OLAP vs OLTP
OLAP or "on-line analytical processing" is an enabling application technology and database model that grants users-such as functional managers-strategic decision making capabilities. OLAP analyzes the results of daily business, so tactical and strategic decisions can be made to change the way business is done and gain competitive advantage. OLAP tools include programs that show Multi-Dimensional Data, rather like a spreadsheet with six or seven dimensions instead of only two with drill down capability. While OLTP or "on-line transaction processing" applications enhance transaction processing by relating atomized data across business processes, OLAP applications and databases provide users with the ability to view "multi-dimensional data," thereby enhancing the manager's ability to create business models. The significance of a "multi-dimensional view" of data is that it allows decision-makers to view many, summarized, historical data records, and group them by subject. In short, it allows for consolidation of data. Rather than executing queries that view data by record and file-such a
Space requirements Can be relatively small if historical data is archived Larger due to the existence of aggregation structures and history data; requires more indexes than OLTP Processing speed Typically very fast Depends on the amount of data involved; batch data refreshes and complex queries may take many hours; query speed can be improved by creating indexes Data warehouses exploration tools such as managed query, OLAP and data mining tools are the (financial) justification of building a data warehouse. OLTP handles the daily business, for example, creating Purchase Orders and keeping track of inventory. The world is multidimensional, and various users will look at data in multiple ways. This brings about the introduction of the "multidimensional conceptual view." This is why OLAP models should be multidimensional in nature for maximum flexibility. Consequently, the quality and speed of the underlying database is distinguishing factor for OLAP tools. Such multidimensional tools are capable of rows or columns in a database hundreds of times faster than a relational database, so th
Some common words found in the essay are:
OLTP Database, Multi-Dimensional Data, Queries Relatively, Mart Source, , Updates Short, OLAP Type, relational databases, complex queries, ability execute, database thereby, olap data, data records, atomized data, historical data, business processes, olap tools,
Approximate Word count = 743
Approximate Pages = 3 (250 words per page double spaced)
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