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technologies
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OLAP With the advent of Data warehouses it became clear that the managing huge amounts of data and attempting to analyze and comprehend it called for different methods than the traditional ones.OLAP stands for On Line Analytical Processing and refers to a category of applications that focus on quick delivery of answers when faced with a data warehouse. Since collections in this model are usually multidimensional, OLAP applications must have the ability to filter data as needed and deal with both large and small scale levels of aggregation. Therefore a common usage pattern is the visualization of requested data into a cube structure. Each dimension of the cube is user-specified. The user can rotate the cube, slice it, drill down and up in order to achieve different views of the same dataset. This ability allows for effective analysis of the data at hand even though the datasets employed are far larger than those handled by traditional database application. Contrast this concept with OLTP (Online Transaction Processing) which reflects the model used with traditional applications. Commonly employed by databases OLTP focuses more on transactions, speed, reliability and performance rather than aggregation and multidimensional data. You can consult the wikipedia entry on OLAP for additional information. Agilis has wide expertise in OLAP applications and one of its flagship products implements the cube approach as explained. Traditional OLTP solutions are also offered if requested. |
OLAP
