New areas of data analysis in the Internet have spawned esoteric professional titles like, “data miner,” “open source data sequencer,” and, “cloud space computer.” What’s important is that software engineers are directed to, or entrepreneurially focused on, the unique opportunity to create data grabbing sequences that enable real-time information streaming, aggregation of information and smart factoring.
Knowledge discovery in database processes reveal trends and patterns as indicators and answers to hypotheses, questions or pointed inquiries. Usually, the main objective of data mining is to obtain more knowledge, solve problems or identify opportunities. Cluster analysis (mining through groups of data records) or anomaly detection (identifying unusual data trends and patterns) are sometimes pursued to identify problems and challenges. Such research is helpful for business intelligence.
Why am I urging this?
BECAUSE there’s a market opportunity with the surge in user/consumer accepted cloud computing!
With user information more heavily stored and more easily access in the cloud, coders can create (and have created) smart systems that mine this data. These systems also aggregate the information in organized and compartmentalized order and deduce information, trends and conclusions based on a desired inquiry.
Imagine a general manager of a sports team data mining the cloud space for statistical trends of players based on desired outcomes and inquiries. The software could indicate prospective players’ compatibility with the desired outcomes, whereby showing value for inclusion on the roster. Such a pointed statistician’s viewpoint can create a tremendous competitive advantage (think, Money Ball).
Gaming companies have been developing data mining systems to gain an advantage in understanding user behavior and identify anomaly sequences. Political and business data mining systems have helped entities identify their warmest leads (those most likely to purchase or vote, depending on the context), which saves resources and time.
Retailers are data mining to identify consumer interests and perform more target marketing. Companies are increasingly relying on data mining results to forecast supply demands and identify buying trends. Bioinformatics use data mining to create personalized prescriptions based on heavy data sequencing in human genetics. Scientists believe data mining sequences can improve understanding, diagnosis, preemptive treatment and prevention – I believe they’re correct!
Data mining is needed now more than ever and the profit opportunity for strong aggregation and mining systems is immediate. Entities with high efficiency standards or heavy market analysis business models (stock trading) will rely on data mining systems to direct company behavior, deduce information and gain new knowledge.
The advantage of data mining sequencing has become more expansive, helping more entities in varied industries. The cloud will soon become a mainstay of the internet-user experience. For enterprisers, data mining must meet the emergence of the cloud and the rise in data population.
