MIS 2502 Research
Using Big Data for Data Analytics
Upon reading an article titled “Leveraging Big Data for Data Analytics” by Derek Wilson, President & CEO, CDO Advisors LLC, I’ve learned that one of the main benefits of utilizing big data is that it enables companies to perform advanced analytics at a very manageable cost. This makes it very profitable for any company that can store and analyze and quantify their customer records, with daily and long term transactional data. In reading this article I’ve learned that there are three types of data that companies utilize in the modern IT environment which is structured, unstructured, and streaming data. Per the article, structured data is what companies use in relational database management systems which reminds me of how the information architecture of an organization works in the early parts of MIS 2502. The architecture of an organization first starts with the data entry in a transactional database which then gets extracted to the analytical data store, which then in turn gives the company data analysis to better utilize the data for future business transactions. For unstructured data, which refers to data that is stored without having a predefined structure, companies use this data in the form of word or pdf documents, images, emails etc. One, would think that mostly unstructured data would be found within the companies’ operational databases for the use of communication amongst management and employees.
Lastly the article described streaming data as data from devices that send out data on regular schedules with examples pointing to things like log files, Internet-of-Things devices such as smart thermostats and floor devices. While reading this article, it is important to note that as I read, many of the terms that Wilson mentioned we have talked about in class such as the three base frameworks of storing data, which is raw, sand boxed, and normalized. Put simply, raw data stores data that is structured, unstructured, or streaming. The sandbox environment then uses that data and transforms it to something that users of the data can utilize, then once the data is normalized it is put in the best data store to be utilized for future endeavors across the company or organization. In conclusion learning many concepts in MIS 2502 has helped me understand much of the rhetoric described when companies refer to big data with the use of databases in the transactional and analytical data storage processes.
Article: http://bigdata.cioreview.com/cxoinsight/leveraging-big-data-for-data-analytics-nid-24225-cid-15.html