Database systems are experiencing very rapid change. Databases are handling structured data at the heart of operations in firms, vendor and customer order systems, financials, inventory management, and manufacturing. Data is being processed by enterprise software connected to back-end databases such as the Oracle product. Also with sensor data and social media data, firms need to be able to handle Big Data using tools such as Apache Hadoop. Streaming big data requires a new approach to data management while maintaining the existing structured database for enterprise systems. Review the following two videos and then produce a comparison of the management issues associated with traditional data management and with Big Data Management. Discuss the future of data management for large firms and the implications for IT management. Srinath, S. (2008). Lecture 30: Introduction to data warehousing and OLAP. Indian Institute of Technology Madras. Retrieved from YouTube: https://www.youtube.com/watch?v=m-aKj5ovDfg Awadallah, A. (2011). Introducing Apache Hadoop: The modern data operating system. Retrieved from https://www.youtube.com/watch?v=d2xeNpfzsYI Case Assignment When you have read through the articles and related material and thought about it carefully, please compose a paper on the following topic:  Compare the management issues associated with traditional data management and with big data management. Include data warehousing and Hadoop in your discussion. Also discuss the applications for these systems and future trends. Your paper should be between three and five pages, not including cover sheet and references. Assignment Expectations Length: Follow the number of pages required in the assignment excluding cover page and references. Each page should have about 300 words. Your assignment will be evaluated according to the Rubric. APA format with proper references and citing. Required reading Aji, A., Wang, F., Vo, H., Lee, R., Liu, Q., Zhang, X., & Saltz, J. (2013, August). Hadoop-GIS: A high performance spatial data warehousing system over MapReduce. Proceedings VLDB Endowment, 6(11), 1009-1021. Retrieved from US National Library of Medicine, National Institutes of Health:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3814183/ Awadallah, A., & Graham, D. (2011). Hadoop and the data warehouse: When to use which.Retrieved from http://assets.teradata.com/resourceCenter/downloads/WhiteP apers/EB-6448.pdf?processed=1 Babcock, C. (2015, September 9). Cloudera sees spark emerging as Hadoop engine. Retrieved from Information Week: http://www.informationweek.com/big-data/software- platforms/cloudera-sees- spark-emerging- as-hadoop- engine/d/d- id/1322100 McAfee, A., & Brynjolfsson, E. (2012, October). Big Data: The management revolution. Big Data, 60-68. Retrieved fromhttp://www.rosebt.com/uploads/8/1/8/1/8181762/big_data_the_ management_revolution.pdf Russom, P. (2015). Hadoop for the enterprise: Making data management massively scalable, agile, feature-rich, and cost-effrective. TDWI Best Practices Report. Retrieved fromhttps://www.cloudera.com/content/dam/cloudera/Resources/P DF/Reports/TDWI-Best- Practices-Report_Hadoop- for-the- Enterprise.pdf Welcome to Apache Hadoop. (2016). Retrieved from The Apache Software Foundation:http://hadoop.apache.org