Data Warehousing

Data warehousing is the process of collecting data in raw form for analyzing trends. The benefits to data warehousing are improved end-user access, increased data consistency, various kinds of reports can be made from the data collected, gather the data in a common place from separate sources and additional documentation of data. Potential lower computing costs, increased productivity, end-users can query the database without using overhead of the operational systems and creates an infrastructure that can be used when changing systems, these are some more advantages to data warehousing Data mining is running algorithms to discover trends and other useful information. It can also classify items, indemnify an event and optimize the use of resources. Data mining can be used as an extremely effective tool if we use it properly. Some benefits to data mining include increased profits, less future business mistakes, less losses and knowing what is trending. If we were to know how much hot chocolate was sold in the winter and the summer, we could lower the losses of expired hot chocolate during the summer months and have enough for the winter months. Several different industries use data warehousing and data mining. Our on government uses it to develop trends of financial transactions to detect money laundering. Google uses these as well. Every time I go to Google a record of my searches is kept. Google uses the searches and the links you click on to determine the order of the search results. They also use an auto word function, that is type in part of a phrase and Google will finish it for you depending on the trend. Data warehouses have a basic design with some variations. Data sources, warehouse and users make up the architect of the basic data warehouse. In our system we will be adding data marts and a staging area.
The warehouse is where the data is kept. It consists of metadata, raw data and summary data. Metadata is data about the data in