SQL Server Analysis Services (SSAS)

The need of Analytical Applications
To create multidimensional objects and to provide multidimensional analysis, we require analytical applications
EX: COGNOS, BO, MICROSTRATEGY, SSAS, HYPERION, OBIEE ETC………
SSAS, COGNOS, MICROSTRATEGY ……. ETC Tools are pure MOLAP tools

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Structure of Multidimensional Objects:
Generally, dimension modeling structure (star schema, snowflake schema, etc) used for multidimensional objects providing many- many relationships with E-R modeling is difficult

Multidimensional Object Usage (Cube Usage):
It provides support to end-user (or) client by using various tools and applications
 Multidimensional Object Usage

SSAS Components and Operations

  1. Cube designing
  2. Cube creation
  3. Writing calculations
  4. Performing actions
  5. Implementing KPIs (Key performance indicators)
  6. Creating and working with partitions
  7. Providing Multilanguage support using trans
  8. Designing the aggregations
  9. Creating named calculation and queries

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Checkout SSAS Interview Questions

Textile Manufacturing Industry

Description:

  • A text tile manufacturing industry manufactures various types of shirts, trousers, etc……
  • Shirts also are different various (half hand, full hand services), etc … trousers also with different various (full, half, ¾), etc….
  • These product sale is happening different location in different time zones (time period)
  • Various raw material requires are (chemical, oils, clothes, etc….) to manufacture this product
  • There are different storage areas ( go down, item keeping units) to maintain the product storage
  • For this project, the client requires an analytical solution where they can take appropriate discussions on the business

STEPS REQUIRED FROM END TO END TO IMPLEMENT THE ABOVE PROJECT

  1. Need to collect the discussions from major to minor
  2. According to the discussions, the analytical team collects or gathers the required business information from the project
  3. Analyzing the business requirements
  4. Identifying dimensions and facts for the above business and creating   LDM’s (logical data modeling )
  5. Converting LDM’s to PDM’s (physical data modeling)
  6. Based on the PDM’s we go for designing the dimensional model (star schema, snowflake schema …. Etc  )
  7. Writing code to the design document in analysis services for analytical application (BO, Cognos, Hyperion ….. etc)

Note: except the last step remaining all steps are platform-independent

Conclusion:

For the above business, the technical team identifies (data modulators, data designers, data architectures, domain experts, SME’s (subject modern experts)) the below dimension and fact tables

Dimensions ad fact tables:
a) Time dimension
b) Product dimension
c) Location dimension
d) Raw material dimension
e) Item storage unit dimension (ISU dimension)N
One fact table for the above all dimensions

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