This post is part of Series Business Intelligence – Tools & Theory
Currently running topic for this series is listed as below :
Series Business Intelligence – Tools & Theory
>>Chapter 1 : Business Intelligence an Introduction
>>Chapter 2 : Business Intelligence Essentials
>>Chapter 3 : Business Intelligence Types
>>Chapter 4 : Architecting the Data
>>Chapter 5 : Introduction of Data Mining
>>Chapter 6 : Data Mining Techniques
>>Chapter 7 : Introduction to Data Warehousing
>>Chapter 8 : Different Ways of Data Warehousing
>>Chapter 9 : Knowledge Management
>>Chapter 10 : Data Extraction
>>Chapter 11 : Business Intelligence Life Cycle
>>Chapter 12 : Business Intelligence User Model<You are here>
Continuing from my previous post on this series, If you have missed any link please visit link below
We are going to Cover the Following Points in this article
- Basic Reporting and Querying
Basic Reporting and Querying
There are many basic reporting and querying tool used in Business Intelligence and is based on the increasing cost, functionality, business intelligence, complexity and decreasing number of total users.
The following are the different types of tools used in BI:
Microsoft Excel is the most important and commonly used tool used in Business Intelligence. It is best for the business operations reporting and for goal tracking. The Excel is the most commonly used tool, as it:
§ Is comparatively cheap.
§ Is frequently used as it can be sent easily to another person without worrying if the recipient knows how to read the numbers.
§ Has almost all the functionalities which the users will require to display data
Excel is still so popular that even the third party reporting or OLAP tool will have “export to Excel” functionality. Even for the home-built solutions the capacity to export numbers to excel usually has to be built.
The reporting tool includes both the custom-built reporting tools and the commercial reporting tools. They give some flexibility with respect to the ability for each user to create, schedule, and also run their own reports. In reporting tool the business operations reporting and dashboard are the most important applications and OLAP is an important reporting tool.
Usually, OLAP tools are used by advanced users. This can make it easy for the users to look at the data from multiple dimensions. There are various OLAP tools used for multidimensional analysis.
Data mining tool:
The Data mining tools are usually used by very specialized users, and also in organizations, which are large, and are generally used by selected users using the data mining tools. The Data mining tools are the one‟s which are used for finding the connection among different factors.
Buy vs. Build:
The OLAP tools usually slice and dice the data. So, they require a strong metadata layer, along with front-end flexibility. These are typically complex features for any home-built systems to achieve. Therefore, if OLAP analysis is part of the charter to build a data warehouse, it is good to purchase an already present OLAP tool rather than creating one from the scratch.
OLAP Tool Functionalities:
The two types of OLAP tools are:
§ MOLAP (Multidimensional OLAP)
§ ROLAP (Relational OLAP)
§ MOLAP: In MOLAP, a cube is combined from the relational data source or data warehouse. When the user generates a report request, the MOLAP tool will generate quickly because all the data is already pre- combined within the cube.
§ ROLAP: In ROLAP, instead of pre-combining everything into a cube, the ROLAP engine will essentially act as a smart SQL generator. The ROLAP tool usually comes with a ‘Designer’ piece, where the data warehouse administrator can show the relationship between the relational tables, along with how the dimensions, attributes, and hierarchies map to the essential database tables.
There is a union between the conventional ROLAP and MOLAP vendors. ROLAP vendor will understand that the users want their reports fast, so they are implementing the MOLAP functionalities in their tools. The MOLAP vendors understand that many times it is necessary to drill down to the most detail level information, levels where the traditional cubes do not get to for performance and size reasons.
The criteria for evaluating the OLAP vendors are as follows:
§ Ability to influence parallelism supplied by the RDBMS and the hardware: This can significantly increase the tool’s performance and can also help loading the data into the cubes as fast as possible.
§ Performance: In addition to influencing parallelism, the tool should be quick in terms of both loading the data into the cube and also reading the data from the cube.
§ Customization efforts: The OLAP tools are used as the advanced reporting tool because in many cases, particularly for ROLAP implementations, the OLAP tools can be used as a reporting tool. In which case, the ease of the front-end customization can become an important factor in the tool selection process.
§ Security Features: The OLAP tools are targeted towards a number of users, making sure that the people see what they are supposed to see is important. By and large, all the established OLAP tools have a security layer which can interact with the common corporate login protocols. There are cases where large corporations have developed their own user verification mechanism and which have a "single sign-on" policy. Having a flawless integration between the tool and the in-house verification might require some work.
§ Metadata support: The OLAP tool combines the data into the cube and also sometimes serves as the front-end tool, which is necessary that it works with the metadata strategy or tool.
Some of the Popular Tools are:
§ Business Objects
§ Microsoft Analysis Services
§ Palo OLAP Server
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