SQL server Analysis is the product of Microsoft, which delivers online analytical Processing (OLAP) and the Data Mining Process. For business Intelligence Apps.It supports OLAP, and it makes you to design, create and maintain multidimensional structures, which contain Data aggregated from other Data sources. For Data mining Services it lets you to design, create, visualize all types of data mining models that are constructed from other data sources by a refreshing, a large variety of Data mining algorithms which are based on Industry standards.

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SSAS Architecture 2017                                                                   

OLAP Engine Components      

The msmdsrv.exe application is the server component, of  Microsoft SQL  Server Analysis Services, that which runs as a Windows Service.All the security components are present in this application, an XML For Analysis (XMLA) listener, it is a query processor and numerous Internal Components that perform the below following  Functions.

1)Resolving Statement that received from Clients.

2)Managing All the MetaData.

3)Handling Transactions.

4)Processing Calculations from all Data Sources.

5)Creating Aggregations.

6)Scheduling Data Related Queries

7)Caching Objects.

8)Managing Server Resources.

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Analysis Service Instances performs as a stand-alone service and communication occur through XML  for analysis (XMLA) using either  HTTP and TCP.AMO is the part between the user application and the analysis service instance.This part provides access to analysis service administrative objects.AMO is the library that which takes commands from the Client application and converts that command to XMLA  messages for the Analysis Services Instance.AMO shows analysis services instance objects as classes to the user end application.

The above Diagram shows the analysis Services components architecture. Including all major elements performing within the Analysis Services Instance and all user elements, that interact with the Instance by using Analysis listener of  XML  by using HTTP or TCP.

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What is XML Listener?

It handles all the XMLA Communications between Analysis Services and its Clients.Its port configuration Setting is msmdsrv.ini.this file is used to specify a port on which the analysis Services listens.The value 0 (zero) in this file that analysis services listen to the default port .it uses the following ports.




Default Instance of  SQL Server Analysis Services.


Redirect for the other Instances of SQL Server Analysis Services.

Dynamically Assigned

Named Instance SQL  Server Analysis Services at Server Startup.

local qubes for multidimensional data

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To write, create, and delete local cubes, should upload and execute either an ASSL Script or an AMO Program.

Local cubes and local mining models performs analysis on a client workstation, while it is disconnected from network

For example,  a client application will call the OLE DB for OLAP 9.0 provider which uploads the local cube engine to create and query local cubes as shown in the above diagram.

Server-based local cubes by this we can create globe cube statement

Relational data source cube with this you can start and proceed a cube from an OLE DB relational database.

Overview of Microsoft OLAP Logical Architecture

SQL Server uses, both Server and Client Components to Implement Online Analytical Processing (OLAP) and Data Mining functions for all Business Intelligence Apps.The analysis server component is configured as Microsoft Windows service. It Supports Multi Examples on the same computer, with each example of analysis Services Implemented, as a unique example of the Windows Service.

All clients around the world communicate with analysis services by using XML, a SOAP-based Protocol, For Issuing Commands and receiving responses, exposed as web service. Client’s models are also exposed by XMLA and can be Accessed by using a managed provider ADOMD.NET or a native OLE DB Provider.

Query Commands can be implemented, by this language Multidimensional Expressions (MDX) an industry standard query language for analysis or Data mining Extensions (DMX).An industry-oriented query language accepted towards Data Mining. To manage analysis Services Database objects analysis services scripting language (ASSL) is used.

Advantages of SSAS

1) It can store Hierarchies

2) It can handle more users than a data warehouse can handle

3) It handles automatically changing Dimensions

4It can use analysis services data mining

5) It can tool like performance point and power view

 Recommended Audience

1) Developers.

2) Project Managers.

3) Analytical Professionals.

4) ETL Professionals.

5) People who are Interested in Maintaining the Data.


It is good to Have Knowledge on Data Bases. But it is Not Mandatory and there is no necessity for the Knowledge of Programming Language.

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