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Dimensions & OLAP Types in Cognos

Conformed Dimensions

It is a dimension which is shared by multiple fact tables

Ex: customer dimension, time dimension

Fact Constellation

It is a process of connecting multiple fact tables with PK-FK relationship

Slowly changing dimension (SCD)

A slowly changing is a dimensions which captures the changes occurs  over a period of time

  • There are three types of SCD’s
  1. SCD type1
  2. SCD type 2
  3. SCD type3

SCD type 1

It contain only current data

SCD type 2

It maintain couple history and current data

SCD type 3

It maintain partial history (or) recent history and current data

Surrogate key

It is a system generated key which access primary key in the dWH tools maintains the uniqueness.

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OLAP and types of OLAP

OLAP

It is a interface (or) a gate way between the user and data source (dWH)

(or)

It is a set of specifications with allows the client application (report application) to query the data from data source and displays the data and to report

Types of OLAP

  1. DOLAP (desk top)
  2. ROLAP (relational)
  3. MOLAP(multi dimensional )
  4. HOLAP(hybrid)

DOLAP

It is a OLAP used to query the data from desktop database like Dbase, fox, ms access, ckpper. While generating the report online

ROLAP

It is used to query the data from multidimensional source like cube and DMR model (dimensional relational model) to perform multidimensional analysis.

Multi dimensional analysis

It is a process of viewing the data at different levels of details

  • Use the following features to perform multidimensional analysis
  1. Drill up:

Navigating from lowest level to highest level

  1. Drill down:

Navigating from highest level to lowest level

HOLAP

It is a combination of both ROLAP and HOLAP it can query the data from the relational sources as well as multi dimensional sources like cognas.

Phases in dimensional modeling

  1. Conceptual modeling
  2. Logical modeling
  3. Physical modeling

Conceptual modeling

In conceptual modeling face, database models conform or decide the dimensional tables and fact tables required for a particular data ware house design.

Logical modeling

In logical modeling database modelers start creating relation between the tables logically

Physical modeling

In physical modeling database modelers creates dimensional tables and fact with relations physically in the database

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