Saturday, October 27, 2012

HR Administration Gets A Boost From Oracle

By Matt Lewison


A Human Resources department in the metropolis of New York, which has nearly 15,000 staff working for it, has made a move to the Oracle data warehousing tools to organize its information analysis needs. The corporation is mainly into offering Medicaid and several extra services to the upward of 3 million residents of New York City.

This is because they have a large amount of data to consider and control, and that is the reason they have decided to work with Oracle as their service providers. If you are seeking specializations for Oracle such as OBIEE administration training classes, you may find that demand for professionals who are equipped with the experience to work with this application might have grown appreciably.

The organization of relevance here works with terabytes of data, which keeps growing day by day. The new warehousing tool became fully operational on the 14.02.2012, but it took them six months, until the month of August, to make sure that the evaluations were carried out methodically. An staff member from the corporation said that even an uncomplicated spreadsheet will have more than 100,000 entries and the biggest spreadsheet in the company's database contains an excess of three and a half billion claims which have been paid.

The implementation of this new business intelligence system has streamlined the data warehousing process appreciably, while reducing the energy required in monitoring large data packets. For example, the new data system has only the data from which the system initially went active (February, 2012). However, the data system also has to respect the older data to make some long term data trend calculations and additional strategic business options.

The same organization was also involved in a survey which showed that in a data warehouse, only 15-20% of the information are actually used and the rest is superfluous. With the assimilation of Oracle business intelligence tools, the people in charge can separate the central data from the unnecessary information without much struggle.




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