1. Introduction Concern about Big Data has been heightened in recent years. The report intents to first discourses the definition of Big Data, relationship between business analytics and Big Data, and several commercial softwares of Big Data. Then the report will illustrate a case study on a global e-commerce company called Alibaba (China) Co, Ltd with company background information, challenges when facing and applying an accounting information system of Big Data and Benefits that Big Data bring to the company. It should be also noted that the report heavily emphases the impact of Big Data particularly through an accounting perspective. As a consequence, the report will come into a conclusion on implications of Big Data to business organizations. 2. Description of Big Data Data are raw materials that constitute an information system. When it comes to Big Data, the common perception of the ‘Big’ is in size, which can be elaborated as significant, complexity and challenge (Ward & Barker 2013). The magnitude is similarly addressed to volume, velocity and variety (Douglas 2001). Howie, one of the Microsoft engineers, succinctly discoursing Big Data as the expression progressively adopted to define the process of exercising serious computing power – the up-to-the-minute in artificial intelligence – to colossal and often highly intricate sets of information (Howie 2013). These diverse explanations present a perspective that Big Data appears as a more integrity and
This excerpt of “Six Provocations for Big Data”, written by danah boyd and Kate Crawford, was a presentation on Big Data at Oxford University as part of a bigger convention. Big Data is mass produced information made possible by people, things and their interactions. Boyd and Crawford point out 6 backed-up claims on Big Data to prove that it’s weakening researchers’ understandings while also affecting the people that become a part of it. Crawford and boyd successfully conveyed through paragraph structure that “Big Data” can be used for research, but it’s use is unethical due to the unseen consequences that follow. The organization that these authors choose helped the reader focus on their point.
Big Data is one of the fastest growing fields in the world. Vast amounts of data are being produced by scientific researchers and social media users. Through the power of computing, humanity can analyze and gain useful information the mountains of data that have been collected. But are there any dangers? In their presentation Six Provocations for Big Data, Dana Boyd and Kate Crawford offer many logical and ethical challenges to the Big Data industry. The excerpt of this presentation in Everything’s an Argument contains two of the six claims in the full presentation. These two claims are that “automating research changes the definition of knowledge” and “just because it is accessible doesn’t make it ethical.” Boyd and Crawford, using ethos,
Many people have become so immersed in data, that they are unable to recognize the data that they have been exposed to. For example, many college students either watch tv or listen to music while completing homework. Students often time just see this as background noise when in reality this is data that become stored in your unconscious mind. The film Big Data gives a visual account of how much data streaming has impacted society both negatively and positively through the use of data analysis. Data has taken away the ability to remain anonymous and has also sparked a decline in human interpersonal skills. However, Data also has allowed humanity to collect new information providing new solutions to world issues. The film Big Data is able to
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.
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 promise of data-driven decision-making is now being recognized broadly, and there is growing enthusiasm for the notion of ``Big Data.’’ While the promise of Big Data is real -- for example, it is estimated that Google alone contributed 54 billion dollars to the US economy in 2009 -- there is currently a wide gap between its potential and its realization.
In a dynamic global economy, companies and organizations have started to rely more and more on statistics gathered from their customers insights and behavior, internal processes and business operations with the aim of finding new opportunities for growth. In order to find and determine this information, large complex sets of data should be generated and analyzed by skilled professionals. The compilation of this large collection of data is known as “Big Data”.
The data is too large, moves too fast or does not meet the constraints of the database
In a fast paced, business ordinated technological world the overall welfare of a company is tied to the success or failure to make the tough decisions. On one instance a company’s CEO might be able to make the choices based on experience, advice, or simple gut instinct. However, this is not the only skill one needs. There is a great deal of information to be found in being able to see investments in data and analytics. These decisions are based off of big data. Big data is a catch-phrase, used to describe a massive volume of both structured and unstructured data that is too large to process using traditional database and software techniques. The volume of data is in most cases is too big, moves too fast or it exceed the processing capacity the company has. Despite these potential drawbacks, big data contains the potential to help companies by improving operations and making faster, more intelligent decisions. This can be broken into three key parts, knowledge, data, and information.
The promise of data-driven decision-making is now being recognized broadly, and there is growing enthusiasm for the notion of ``Big Data.’’ While the promise of Big Data is real -- for example, it is estimated that Google alone contributed 54 billion dollars to the US economy in 2009 -- there is currently a wide gap between its potential and its realization.
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 emergence of new technologies, applications and network systems makes it hard to run the current business models and huge data types, and thus emerged various types of analytic tools like Big Data, which make this work easier by way of proper organization of data. Big Data is all about analyzing different forms of data (Structured, Semi-structured and Un-structured) and it is not about the procedure, creation or consumption of data.
This article can be regarded as current since it was published in 2013. What is more, the authors of this text both work for the department of business in the universities. They may have specific expertise or knowledge in the field of big data as it is an essential factor in business. Furthermore, Business Intelligence Journal contains a professional data warehouse for business. As a result, this article is also authoritative and reliable. Besides, as a journal article, not only does it follow the usual academic conventions like in-text citations and references, but also its language is impersonal and formal, which seems to be objective. Big data has become a useful tool to help companies make decisions and turn to customer-centred
The guarantee of information driven choice making is presently being perceived extensively, and there is developing excitement for the thought of ``Big Data. ' ' While the guarantee of Big Data is genuine for instance, it is assessed that Google alone contributed 54 billion dollars to the US economy in 2009 - there is right now a wide crevice between its potential and its acknowledgment. Heterogeneity, scale, convenience, intricacy, and protection issues with Big Data block progress at all periods of the pipeline that can make esteem from information. The estimation of information blasts when it can be connected with other information, subsequently information combination is a noteworthy maker of quality. Since most information is directly produced in advance today, we have the open door and the test both to impact the creation to encourage later linkage and to naturally interface already made information. We trust that fitting interest in Big Data will prompt another rush of central mechanical advances that will be epitomized in the following eras of Big Data administration and investigation stages, items, and frameworks. The interest in Big Data, legitimately coordinated, can result in major investigative advances, as well as establish the framework for the up and coming era of advances in science, solution, and business.
It is hard nowadays not to hear news about “big data”. As technology continues to grow, companies are constantly trying to leverage them to remain competitive. Scientists, governments, and even the media are now also invested in extracting big data for their uses. McKinsey Global Institute (2011) defines big data as “datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze”. Furthermore, Barnatt (2012) explains that big data can be categorized into the three V’s: volume, velocity, and variety. Technologies like the internet, smartphones, computers, appliances, and automobiles are creating expansive amounts of data every second which contributes to the volume of data.