In today’s society, technology has become more advanced than the human’s mind. Companies want to make sure that their information systems stay up-to-date with the rapidly growing technology. It is very important to senior-level executives and board of directions of companies that their systems can produce the right and best information for their company to result in a greater outcome and new organizational capabilities. Big data and data analytics are one of those important factors that contribute to a successful company and their updated software and information systems. What are Big Data and Data Analytics? You may ask what big data analytics is. Well according to SAS, the leading company in business analytics software and services describes big data analytics as “the process of examining big data to uncover hidden patterns, unknown correlations and other useful information that can be used to make better decisions.” As the goal of many companies which is to seek insights into the massive amount of structured, unstructured, and binary data at their disposal to improve business decisions and outcomes, it is evident why big data analytics is a big deal. “Big data differs from traditional data gathering due to that it captures, manages, and processes the data with low-latency. It also one or more of the listed characteristics: high volume, high velocity, or high variety. Big data comes from sensors, devices, video/audio, networks, log files, web, and social media which much of it is generated in real time and in a very large scale.”(IBM) In other words, companies moving towards big data analytics are able to see faster results but it continues to reach exceptional levels moving faster than the average person can maintain. ... ... middle of paper ... ...4. . 3. Zavadszky, Andrea. "New Accounting Needs Data and Analysis Skills." Classified Post. N.p., 30 Nov. 2013. Web. 18 Mar. 2014. . 4. Davenport, Thomas H., Paul Barth, and Randy Bean. "How Big Data Is Different." MIT Sloan Management Review. N.p., 30 July 2012. Web. 18 Mar. 2014. . 5. "Big Data Analytics." SAS. N.p., n.d. Web. 10 Mar. 2014. . 6. "What Is Big Data Analytics?" IBM. N.p., n.d. Web. 18 Mar. 2014. .
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Big Data is a term used to refer to extremely large and complex data sets that have grown beyond the ability to manage and analyse them with traditional data processing tools. However, Big Data contains a lot of valuable information which if extracted successfully, it will help a lot for business, scientific research, to predict the upcoming epidemic and even determining traffic conditions in real time. Therefore, these data must be collected, organized, storage, search, sharing in a different way than usual. In this article, invite you and learn about Big Data, methods people use to exploit it and how it helps our life.
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If auditors can look at a complete population, they may not have a great defense if they missed a “smoking gun” since they looked at all the data (Alles and Glen). However, this data may not be valid which raises the importance of the auditor understanding where the data came from and how reliable it is. Not only this, it will be interesting to see how standards consider big data evidence. While it most likely will not be as reliable as confirmations, it would be a challenge to figure out how much the auditors could rely on it. Furthermore, higher education would most likely play a role in helping their graduates understand data and how to use technology to be not only more efficient but also ensure they are able to use sound professional judgement while using big data.
The key strategy implementation efforts at Amazon all surround the use of “big data”. Big data is the growth and availability of large volumes of structured/unstructured data. The use of big data has allowed decision making based upon data and analysis instead of past experience and intuition. Big data has directed organizational change in allowing Amazon to expand from an online book store to an internet giant. Revolutionary application of big data has allowed Amazon to create superior service quality while motivating employees by providing real time information to solve customer issues. Big data has strengthened Amazon’s competitive capabilities by pioneering the application of big data and charging a monthly fee to smaller businesses
Companies have transformed technology from a supporting tool into a strategic weapon.”(Davenport, 2006) In business research, technology has become an essential means that many organizations use in their daily operations. According to the article, Analytics is a major technological tool used. It is described as “the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions."(Davenport, 2006) Data is compiled to enhance business practices. When samples are taken, they are used to examine research and understand how to solve problems or why situations are as they are. Furthermore, in this article, Thomas Davenport discusses analytics from a business standpoint. He refers to organizations that have been successful in their usage of data and statistical analysis. In addition, he also discusses how data and statistics can be vital in the efforts to improve the operations of businesses.
Only when an organization is capable of using analytics to its full potential will it have a sustainable competitive advantage. The number of organizations using analytics is growing exponentially. Much information can be gained just from analyzing one variable, but every piece of information is significant in some way. Businesses use analytics to make improvements, better see future demands, meet sales forecasts, make decisions, come up with strategy plans, and rationalize and validate key performance indicators.
Effectively, big data provides the companies with the opportunity to know and understand their customers. With Big Data, a company holds a lot of information about their customers, such as their habits, what is the product they prefer, the time they make purchases, how many products they buy and what kind of promotion their prefer. Then they can make a relation with who the person is, age, gender. Thus they can adapt their offer to the customer. If you are a good client, you can have private discount, or more discount. The objective is to know personally your customer to make them feeling unique.
Prior to the start of the Information Age in the late 20th century, businesses had to collect data from non-automated sources. Businesses then lacked the computing resources necessary to properly analyze the data, and as a result, companies often made business d...
For the past couple of decades the majority of businesses have wanted to construct a data-driven organization or company. Furthermore, companies around the world are considering harnessing data as a basis of competitive advantage over other companies. As a result, business intelligence and data science use are popular in many organizations today. The increase in adoption of these data systems is in response to the heavy rise in communications abilities the world over. Which, in turn ,has increased the need for data products. Indeed, the Data Scientist profession is emerging to be one of the better-paying professions due to the urgent need of their labor. This paper is going to discuss what business intelligence is all about and explain data science that is usually confused to be similar to business intelligence. I will tackle a brief overview of data scientists and their role in organizations.
Big data originated with web search companies that encountered problems with querying large amounts of both structured and unstructured data. With regard to its background, “big data came into being when web search companies developed ways to perform distributed computing on large data sets on computer clusters” Floyer (2014: 1). Big data then spread to enterprises due to their adoption of developing, processing and dissemination of data.
Data Science is a new interesting software technology, which is used to apply critical analysis, provide the ability to develop sophisticated models, for massive data sets and drive the business insights. Data science is an umbrella term used to describe how the scientific method can be applied to data in a business setting. Data science is also playing a growing and very important role in the development of artificial intelligence and machine learning. Although the differences exist, both data science and data analytics are important parts of the future of work and data. Data Analysts take direction from data scientists, as the former attempts to answer questions posed by the organization as a whole. Both terms should be embraced by companies that want to lead the way to technological change and successfully understanding the data that makes their organizations run. Company need both data scientists and data analytics in their project. Both are part of company’s