Information Technologies for Business Research †Free Samples

Question: Discuss About the Information Technologies for Business Research? Answer: Introducation At present business, the organizations and researchers are seeing big changes in the potential value as well as insight in order to be obtained gained by warehousing for emerging wealth of the digital information that is known as big data, On the other hand, making it available for the analysis and querying, as well as different purposes, the online businesses in spite of its shapes along with sizes are tracking purchases of the consumers (Raghupathi and Raghupathi 2014). The searches of product and interactions with website, and different information in order to increase effectiveness of marketing as well as efforts for customer service are included in the process. However, the Governments as well as the businesses are tracking content of the blogs as well as tweets for performing analysis of sentiment (Hu et al. 2014). At present days, the IT notion of big data has reached to the range of petabyte for making conventional as well as high-end data warehouses along with exabytes that are presumably waiting in particular wings (Kambatla et al. 2014). On the other hand, the database world has admired the finished work on the parallel databases as well as main vendor for database software. These were busy to make commercializing the outcomes and distributed systems world that has began to face the own set of big data challenges. In addition, the rapid development of the World Wide Web along with the resulting are required to have index as well as query that has mushrooming content and created the big data challenges in order to search the companies like Google Inktomi and Yahoo. On the other hand, storage and analysis for big data back-end has dichotomy and the historical record for the big data that also has a front-end story. As organizations between 1980 and 1990s has started automating in their system in day-to-day operations utilizing databases (Alexandrov et al. 2014). These databases had to scale up own online transaction processing (OLTP) systems and data warehouses as well. However, Hadoop and HDFS have developed to become in the dominant platform for analytics of Big Data at large web organizations and has less traditional corners from the traditional organization. Data analysts have developed in tired of low-level Map minimizing the model of programming and selecting instead from handful high-level declarative languages. The frameworks allow data analyses to express more easily write and debug. These languages consist of Hive from Facebook as well as Pig from Yahoo. The tasks are expressed in the languages that are compiled down into the series of MapReduce jobs to execute the process on Hadoop clusters. The ASTERIX data model has borrowed the data concepts. In this aspect, ASTERIX is one of the counter-cultural projects in various ways that tweaking Hadoop and the existing packages (Talia 2013). Setting out for exploring the platform for big data and space from the ground up are involved in the process. Hence, it is important to take fruitful steps that can be helpful to adopt the platform and reduce the challenges faced for the platform. References Alexandrov, A., Bergmann, R., Ewen, S., Freytag, J.C., Hueske, F., Heise, A., Kao, O., Leich, M., Leser, U., Markl, V. and Naumann, F., 2014. The stratosphere platform for big data analytics.The VLDB Journal,23(6), pp.939-964. Hu, H., Wen, Y., Chua, T.S. and Li, X., 2014. Toward scalable systems for big data analytics: A technology tutorial.IEEE Access,2, pp.652-687. Kambatla, K., Kollias, G., Kumar, V. and Grama, A., 2014. Trends in big data analytics.Journal of Parallel and Distributed Computing,74(7), pp.2561-2573. Raghupathi, W. and Raghupathi, V., 2014. Big data analytics in healthcare: promise and potential.Health Information Science and Systems,2(1), p.3. Talia, D., 2013. Toward cloud-based big-data analytics.IEEE Computer Science, pp.98-