Datawarehouse is an assembly of data that helps in decision making. It is one ofthe components of business intelligence. It is a type of database which is generallyused in processing queries and analysis and contains details of previoustransaction or processes. To ensure quality of data it usually goes throughvarious steps of data cleaning. Relational database is used for onlinetransactions in which data is stored in previously defined categories which includesinsertion, update and deletion.
Data warehouse is used for analytical processing where asrelational database is used for transactional processing. When it comes toquery analysis, data warehouse shows high performance and relational databasehas a low performance. In data warehouse,online Analytical processing (OLAP) is used to which is used to improveresponse time and helps in analyzing better, which is done by denormalizationof the data. Where in online data transactional processing (OLTP) the data ishighly normalized which helps in quick response time and provides a lot ofstorage. Both operational data and decision support data have differentfunctions from each other. Operational data is used to store the data in RDBMSand supports the transactions which takes place in the business.
Operationaldata is more real time whereas decision support data shows processes or transactionwhich have already occurred. Operationaldata is usually used in places to keep up with the simple operations such as keepingtrack of every item sold in a store. Decision support data require denormalizationof data and are useful for place where data there are not a lot of data changesdone on daily basis. Since decision support data requires high speed it doesnot include all the details of every transaction but at the same time it containshuge amount of data. It is highly likely that it contains many duplications andthe data is in denormalization form.
Operationaldata usually has a short time span whereas decision support has a longer timespan. In decision support data, data can be analyzed at different levelsstaring from an overall summary to details of each transaction whereas operationaldata tends to focus on individual transaction. Oneexample where database could be used to support decision making could be companysuch as amazon which requires large database for its inventory and for its variousproducts. They also must keep up with the large amount of their customer’sinformation which includes billing details, shipping date, payment method etc. Anotherexample could be it can also be useful in companies where decision making is requiredto take further actions or future decisions for the company or using queries toanalyze the data. This can be based on several details. Last example of thiscould be that, it is helpful for organizations who need to keep track of theirthings which include keeping track of assets, liabilities, sales and profits. Data mining is a subset of business intelligence used byvarious companies these days.
Data warehouses and data mining these days areused by companies along with sophisticated software to predict the market. Agood example could be data mining used by large organization such as a credit companyto predict as to what type of advertisement a client would be interested in orwhich areas to focus more from where we can a potential client. Another exampleis that is also helpful in keeping up with the market and latest trends whichhelp companies to outgrow positively and plan for future. Last example of datamining could be that it is used by companies to analyze the change whetherthere is an overall increase or decline in their market value or a product.