Big Data Analytics of Marketing

Question: Discuss about the Big Data Analytics of Marketing. Answer: Introduction The essay describes about the big data and its benefits and challenges if it is applied in a companys management structure. Big data contains 3V that are as: volume, variety and velocity. These are considered as dimensions for using big data tools in the organization. The assignment has considered wesfarmers limited for such analysis. The reasons behind this are high volume of data, high level of heterogeneity in data and velocity. It helps the company in generating new knowledge, technical knowledge, and involving into advanced research and development (Kitney, 2013). Due to evolvement of internet, there has been massive growth in the volume of data. Big data is when an organization has a huge amount of data with it. Big data in an organization consists of structured as well as unstructured data. In an organization, big data can be understood as analyzing the data in such a way that it helps the organization in taking effective decisions and strategic decision. To come out with an effective decision, management uses business analytics. It is a process in which the organization emphasis on statistical analysis. Besides this, business analytics is used if an organization is having big data with it, and it is difficult for the organization to arrive at a solution, hence in such a situation business analytics is preferred. Softwares which are used to deal with big data are as: SAP bigdata analytics, IBM bigdata analytics, Oracle bigdata analytics, SAS big data and many more (Mohanty, Bhuyan Chenthati, 2015). Brief background to the case The assignment has considered wesfarmers limited for such analysis. It is one of the established companies in Australia, founded in 1914 headquartered in Australia. It is a conglomerate company dealing in a wide variety of products. The company has a wide variety of product offerings and large variety of customer base. To excel in the industry, the company requires having some control in its logistics. In case of requirement of big data tools in the company, the company offers a wide variety of products such as: coal mining, fertilizers, chemicals and industry safety products. Hence due to this, the company requires a tool which helps the company in managing its customers demands and expectations. The use of big data tools would help in bridging the gap between customer expectations and actual offerings made by the company. Big data tools would help the company in overcoming such gaps, but for this wesfarmers limited must have developed informational technology in which wesfarmers la cks. Hence this would be requiring a major investment in information technology and data analytics (Morabito, 2015). Challenges of Big Data to the case Use of big data can depict about the real picture of the company, hence it affects the principle of confidentiality in the organization. The major challenges in use of big data in the company are as: timeliness and privacy, storage, search, transfer, and sharing of data. This would also affect the analysis and visualization of data. Besides such issues, another challenge is that who would be responsible for managing the big data in the organization. Storage of big data in the organization creates heterogeneity. For example in case of wesfarmers, there are different experiments that need to be done for collection of information from consumers, and the results from experiments are different every time. The reason behind this is, every experimenter has different perspective regarding the models to be followed for conducting experiment (Zicari, 2013). Furthermore, it is not easy to store all the information electronically due to huge volume and heterogeneity involved in the data. In case of timeliness the more the data would be stored in wesfarmers database it would lead to late retrieving of data from the storage. To collect information from the external source is itself a major task due to belongingness of different culture, geographical tutorials. Hence it is very difficult for the company to arrive at a decision from the data. Due to heterogeneity involved in the data, sometimes it is very difficult for the company to analyze the data in an effective manner and how to use the data to arrive at an effective solution (OReilly Media, Inc, 2012). In case of the given case study of wesfarmers, for applying big data tools, it requires special computer power so to enhance the quality of real time analysis. While the company lacks in technical knowledge and information technology. Hence using big data tools effectively are considered as challenge for wesfarmers limited because to retrieve the data in no time would be requiring high end technology. Hence it would increase the cost for the company in its initial year. Besides this, the data stored in the company database regarding its customer contains a high level of variety that is it is in highly unstructured form, which creates difficulty for the management to analyze the whole data, and arrive at a common solution (Foster, Ghani, Jarmin, Kreuter Lane, 2016). The data as stored in the organization does not ensure about reliable source, this means that there are some possibilities that the data in the organization is biased. Due to which the quality of the data stored in the company database is affected. The main challenges involved in the big data management tools are data privacy, security, ethical and governance. This means that how the data would be used, whether it complies with the law and regulations of the country like in the given case rules and regulations of Australia. Besides this, whether it is ethical to obtain such information from the market or customers. Hence these are considered as some of the major challenges for the company for applying big data tools (Howarth, 2013). Benefits of Big Data to the case Big data is considered as back bone for an organization. The use of big data in an organization contains benefits like the organization can keep a track of customers who has visited the company website. It helps an organization in procuring and keeps tracking of component parts. In case of banking company like HSBC bank, it helps in keeping a track record of number of deposits, customers having account in bank, determining the processes of accounting (Yu Guo, 2016). In the context to the given case study on wesfarmers, the use of big data analysis helps in determining the trends, markets and behavior of the market and its customers. Besides this, it helps an organization in providing advisory services (Frampton, 2014). By this, it creates various levels for building innovation strategies in the organization. It also provides a base for competing with competitors and building growth in the business. Besides this, it helps in analyzing the errors and rectifying them instantly. This would help the company in managing its operations effectively. Hence by using big data tool, the company can analyze the demand from its customers, hence it can reduce the percentage of unsatisfied consumers. Hence it can be said, that errors in the organization can be solved early by applying big data tools in the organization (Pal, 2016). In case of wesfarmers limited, the management of the company can form strategies effectively so to compete in the market. With the availability of big data with the management, they can take strategies to stay at a step ahead from its competitors. This would help the company in becoming an industry leader; hence this would lead to reduction in prices (Management association, 2016). Hence it can be said that by big tools data helps the organization in improving their services and would help the company in earning higher revenue. The reason behind increase in the revenue would be because of detecting the errors at an earlier stage. Hence by this, frauds in the management, internal control mechanism of the company would become apparent at an earlier stage (Loshin, 2013). Big data helps wesfarmers limited in analyzing the cost; hence it would lead to adaptation of cost effectiveness strategies. Besides this, it would help the company in analyzing the customers latent demand, and would lead to better comparison between the customers expectations from the company and actual offerings made by the company. Hence by this, real time analytics can be ensured in the wesfarmers limited to establish a better match with its customers and would help the wesfarmers limited in performing customized services (Tedex, 2014). Conclusion In todays world big data is used by the various organizations, companies such as: eBay, Facebook, Google were the first one who has incorporated big data analytics in their business structure. In case of the given case study, the increase in the data has affected the growth of the company. It was very difficult for the company to analyze the demand and expectations of the market or consumers from them; hence to accomplish such requirement the company has adopted the tools of big data tools. Besides this, the requirement of big data tools was due to increase in the volume of data, and variety of data. However these factors are also considered as critic for the company that is it is very difficult for the management to store all the data electronically, and to retrieve the data so to arrive at an effective solution. References Foster, I,. Ghani, R,. Jarmin, R, S,. Kreuter, F Lane, J,. (2016) Big data and social science: a practical guide to methods and tools, CRC press, United States Frampton, M,. (2014) Big data made easy: a working guide to the complete hadoop toolset, Apress, USA Howarth, B,.(2013) CMO, Big data analytics: the new black magic of marketing? Retrieved on 27th March, 2017 from https://www.cmo.com.au/article/529936/big_data_analytics_new_black_magic_marketing_/ Kitney, D,. (2013) The Australian, Retailers battle it out on big data. Retrieved on 27th March, 2017 from https://www.theaustralian.com.au/business/companies/retailers-battle-it-out-on-big-data/news-story/923f664484a17cb1cc76f7a713826c92 Loshin, D,. 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Retrieved on 27th March, 2017 from https://www.odbms.org/wp-content/uploads/2013/07/Big-Data.Zicari.pdf pp (104-128)