CSCI-5012 Special Class

JAGADISH.MUDDAPATI Student ID: 104722670

Many Data Systems are used in Scientific or non-Business Domains. Many of the Books and Reference Materials available implicitly support Business Domain concepts. If you look a Data Warehousing Books, Online Analytical Processing (OLAP) books, even many of the current Big Data and NoSQL books are oriented towards Business Data.
If you look at the Tools available, such as Extract, Transform and Load (ETL) tools, and Data Processing Tools like Hadoop, Storm, and Spark, you still see primarily Business Domain support.
Think about the differences between Business Data Systems and Scientific Data Systems. Write a small paper (1 – 2 pages) discussing any differences and similarities you can find or think of.

Scientific data systems is less oriented on yielding practical results and more concerned with finding out more about how the world works. Scientific data systems usually involve a great deal of computation (arithmetic and comparison operations) upon a relatively small amount of input data, resulting in a small volume of output.

An SDMS (Scientific data management systems) can be seen as one potential solution for handling unstructured data, which can make up nearly 75 percent of a research and development unit's data. This includes PDF files, images, instrument data, spreadsheets, and other forms of data rendered in many environments in the laboratory. Traditional SDMSs have focused on acting as a nearly invisible blanket or wrapper that integrate from corporate offices (SOPs, safety documents, etc.) with data from lab devices and other data management tools, all to be indexed and searchable from a central database. An SDMS also must be focused on increasing research productivity without sacrificing data sharing and collaboration efforts.

Business data systems usually have a