Introduction. Big Data Is One Of The Most Discussed Concepts

Every day, we produce 2.5 quintillion bytes of data. 90% of all data in the world was produced in the past two years. Data has been around forever; we have always gathered information. Paleolithic cavemen recorded their activities by carving them in stone or notching them in sticks. Egyptians used hieroglyphics to record significant events in history. The Library of Alexandria was home to half-a-million scrolls of the ancient world. Less than hundred years ago, we used punch cards to record and store information. As technology continues to evolve, the amount of data we store continues to grow. We’ve come a long way since stone tablets, scrolls, and punch cards. It’s important to understand the concept of big data and the impact is has created. This paper will define the classifications of data, explain the challenges of big data, and describe how big data analytics is being used in today’s data driven world.

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.

1, Data raw facts, such as an employee 's name and number of hours worked in a week, inventory part numbers, or sales orders .several types of data can be used to represent these facts

The big data phenomenon is about collecting and storing large amounts of data and running analytics application ns on these large datasets.

This paper will look at some of the ‘Big Data’ being implemented today. Regardless of ow anyone feel, ‘Big Data’ s a thing that is not going away. This paper will look at Video and Image Data, Audio Data, Textual Data, Managerial Accounting.

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”).

What is big data? Big data is structured and unstructured data that is difficult to process using traditional database and software techniques. This is because of its extensive size. Big data ranges “from a few dozen terabytes to many petabytes of data in a single data set – and are constantly growing” (Hopp). A terabyte is equal to 1,024 gigabytes, while a petabyte is equal to 1,024 terabytes. A regular iPhone has 16 gigabytes, so a terabyte contains the same amount of digital storage as 64 iPhones, while a petabyte contains the same amount of digital storage as 65,536 iPhones! Structured data is in a fixed field within a record or file (usually databases or spreadsheets). Unstructured data is unorganized and hard to interpret by traditional databases or data models (like photos, webpages and emails). Structured data is a lot easier to work with and can be easily classified, so it is preferred in big data over unstructured data.

big data is a dynamic that seemed to appear from almost nowhere. But in reality, Big Data is not new – and it is moving into mainstream and getting a lot more attention. the growth of Big Data is being enabled by inexpensive storage, a proliferation of sensor and data capture technology, increasing connections to information via the cloud and virtualised storage infrastructure, as well as innovative software and analysis tools. It is no surprise then that business analytics as a technology area is rising on the radars of CiOs and line-of-business (lOB) executives. to validate this, as part of a recent survey of 5,722 end users in the uS market, business analytics ranked in the top five It initiatives of organisations. the key drivers for business analytics adoption remained conservative or defensive. the focus on cost control, customer retention and optimising operations is likely a reflection of the continued economic uncertainty. however,

Big Data is a term for very large amounts of formal and informal information that can be analyzed to find trends and patterns. The information can be about anything, but it needs to be processed in a way that will give it value and relevance. It can come in multiple formats and from different sources such as large databases, electronic records, social media, mobile phones, apps, wearable devices such as pedometers, and others. Different data sets are combined and contrasted in different ways to give perspectives and insights about a topic. It can be used in a seemly endless number of ways and people are discovering new ways to use it all the time, some of them entertaining. The largest areas of use include those relating to consumer behavior and choices, business procedures, healthcare, science and research, and law enforcement. People are also discovering its use in their personal lives as well for things like buying a home, dating, fitness routines and travel.

A very simplified way of looking at big data refers to, “the sheer mass of data produced daily by and within global computer networks at a pace that far exceeds the capacity of current databases and software programs to organize and process” (Dewey, "Big Data"). The world of big data has evolved primarily from the business intelligence and analytics field of information technology. Big data and big data analytics involve big data sets. The information that is stored requires unique ways of holding and organizing the data in order to process it correctly. Common methods of data storage are just not possible. The internet has added to the amount of data that can be captured. With the ability of advertisers to utilize technologies to capture user information through web interfaces, the sheer magnitude of information that can be kept is staggering. All of this information can be put to use by any number of businesses and governments (Chen, Chiang, and Storey, "Business Intelligence and Analytics: From Big Data to Big Impact."). The ability to direct or channel all of that information opens unbelievable doors to virtually any organization. All kinds of organizations would benefit including businesses, governments, schools and hospitals (Dewey, "Big Data"). “Big data may be as important to business –

Several explanations were given about the buzzword “Big Data”. Big Data describes a process in which “serious computing power” is applied to “seriously massive and often highly complex sets of information” (Microsoft Research, 2013). Big data is also defined as a cultural, technological, and scholarly phenomenon” based on three elements such as Technology, Analysis and Mythology (Boyd and Crawford, 2012). The first reason behind the quick expansion of Big Data is the extensive degree to which data are created, shared and utilized across the organizations and virtual networks formally and informally in the recent times. Digitization, that is, the transformation of analogue signals into digital ones, reached massive popularity in the early 1990s. The data-information-knowledge-wisdom hierarchy offers an alternative view, according to which information appears as data that are structured in a way to be useful and relevant to a specific purpose (Rowley,

There is a dramatic transformation in the 21st century due the increase in technology therefore changing the way we perform accounting. The first to occur in the solution is Big Data, which creates” a collection of data from traditional and digital sources inside and outside your company that represents a source for ongoing discovery and analysis”. (Arthur, 2017). Once gathered the next process requires to be it developed via Data analytics being the “the process of examining data sets in order to draw conclusions about the information they contain, increasingly with the aid of specialized systems and

Big data is an extensive collection of structured and unstructured data. It is a modern day technology which is applied to store, manage and analyze data that are not possible to manage, store and analyze by using the commonly used software or tools. Since all of our daily tasks are overtaken by the modern technologies and all the businesses and organizations are using internet system to operate, the production of data has increased significantly in past

However, "Big Data" suggests something more than just an analysis of huge volumes of information. The problem is not that the organizations create high volume of data, but the fact that most of them are presented in a format consisting with traditionally poor structured form of database such as: a web-based magazines, images, videos, text documents, machine code and geospatial data . All of these are allocated in a distributed storages, sometimes even

Another challenge is ensuring that the auditors are adequately trained to handle the Big Data information during an audit. As discussed previously in this report, the supply of Big Data is much too large for regular employees to handle. Auditors now need to be trained to handle Big Data during an audit. This includes adding Big Data components to education curriculums in accounting and auditing (Griffin & Wright, 2015, p. 378). Auditors—both current and future professionals—will need to evolve and gain the skills and experience necessary to respond to the changes enacted in the auditing process with Big Data (Fisher, 2015).