Introduction to OLAP
OLAP basically means On-Line Analytical Processing which means that it can be used to extract or retrieve data selectively so that it can be analyzed from different viewpoints. It is of great value in Business Intelligence and can be used in the analysis of sales forecasting, financial reporting.
Example:
An example of this can be that the user can be asked for data and analysis of that data of number of footballs sold in a particular region say Jharkhand in the month of September and compare the same with number of footballs sold in the month of may and they may see a comparison of other sports good sold in Jharkhand for the same month.
How does OLAP Work?
OLAP works by extracting data from multiple sources and storing the same in data warehouses from where data is cleansed and then stored in OLAP cubes and the user gets the data from OLAP cubes against the queries run by it. The new term here is OLAP cubes. In cubes, data is categorized in dimensions (geographical region, time period) derived from dimensions in data warehouses which are filled by members (name, id), etc.
Classification of OLAP Tools
So OLAP tools help us to analyze data multi-dimensionally in data mining. OLAP tools can be classified as the following :
1. MOLAP
It stands for Multidimensional Online Analytical Processing. It stores data in multidimensional arrays and requires pre-computation and storage of information in the cube.
Some of the tools for that are:
- IBM Cognos: It provides tools for reporting, analysis, monitoring of events and metrics.
- SAP NetWeaver BW: It is known as SAP NetWeaver Business Warehouse. Just like IBM Cognos, It also delivers reporting, analysis, and interpretation of business data. It runs on Industry-standard RDBMS and SAP’s HANA in-memory DBMS.
- Microsoft Analysis Services: Microsoft Analysis Services is used by Organisations to make sense of data that is spread out in multiple databases or it is spread out in the discrete form.
- MicroStrategy Intelligence Server: MicroStrategy Intelligence Server helps the business to standardize themselves on a single open platform which in return will reduce their maintenance and operating cost.
- Mondrian OLAP server: It is an open-source OLAP tool and it’s USP is it is written in Java. Another feature of this tool that it supports XML language, SQL and other data sources.
- Ic Cube: Just like the above OLAP tool, this is also written in Java and it is also an in-memory multidimensional OLAP tool.
- Infor BI OLAP Server: It is a real-time, in-memory, OLAP database for multidimensional analysis, planning, and modeling. It is also used for financial, operational planning and reporting.
- Jedox OLAP Server: It is cell-oriented, multi-dimensional and most important in-memory OLAP server.
- Oracle Database OLAP option: As the name suggests this OLAP tool is used to introduce OLAP in the database environment of Oracle. The main objective that it serves is that it can direct the SQL queries to OLAP cubes which in return will speed up the process.
- SAS OLAP Server: Just like the IcCube OLAP server, It provides a multidimensional data storage facility. This server can also be used to get quick access to pre-summarized data.
- IBM T1: This OLAP server also provides multidimensional data storage which is represented in OLAP cubes and computations are done in real time.
2. ROLAP
The ‘R’ in ROLAP stands for Relational. So, the full form of ROLAP becomes Relational Online Analytical Processing. The salient feature of ROLAP is that the data is stored in relational databases. Some of the top ROLAP is as follows:
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- IBM Cognos
- SAP NetWeaver BW
- Microsoft Analysis Services
- Essbase
- Jedox OLAP Server
- SAS OLAP Server
- MicroStrategy Intelligence Server
- Oracle Database OLAP option
3. HOLAP
It stands for Hybrid Online Analytical Processing. So, HOLAP bridges the shortcomings of both MOLAP and ROLAP by combining their capabilities. Now how does it combine? It combines data by dividing data of database between relational and specialized storage. Some of the top HOLAP is as follows:
- IBM Cognos
- SAP NetWeaver BW
- Mondrian OLAP server
- Microsoft Analysis Services
- Essbase
- Jedox OLAP Server
- SAS OLAP Server
- MicroStrategy Intelligence Server
- Oracle Database OLAP option
Now let’s go through the advantages that OLAP tools have in the domain of Business Intelligence.
Advantages of OLAP Tools
- It helps us to analyze and modify reports at a much faster pace since the data is used from in-memory from data cubes rather than the data warehouse.
- OLAP tools like MicroStrategy have intelligent secure Cube data share which allows data to be shared in a secure way.
- Another benefit is the consistency of information and calculations. It means the speed with which data is shared in OLAP servers does not interfere with reporting and the reporting always remains consistent.
- The multidimensional presentation using OLAP tools helps in better understanding of relationships which was not present previously.
- Another popular scenario is the “What if” scenarios of OLAP software. They are made eminently more possible by multidimensional processing of OLAP tools.
- We can apply security restrictions on users and objects using OLAP tools.
- It creates a single platform for planning, forecasting, reporting, and analysis.
Drawbacks of Traditional OLAP
The traditional OLAP had its drawbacks. Couple of them is as follows. Disadvantages of traditional OLAP:
- Pre-modelling is a must in traditional OLAP tools which is a time-consuming process.
- Great dependence on IT: In this case, a user is a business person but he should have good knowledge of IT. The traditional OLAP tools require heavy involvement of IT technicians and people who have good business expertise along with IT.
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