Wednesday, May 6, 2020

Literature Review on Use of Big Data in Business Organizations

Question: Discuss about theLiterature Review on Use of Big Data in Business Organizations. Answer: Introduction Todays world has been revolutionized with the onset of Internet couple of decades back. The connectivity parameters have evolved drastically and now it seems impossible to live a day without remaining connected with the internet. The world has become over depended on the internet and the web applications which many service providers are offering. With the evolution of internet, system software solutions have also seen a tremendous growth in the last decade. Many ERP solutions like SAP, Oracle have come forward and established their footprints globally. However, along with the ERP solutions growth, growth in terms of data handling also rose. It became difficult to handle this huge volume of data (Agrawal, 2011). With more and more organizations starting to mark their presence in the market, the data grew even more. However, the data explosion started a new trend in technology. The huge volume of data, when analyzed properly, can provide very useful information which can be used by any organization for decision making activities. The trend and patterns can be predicted by analyzing the data. With this, Big Data came into existence. The augmentation of Big Data changed the way we looked at data before. Many analysis seemed simple now and the business organizations started using Big Data tools and methods for decision making activities (Anuradha, 2015). About Big Data Big Data is generally taken as a catch phrase or a jargon by many people. It relates to the huge volume of structured and unstructured data which cannot be handled by the old or traditional DBMS techniques. The size of the Big Data can confirm the ability of the tools to provide valuable information to the organizations. Many of the organizations face issues related to storage and processing of huge volume of Data. Big Data tools and methods help the companies in this regard. Big Data is a concept and the meaning of the concept can vary based on the interpretation of someone who is going to use the concept. In similar lines, Big Data can be huge data which traditional technologies will face difficulty to store. Big Data can be velocity driven data which increases continuously as in case of stock markets. Or it can be hi-tech and complex data which needs different ways to store and process (Ahlawat, 2015). Big Data Technology helps the organization to capture high velocity, multivariate data, analyze them and provide reports to business managers to take decisions based on them. Big Data tools capture data which may be in structured format, semi-structured format or unstructured format. By Structurally formatted data, we mean the data which are current present in columnar or row based formats. These data may exist currently in any data warehouse. Processing of these data is bit easier since, we know what data is placed in which columns. Also, there might exist relational data models with pre-defined attributes, schema etc. based on the organizational data. These will help the organizations to get in place all their data and load it into the tool (Bakshi, 2012). The semi-structured data is the one which are not fully grouped in any kind of relational models. They might be group of data at some place but some other data might be stored in a random manner. Unstructured data are stored irre spective of the data type, format, rules etc. They can be present in any format and in any type. For example, videos, audios, images etc. might be stored together irrespective of being different based on data type. Big Data Tools and Methods in Business Organizations With the advancement of innovation and the expanded huge numbers of information streaming all through associations every day, there has turned into a requirement for speedier and more effective methods for examining such information. Having heaps of information close by is no sufficiently longer to settle on productive choices at the perfect time. Such informational indexes can never again be effortlessly investigated with customary information administration and examination systems and frameworks (Duggal, 2013). In this way, there emerges a requirement for new instruments and strategies specific for huge information examination, and the required designs for putting away and overseeing such information. In like manner, the rise of enormous information affects everything from the information itself and its accumulation, to the handling, to the last extricated choices. The Big Data Analytics and Decisions framework combines the tools and methods provided by Big Data and the process of decision making. The different parts and phases of the decision making process is aligned with different Big Data storage and processing tools (Chen, 2014). The Big Data Analytics consists of three important areas which are as follows: Big Data Architecture and Storage Data and Analytics Processing Big Data Analysis which is used for decision making In this review, all the three section will be covered. However, since the big data is still evolving, exhaustive data will not be present. The focus is to touch base all points which are relevant for any business organization. The big data storage happens in the data marts, data warehouses. The way of upload is still same i.e. Extraction, Transformation. Load (ETL) process (Liebowitz, 2013). The ETL process is widely used for all storage related activities. Big Data environment also asks for the MAD analysis. The MAD analysis is nothing but Magnetic, Agile and Deep analysis. There are many frameworks like Hadoop etc. which are used for the same. After the storage of the data, then comes the processing part. The primary requirement is the faster loading of data. Secondary requirement is faster query processing. The third requirement is to utilize the storage space efficiently. The final requirement is the ability to adapt to the dynamic data patterns. With the help of these, the analy sis is done on the data which can be exported into reports. The reports are used by the business managers to check for the specific details about their requirement. These helps in making informed decisions (Kaiselr, 2013). Big Data Analytics and Decision Making in Business Organizations By looking from the perspective of the decision maker, the big datas significance is present in the ability to give correct information and valuable knowledge which can be used to take complex business decisions. Big Data is slowly making its way into being an integral part for driving the business decision making process (Gerhardt, 2012). The data from various modes like cellular data, data from smartphones, cards, social media etc. provide the chance to the organization to make good use of them. The productive use of data is to get something out of it on which a decision can be based upon. This can be only possible if the data goes through good analysis procedures which can project great insights. These insights will help the decision takers to grab the opportunity and act towards the development of their organization. Earlier the organization tend to analyze the internal data. These data included inventory data, shipment related data, sales data (in case of manufacturing organizat ions). They tend to make business decisions based on this. However, external sets of data like the entire supply chain data, customer centric data etc. are equally useful for taking informed decisions. The use of big data helps the organizations to get a cumulative information based on all the parameters (Durgude , 2015). As discussed in the above section, the amount of data can grow exponentially in any organization with time. The best way to get the most out of the data is to continuously upload and store all data into the data storage. Once the data is stored, a model can be made to analyze the data. The design of the model will consider all the parameters which are important for the organization. Based on these parameters, the system will tune the data (zkse, 2015). The filters will be set and data will be normalized to some extent. Upon the completion of process, the business managers will get a list of proposed alternatives. The managers will now have a choice based on different parameters. The decision of selection of the best solution from the choices will lie with the business managers. Big Data can help the organizations to launch new services and products. It can also help in improvising the existing products and services as well. As per various studies, the manufacturing industry, retail i ndustry, telecom industry, healthcare sector are the ones which can make the maximum out of Big Data (Sreedhar, 2014). Importance of Big Data in Business Organizations for their Future The importance of Big Data can be evaluated by checking the effectiveness of concept when used by any organization. The KPIs of the organization should be checked in association with the insights generated by big data for the organization. The organizations can have data ranging from various sources as discussed in the above sections (Polonetsky, 2013). Those data needs to be compiled from all the sources and integrated across the different environments. The analysis of this data will help the business decision makers to get ideas regarding the following: New Product development / Improvisation of existing product in the market Development of new strategies Reduction of cost and time Decision making in smart manner The data analytics tools helps in fine tuning of data for business use. Lot of decisions need to be taken in smaller time frames. Big Data helps the organizations for the same. It helps the organization in analyzing the business tasks to accomplish a range of tasks a listed below: Evaluation of Risk level of any decision or process. The risk portfolio can be maintained RCA activities can be done which will help the organization to find the root cause for any issue It can help in detecting frauds Help in understanding customer behavior which will help the organization to attract more customers and retain their loyal customers (Sagiroglu, 2013) The root cause analysis is one of the major task in case any issue arises in any organization at any point in time. The permanent solution to an issue can be found only when the root cause is understood by the issue attendee. Thus, Big Data can be a boon for the organization if it tries and find out the main cause behind any issue. There might be cases where it may not be able to find the cause but in maximum cases, a solution would be found with the help of Big Data. Risk portfolio management is another big area where Big Data is helping many organization currently (Subramaniyaswamy, 2015). The detection of various risks at a preliminary point of time helps in getting prepared for the same in advance. These will save time and energy. Moreover, it will help in easy mitigation of the risks. Thus, we can see that Big Data can be of big use for the organization. They can provide numerous benefits and can also be termed as the concept in which the organization can depend upon. Conclusion Many of the organizations face issues related to storage and processing of huge volume of Data. Big Data tools and methods help the companies in this regard. Big Data is a concept which is bringing new changes in the way data are treated. Big Data tools capture data which may be in structured format, semi-structured format or unstructured format. The Big Data Analytics and Decisions framework combines the tools and methods provided by Big Data and the process of decision making. The different parts and phases of the decision making process is aligned with different Big Data storage and processing tools. . The permanent solution to an issue can be found only when the root cause is understood by the issue attendee (Tallon, 2013). Thus, Big Data can be a boon for the organization if it tries and find out the main cause behind any issue. The decision of selection of the best solution from the choices will lie with the business managers. Big Data can help the organizations to launch new s ervices and products. It can also help in improvising the existing products and services as well. Thus, we can see that Big Data can be of big use for the organization. They can provide numerous benefits and can also be termed as the concept in which the organization can depend upon. References Agrawal, D., Das, S. and El Abbadi, A., 2011, March. Big data and cloud computing: current state and future opportunities. In Proceedings of the 14th International Conference on Extending Database Technology (pp. 530-533). ACM. Anuradha, J., 2015. A brief introduction on Big data 5Vs characteristics and Hadoop Technology. Procedia computer science, 48, pp.319-324. Ahlawat, T. and Rambola, R.K. 2015., Literature Review On Big Data. Bakshi, K., 2012, March. Considerations for big data: Architecture and approach. In Aerospace Conference, 2012 IEEE (pp. 1-7). IEEE. Chen, M., Mao, S. and Liu, Y., 2014. Big data: A survey. Mobile Networks and Applications, 19(2), pp.171-209. Duggal, P.S. and Paul, S., 2013, November. Big Data analysis: challenges and solutions. In International Conference on Cloud, Big Data and Trust (Vol. 15, pp. 269-276). Durgude, D.M., Yalij, N.S., Bhosale, A.B. and Bharati, M., 2015. Big Data Analysis: Challenges and Solutions. International Journal of scientific research and management (IJSRM), 3(2), pp.2106-2112. Gerhardt, B., Griffin, K. and Klemann, R., 2012. Unlocking value in the fragmented world of big data analytics. Cisco Internet Business Solutions Group. Kaisler, S., Armour, F., Espinosa, J.A. and Money, W., 2013, January. Big data: Issues and challenges moving forward. In System sciences (HICSS), 2013 46th Hawaii international conference on (pp. 995-1004). IEEE. Liebowitz, J. ed., 2013. Big data and business analytics. CRC press. zkse, H., Ar?, E.S. and Gencer, C., 2015. Yesterday, today and tomorrow of big data. Procedia-Social and Behavioral Sciences, 195, pp.1042-1050. Polonetsky, J. and Tene, O., 2013. Privacy and big data: making ends meet. Sagiroglu, S. and Sinanc, D., 2013, May. Big data: A review. In Collaboration Technologies and Systems (CTS), 2013 International Conference on (pp. 42-47). IEEE. Sreedhar, C., Kavitha, D.D. and Rani, K.A., Big Data and Hadoop. International Journal of Advanced Research in Computer Engineering Technology (IJARCET) Volume, 3. Subramaniyaswamy, V., Vijayakumar, V., Logesh, R. and Indragandhi, V., 2015. Unstructured data analysis on big data using map reduce. Procedia Computer Science, 50, pp.456-465. Tallon, P.P., 2013. Corporate governance of big data: Perspectives on value, risk, and cost. Computer, 46(6), pp.32-38.

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