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Online Analytical Processing |
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Using the OLAP technology, we develop solutions that can provide insight into data
through fast, consistent, interactive access to information. It helps in reflecting
the real dimension of the enterprise by dynamic multi-dimensional analysis of consolidated
enterprise data. |
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- Online Analytical Processing Tools |
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- DSS tools that use multidimensional data analysis techniques |
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- Support for a DSS data store
- Data extraction and integration filter
- Specialized presentation interface
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View Samples |
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OLAP Design Cycle |
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Four Main Characteristics |
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- Multidimensional data analysis |
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- Advanced Database Support |
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- Easy-to-use end-user interfaces |
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- Support Client/Server architecture |
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OLAP Client/Server Architecture |
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- 3 Main Modules |
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- GUI
- Analytical Processing Logic
- Data-processing Logic
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OLAP definition in just five key words: |
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Fast Analysis of Shared Multidimensional
Information or FASMI for short. |
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FAST
means that the system is targeted to deliver most responses to users within about
five seconds, with the simplest analyses taking no more than one second and very
few taking more than 20 seconds. |
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ANALYSIS
means that the system can cope with any business logic and statistical analysis
that is relevant for the application and the user, and keep it easy enough for the
target user. |
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SHARED
means that the system implements all the security requirements for confidentiality
(possibly down to cell level) and, if multiple write access is needed, concurrent
update locking at an appropriate level. |
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MULTIDIMENSIONAL
is our key requirement. If we had to pick a one-word definition of OLAP, this is
it. The system must provide a multidimensional conceptual view of the data, including
full support for hierarchies and multiple hierarchies, as this is certainly the
most logical way to analyze businesses and organizations. |
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INFORMATION
is all of the data and derived information needed, wherever it is and however much
is relevant for the application. |
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Some of the benefits of OLAP are: |
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- The main benefit of the OLAP is its steadiness in calculations. The reporting is always represented in a coherent presentation irrespective of how fast data is deal with through the OLAP server or software and thus allows the executives and analysts to know exactly to look for where.
- The other convenience of OLAP is that it allows the manager to tear down data from OLAP database in specific or broad terms. In layman's term, the report can be as simple of comparing two columns or as complex of analyzing a huge amount of data. Moreover, it also helps to realize relationships that were forgotten earlier.
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OLAP never had wide spread APIs which were enjoyed by other relational databases
until 1997, when Microsoft, introduced the first real API, OLE DB for OLAP or ODBO
and also introduced Multidimensional Expressions or MDX query language. MDX provides
powerful syntax for manipulating the multi-dimensional data.
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The main component of OLAP is the OLAP server which is a high capacity, multi-user
manipulation engine designed to operate multi-dimensional data and it sits between
a client and database management systems or DBMS. An OLAP server is designed to
support fast extemporized information in any alignment and also designed for rapid
calculations.
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Types of OLAP systems |
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- MOLAP - Multidimensional Online Analytical Processing or MOLAP is considered to be main form of OLAP and thus sometimes just referred as OLAP. It is known for its fast query performance which is because of optimized storage, multidimensional indexing and caching. One of the advantage of MOLAP is that array model provides natural indexing. The main disadvantage is that it introduces data redundancy.
- ROLAP - Relational Online Analytical Processing is an alternative to the MOLAP and works directly with relational databases. The main difference between MOLAP and ROLAP is that it doesn't require storage of information. One advantage of ROLAP is that data stored in database can be accessed through SQL tool. But it is considered to be slower than MOLAP tools by industry people.
- HOLAP: The aggregate data is stored in the multi-dimensional model in the OLAP database and the transactional level data is stored in the relational form in the data-warehouse database. Hybrid OLAP is a combination of the above two. There is a linkage between the summary MOLAP database of OLAP and relational transactional database of Data-warehouse. This gives you the best of both the worlds.
- Some other types of OLAP which are not wide-spread are WOLAP, DOLAP, and RTOLAP.
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OLAP makes Business Intelligence happen, broadly by enabling the following: |
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- Transforming the data into multi-dimensional cubes
- Summarized pre-aggregated and derived data
- Strong query management
- Multitude of calculation and modeling functions
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