Big Data's Big Problem - Research Paper Example

ID # Big Data In the past years, the majority of business organizations have started heavily relaying on data and information not only to survive in this competitive environment but also to compete with other business organizations. Without a doubt, these data and information are believed to be the most important asset for business organizations for the reason that they make use of these data to drive useful patterns on the basis of which they take effective decisions. At the present, because of latest tools and technologies such as the Internet this world has turned into the information based age. There is a huge amount of data available on the Internet. This paper presents an analysis of big data. The basic purpose of this research is to present an overview of big data and how it can be used by the organizations for the betterment of their organizations. Basically, “the term big data is normally used as a marketing concept refers to data sets whose size is further than the potential of normally used enterprise tools to gather, manage and organize, and process within an acceptable elapsed time.” (Josyula, Orr and Page 89). In fact, the size of these huge data sets is believed to be a continually growing target. Additionally, the size of big data is presently ranging from a few dozen terabytes to a number of petabytes of data in a single data set (Josyula, Orr and Page 89). In view of the fact this era is known as the age of information and communication technology in which everything appears in digital format, and as a result everything comes under the domain of data. For instance in the medical sector, an electrocardiogram is now used in digital format which can be collected and stored as a dataset and information (attained after the processing of these data). In the same way, MRIs, CT scans and a variety of medical images are at the present digital, and these unique digital records and files are being stored and processed in the form of datasets. Hence, thousands and thousands of distinct datasets are adding up to the big data (Ackerman). The research has shown that the organizations that use big data for their business can be familiar with their customers and the way they communicate with the business and shop online much better than many of those customers can be familiar with themselves. In fact, these datasets are not only the huge volumes of data but also they provide the organizations with excellent ways to determine and keep records of their transactions as well as other communications with suppliers, retailers, banks, utilities and service providers. In addition, at the present there have emerged a number of algorithms which can be applied on these data sets to determine their customers’ behaviors, shopping patterns, usage of sales coupons and how the business organization performs transactions and certain tasks are recorded and analyzed with the purpose of getting a broad and effective depiction of who your customers are and what products you should take the chance to offer them. In their research article, (Arthur) discusses an example in which Portland Oregon Savory Spice Shop owners Jim Brown and Anne have decided to put into practice social media based marketing and advertising with the intention of getting “the best of big data's” support and capabilities for launching their new boutique store. In this scenario, by making use of their Facebook ads they have been capable of routing to catch the attention of those potential customers and groups of purchasers who almost certainly wish to purchase their high-end specialty products. It is an admitted fact that in the past few years the majority of business organizations have started utilizing social networking based sites such as facebook to advertise their products and services for the reason that these social networks provide huge amounts of data. Considering these innovative aspects of social networks, they just had to invest in the ad and then Facebook algorithms and performing analysis by utilizing ton of consumer data available on Facebook in order to identify those people who most directly match their customer profile. “Those potential customers then get targeted ads and special announcements from the store.” Though, big data provides a large number of advantages and if it is used effectively then it can bring a number of opportunities and benefits to organizations. On the other hand, big data can also be turned into a potential source of annoyance (and even bad) when it encourages unnecessary and unwanted advertising and marketing movements, emails, phone calls; or get the wrong impression about the main theme, causing refutation of credit, wrong charges, or in serious cases, the harmful certainty of identity theft (Arthur; Costonis; Schultz, Schwepker and Good). At the present, with the big data the majority of business organizations and retailers make use of data more efficiently to make planned decisions that commence with the customer and help to develop a more thorough design process. In addition, “this analytics-driven design can intensify major touch points all the way through the customer experience at the same time as improving sales beneficially” (Trank p.2). Though, big data are used in all kinds of organizations, but its key implementations are seen in the healthcare industry. In the past few years, the trend of using big data has quickly increased particularly in the healthcare sector. It is expected that in the next year it will further grow from $30 billion to $34 billion predominantly due to increasing use in the healthcare sector. It is believed that this investment is more than counteract by the expected opportunities in minimizing healthcare operating cost, with organizational deficiencies and mistakes predictable to cost providers $100-$150 billion yearly. Additionally, the majority of healthcare firms are turning to IT providers for instance Microsoft, SAS, Oracle, Dell and IBM for hiring their data-mining proficiency. They believe that it will help them carry out detective work as well as improve the quality of health care services. In this scenario, by making “purposeful use” of information technology particularly latest IT supported tools and technologies, healthcare providers can qualify for getting the support of millions of dollars from the Obama administration’s health care funding program which they launched in 2009 to support digitization of healthcare data and medical records. There are many cases which can be acknowledged as the successful examples of information technology use to some quantifiable enhancements in the healthcare industry. For instance, in 2010, New York-Presbyterian implemented Microsoft technology to scan and keep track of patient records, which proved to be successful and reduced the pace of potentially lethal blood clots almost by a third (Robertson; Easterwood and Power) (Robertson, 2012; Easterwood & Power, 2012). There is one important example of practical implementation of big data in this example the largest healthcare provider in Massachusetts “Partners Health Care” made use of its huge volume of health data to implement a pilot program on electronic health record usage in post-market analysis of drugs. However, while analyzing system-wide EHRs, it was found that beginning in 2001 the baseline anticipated rate of heart attack admissions to two hospitals jumped approximately18 percent and returned back to regular rate in 2004 matching up with the initiation and termination of the medicine pain-reliever Vioxx. Additionally, Partners Healthcare is currently working to construct this model by making use of the latest developments in health IT (Chai; Fluckinger and Writer; Rooney). In addition, big data has the capability to support not only health care providers, but it also provides an excellent support for other industry stakeholders. One of the most important examples of this scenario is the implementation of an integrated health database by Aetna Healthcare, a national diversified healthcare benefits provider. This database is being used by the healthcare firm to enhance evidence-based medicine practices in the most affordable way. Additionally, Aetna has implemented big data in its newly coordinated CarePass and iTriage application to allow its customers to get access to a large collection of health resources on a centralized platform (Chai, 2012; Fluckinger & Writer, 2011; Rooney, 2012). However, there are various problems associated with big data for instance there can be some data security and privacy related problems. In view of the fact that big data contain large volumes of raw data and extracting useful information from these mountains of data is a challenging, costly and time-consuming task (Ackerman) Question Number 2. Regression Analysis At the present, a large number of business organizations make use of regression models to identify some useful trends in their business data. Without a doubt, regression analysis is a form of business analytics. In this scenario, regression analysis allows the business organization to use the value of some variable(s) which is known or they are able to control to forecast the value of another variable. In addition, it can be acknowledged as a metric for which a firm can optimize (almost certainly obtain as far above the ground as possible). In simple words, a regression analysis method can refer to the equation for a line that goes onto a disperse area. In this scenario, each value refers to an object of one variable’s response provided the condition of another variable. However, it requires the business management to learn basic concepts of fairly sophisticated linear algebra especially the partial derivatives. There are many software applications which provide excellent support for regression analysis. Some of the well known software applications can be MS Excel or SAS, or R, or a wide variety of other statistical analysis applications and tools. In a business regression analysis can be acknowledged as the relationship between two variables. For instance, what will be the effect on variable B if the value of variable A changes to some extent? This scenario can be understood with another example, in which a business wants to invest in e-commerce but what will be the return on investment. In this example, investment will be variable A and return on investment will be variable B. In another example, a business can use this regression analysis to determine if a number of employees are increased then what will be the effect on business performance (Jeff) , Works Cited Ackerman, Michael J. "Big Data." The Journal of Medical Practice Management : MPM, Volume 28 Issue 2 (2012): 153-154. Print Arthur, Ed. "Big Data." Alaska Business Monthly, Volume 29 Issue 1 (2013): 72. Print Chai, Christian. “Big Data in Healthcare.” Ihealthtran. 2012. Web.04 April 2013 . Costonis, Michael. "Big Data." Best's Review, Volume 113 Issue 1 (2012): 1-80. Print Easterwood, Allison Cerra' Kevin and Jerry Power. Transforming Business: Big Data, Mobility, and Globalization. New York: Wiley, 2012. Print Fluckinger, Don and Features Writer. “Success of ACO model hinges on clinical data analytics.” Searchhealthit. 2011. Web.10 April 2013 . James, Jeffrey. “Are regression models useful?” Getdelve. 25 April 2012. Web.22 April 2013 . Josyula, Venkata, Malcolm Orr and Greg Page. Cloud Computing: Automating the Virtualized Data Center. 1st. New York: Cisco Press, 2011. Print Robertson, Jordan. “The Health-Care Industry Turns to Big Data.”Businessweek. 2012. Web.07 April 2013 . Rooney, Ben. “Big Data's Big Problem: Little Talent.” Online.wsj. 2012. Web.10 April 2013 . Schultz, Roberta J., Charles H. Schwepker and David J. Good. "Social media usage: an investigation of B2B salespeople." American Journal of Business 27.2 (2012): 174-194. Print Trank, Mindi. "Big Data." Proquest: Display & Design Ideas : DDI, Volume 25 Issue 3 (2013): 100. 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