week 2 data mining and BI application

I have changed one of my unit enrollments from distributed database to knowledge discovery and data mining this week. One reason is that distributed database unit has not changed its prescribed textbook for many years. It’s still using a book which was published in 1999. Technology keeps updating all the time, I don’t believe distributed database technology has not evolved during the last few years. Another important reason is that data mining has close relationship with business intelligence application. Studying these two units can give me more insight into data analysis within the context of business environment.

Business intelligence is information about a company's past performance that is used to help predict the company's future performance. Data mining allows users to sift through the enormous amount of information available in data warehouses, it is from this sifting process that business intelligence gems may be found. Data mining is intuitive, allowing for increased insight beyond data warehousing. An implementation of data mining in an organization will serve as a guide to uncovering unknown trends in historical data. It will also allow for statistical predictions, groupings and classifications of data. Data mining software allows users to analyze large databases to solve business decision-making problems. Data mining tools predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. Data mining tools can answer business questions that traditionally were too time-consuming to resolve. As the semester progresses, it would be interesting to see how data mining technology is built into BI applications and how these two units support one another.