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have to be released to the public
have to be released to the public
difference between Data Mining and OLAP
Nabisco has created the online analytical processing (OLAP) data mart
OLAP stands for Online Analytical Processing. An OLAP system can be considered as a category of applications and technologies that are used for collecting, managing, processing and presenting multi-dimensional data for analysis and management purposes.
One disadvantage of OLAP (Online Analytical Processing) is that it can be complex and time-consuming to set up and maintain. Additionally, OLAP systems may struggle with handling real-time data updates and can be resource-intensive in terms of memory and processing power.
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The issue is, what distinguishes relational database systems and multidimensional data base systems. It is certainly possible to have an OLAP DMBS, and indeed a number of them have been on the market in the past. The defining difference is how the data is stored. An OLAP system has specialized data structures for optimizing performance with multidimensional data. A relational system uses data tables and SQL to store data. An native OLAP system (a.k.a MOLAP) does not store the data in relational tables. ...At least not directly. For example Oracle embeds their MOLAP system into relational tables. That can make it confusion, but for simplicities sake, just consider, a conventional, relational DBMS stores data in tables and uses SQL, an OLAP system uses something else and a different language, depending on the vendor. Examples are store data in variables, use Oracle OLAP DML, store data in Microsoft Analysis Services, use MDX, Store data in Essbase, use MDX, etc. For detailed information on using a native OLAP system see "The Multidimensional Data Modeling Tool Kit" on Amazon.
3 Main reasons: 1.OLTP systems require high concurrency, reliability, locking which provide good performance for short and simple OLTP queries. An OLAP query is very complex and does not require these properties. Use of OLAP query on OLTP system degrades its performance. 2.An OLAP query reads HUGE amount of data and generates the required result. The query is very complex too. Thus special primitiveshave to provided to support this kind of data access. 3.OLAP systems access historical data and not current volatile data while OLTP systems access current up-to-date data and do not need historical data.
OLTP vs. OLAPWe can divide IT systems into transactional (OLTP) and analytical (OLAP). In general we can assume that OLTP systems provide source data to data warehouses, whereas OLAP systems help to analyze it.- OLTP (On-line Transaction Processing) is characterized by a large number of short on-line transactions (INSERT, UPDATE, DELETE). The main emphasis for OLTP systems is put on very fast query processing, maintaining data integrity in multi-access environments and an effectiveness measured by number of transactions per second. In OLTP database there is detailed and current data, and schema used to store transactional databases is the entity model (usually 3NF).- OLAP (On-line Analytical Processing) is characterized by relatively low volume of transactions. Queries are often very complex and involve aggregations. For OLAP systems a response time is an effectiveness measure. OLAP applications are widely used by Data Mining techniques. In OLAP database there is aggregated, historical data, stored in multi-dimensional schemas (usually star schema).
OLAP allows Nabisco to accurately track sales and consumer preferences, with the largest data mart holding sales, price discount, spoilage, transportation, and promotional information for two years
The primary advantage of OLAP data storage is better performance for accessing multidimensional data. OLAP systems are also accompanied by calculation engines and data manipulation languages. So a second advantage is that it gives analytical capabilities that are not in SQL or are more difficult to obtain. Finally, if you know how to use it, it is easier to work with multidimensional data in a multidimensional system. There are no table joins, storage is set up to include aggregates along with leaf level data, data is articulated in terms of functional categories (rather than rows and columns, or integer indexes), and so on. This is discussed in, The Multidimensional Data Modeling Toolkit, if you want more information.
The OLAP allows Nabisco to accurately track sales and consumer preferences
OLTP : customer oriented. OLAP : Market oriented OLTP : ER based application oriented concern OLAP : subject oriented concern. Current data : Historical data used for detailed for decesion making Access patterns are short. : COCancelMPLEX