Introduction
Background
Big data is a process in which transforming audits is conducted. Along with this, some major challenges are also adopted in order to maintain the standards as well as to give training in the required processes and systems. It is also said and impossible to further corroborate that around 75% of the world’s data has been initiated as well as created in the past two to three years. The actual and well organized proliferation of the entire data has changed our lives, and the way we act as consumers too. Therefore it is correct to mention that this era of big data helps in reshaping the operations of the businesses and it helps in giving them greater insights as compare to the early days. Therefore this is one of the
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This is the reason why today professionals have actually struggled to stay ahead of the cluster of data curve. In the beginning of electronic communication, auditors were no doubt playing the catch-up method as the volume of data generated by clients was increasing so that they can easily monitor it properly. But on the same side the big data has given the audit professionals an opportunity in order to mine this deluge of loaded information to easily generate maximum effect. This is the reason why majority of the research analysts highlighted that big data along with the technology is one of the bigger impact on auditing as compare to any other thing or issue. Whereas others report that big data related technology is known as the actual revolutionary for the audit profession and this is why majority of the companies is today working with technology and big data in order to change the nature of the auditing process.
Technology based innovation for audit is the main area where professionals should focus so that technology can be well used and performed accordingly. Technology innovation is therefore making it possible to automatically replicate the work. Technology based innovation has also made the best use of analytics in this field of audits in more accessible manner. This is therefore correct to state that technology is the key
Big data analytics is the process of analyzing large data to find useful information such as improving efficiency of business, market trends, customer’s preferences, information of competitors, and other useful business information. According to the IT Glossary, “Big Data is high-volume, high-velocity, and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.” In other words, it is an abundant array of information used to acquire insights and make business decisions.
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.
Information technology has certainly changed the traditional auditor's paper trail. Innovative technology data demands the update of auditing standards for improving efficiency and effectiveness of auditing.
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.
Businesses are struggling with the rapidly increasing volume, speed and variety of information being generated today -- what 's come to be known as big data. Companies are seeking technologies that not only help them process and manage all that data, but tap into it to develop insights about the markets they compete in as well as their own performance within those markets.In addition to the growth in importance of analytics and its prospects for the future, other central themes emerged, including the varied ways in which analytics is structured and managed within these enterprises.
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.
Big data is a term that describes a large volume of data. This data comes in the form of structured and unstructured data. Structured data is information taken and sorted in rows and columns while unstructured data is pictures, tweets, videos, and location-based data. It is not surprising to see many businesses today utilizing data for financial gain. Businesses are harnessing data and using it to make investment decisions, marketing strategies, fraud reductions, and much more. These businesses and organizations can expect to become more profitable, effective, and efficient, but pushes the limits
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.
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 –
Organizations use Big Data to have a bargaining power of customers by using buyer’s history to anticipate the needs of those buyers or products or to find a suitable replacement for the product on the website being used, to secure a purchase before the buyer changes their mind. Big data can also be used to increase margins through price discrimination. Big Data can provide you with insights into the raw material prices paid by your supplier. Organizations control new entrants by tying customers to their product and services making it expensive for them to switch suppliers. Big Data is also used to identify and eliminate inefficiencies. It does this by making data more transparent. Large organizations relentless use of data to drive efficiency makes it difficult for new entrants to match
Because of this classification of data becomes even more important. Techniques such as encryption, logging, and security measures are required for securing this big data. Usage of the Big data for fraud detection looks very interesting and profit making for many organizations. Big data style analyzing of data can solve the problems like advanced threats, cyber security related issues and even malicious intruders. With the use of more sophisticated pattern analysis and with the use of multiple data sources it is easy to detect the threats in early stages of the project itself. Many organizations are fighting with the remaining issues like private issues with the usage of big data. Data privacy is a liability; thus companies must be on privacy defensive. When compared to security, Privacy should consider as profit making asset because it results in the selling of unique product to customers which results in making money. We need to maintain balance between data privacy and national security. Visualization, controlling and inspection of the network links and ports are required to ensure security. Thus there is a necessity to invest ones in understanding the loop holes, challenges, and components prone to attacks with respect to cloud computing, and we need to develop a platform and infrastructure which is less protected to
Big Data is a newer term that has been introduced to the technology world. By definition, the term “Big Data” refers to large amounts of complex sets of data, their relationships and their analysis. (Electronic Privacy Info Center). It can also be defined as a “collection of data from traditional and
Due to the rapid growth in the use of Internet and its connected tools, an enormous amount of data are being produced on a daily basis. The concept of big data arrives when we were unable to manage this huge data with traditional methods. Big data is a mechanism of capturing, storing and analyzing the big datasets and also an idea of extracting some value from it. It is very handful while determining the root causes of failures, issues and defects in near-real time, creating coupons and other sales offers according to the customers shopping patterns, detecting any suspicious and fraudulent activities in real-time. As it is very advantageous, it also has some issues. Some of the common issues can be characterized into heterogeneity, complexity, timeless, scalability and privacy. The most important and significant challenge in the big data is to preserve privacy information of the customers, employees, and the organizations. It is very sensitive and includes conceptual, technical as well as legal significance.
Big Data is one of the most discussed concepts in the business world today. The concept of Big Data is one that has been increasingly debated over the past few years by many different kinds of business industries. One industry where this discussion is prominent is the accounting profession. Big Data will be defined more in-depth later on, but in shorter terms, Big Data refers to the exponential sum of data available in our world today. This amount of data is beyond the traditional analysis that can be computed by human power. When Big Data is converted and used to its full potential, it could have a material impact on the accounting industry as we know it. Companies today must stay on top of the Big Data trend if they wish to