relative to a Staples’ competitor. In another instance, Target came under fire for its marketing algorithm accurately sending a teenager information about pregnancy.

The aim is to review the current ways of storing and obtaining data and compare them and determine the methodology used. Look into future methodologies and new developments in the industry. It is also crucial to assess how big data is already used and implemented into certain organisations. How the organisations improve their own businesses with this data and how it could help their clients with similar interests.

The world is changing with respect to the growth in big data and to the way in which it is used. Growth in big data brings with it many challenges, but it also presents new opportunities. Figure 1, helps understand some of the big data related activities that are taking place in the world with respect to volume of data that is being consumed by these activities over the next 5 years.

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 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.

Big Data embraces structured, semi-structured and unstructured information. It can be demographic or psychographic information about the customers, their opinions, product reviews etc gathered from variety of sources such as tweets, blogs, other social media content, technical devices like sensors and stream of data from mobile devices. Businesses have started using Big Data to get right information to identify right markets and right customers at the right time in order to make right strategic decisions. The Big Data market is estimated to grow to $32.1 bn by 2015 and $54.1 bn by 2017. According to the report “Be Careful or Big Data Could Bury Your Bank”, the world creates 2.5 quintillion bytes of data daily and last 2 years have contributed to almost 90% of the data which exists today. It empowers institutions to learn more, create more and do more using the data available with them.

There are lots of opportunity associated to big data that help any organization to handle their large amount of data, like in financial sector it store data related to finance, healthcare sector it store health related patient records, doctors detail and medicine ,medical equipment related details . In retail sector it is also used [5]. Web/social media/mobile companies also use it for storing their user detail and data like their likes, search pattern, calling and messaging records. Manufacturing and government sectors also use it.