SSAS - SQL Server Analysis Services
Q: What is Analysis Services? List out the features?
Microsoft SQL Server 2005 Analysis Services (SSAS) delivers online analytical processing (OLAP) and data mining functionality for business intelligence applications. Analysis Services supports OLAP by letting we design, create, and manage multidimensional structures that contain data aggregated from other data sources, such as relational databases. For data mining applications, Analysis Services lets we design, create, and visualize data mining models that are constructed from other data sources by using a wide variety of industry-standard
data mining algorithms.
Analysis Services is a middle tier server for analytical processing, OLAP, and Data mining. It manages multidimensional cubes of data and provides access to heaps of information including aggregation of data. One can create data mining models from data sources and use it for Business Intelligence also including reporting features.
Analysis service provides a combined view of the data used in OLAP or Data mining. Services here refer to OLAP, Data mining. Analysis services assists in creating, designing and managing multidimensional structures containing data from varied sources. It provides a wide array of data mining algorithms for specific trends and needs.
Microsoft SQL Server 2005 Analysis Services (SSAS) delivers online analytical processing (OLAP) and data mining functionality for business intelligence applications. Analysis Services supports OLAP by letting we design, create, and manage multidimensional structures that contain data aggregated from other data sources, such as relational databases. For data mining applications, Analysis Services lets we design, create, and visualize data mining models that are constructed from other data sources by using a wide variety of industry-standard
data mining algorithms.
Analysis Services is a middle tier server for analytical processing, OLAP, and Data mining. It manages multidimensional cubes of data and provides access to heaps of information including aggregation of data. One can create data mining models from data sources and use it for Business Intelligence also including reporting features.
Analysis service provides a combined view of the data used in OLAP or Data mining. Services here refer to OLAP, Data mining. Analysis services assists in creating, designing and managing multidimensional structures containing data from varied sources. It provides a wide array of data mining algorithms for specific trends and needs.
Some of the key features are:
- Ease of use with a lot of wizards and designers.
- Flexible data model creation and management
- Scalable architecture to handle OLAP
- Provides integration of administration tools, data sources, security, caching, and reporting etc.
- Provides extensive support for custom applications
Q: What is UDM? Its significance in SSAS?
The role of a Unified Dimensional Model (UDM) is to provide a bridge between the user and the data sources. A UDM is constructed over one or more physical data sources, and then the end user issues queries against the UDM using one of a variety of client tools, such as Microsoft Excel. At a minimum, when the UDM is constructed merely as a thin layer over the data source, the advantages to the end user are a simpler, more readily understood model of the data, isolation from heterogeneous backend data sources, and improved performance for summary type queries. In some scenarios a simple UDM like this is constructed totally automatically. With greater investment in the construction of the UDM, additional benefits accrue from the richness of metadata that the model can provide.
The role of a Unified Dimensional Model (UDM) is to provide a bridge between the user and the data sources. A UDM is constructed over one or more physical data sources, and then the end user issues queries against the UDM using one of a variety of client tools, such as Microsoft Excel. At a minimum, when the UDM is constructed merely as a thin layer over the data source, the advantages to the end user are a simpler, more readily understood model of the data, isolation from heterogeneous backend data sources, and improved performance for summary type queries. In some scenarios a simple UDM like this is constructed totally automatically. With greater investment in the construction of the UDM, additional benefits accrue from the richness of metadata that the model can provide.
The UDM provides the following benefits:
• Allows the user model to be greatly enriched.
• Provides high performance queries supporting interactive analysis, even over huge data volumes.
• Allows business rules to be captured in the model to support richer analysis.
• Allows the user model to be greatly enriched.
• Provides high performance queries supporting interactive analysis, even over huge data volumes.
• Allows business rules to be captured in the model to support richer analysis.
Q: What is the need for SSAS component?
- Analysis Services is the only component in SQL Server using which we can perform Analysis and Forecast operations.
- SSAS is very easy to use and interactive.
- Faster Analysis and Troubleshooting.
- Ability to create and manage Data warehouses.
- Apply efficient Security Principles.
Q: Explain the TWO-Tier Architecture of SSAS?
- SSAS uses both server and client components to supply OLAP and data mining functionality BI Applications.
- The server component is implemented as a Microsoft Windows service. Each instance of Analysis Services implemented as a separate instance of the Windows service.
- Clients communicate with Analysis Services using the standard the XMLA (XML For Analysis) , protocol for issuing commands and receiving responses, exposed as a web service.
Q: What are the components of SSAS?
- An OLAP Engine is used for enabling fast ad hoc queries by end users. A user can interactively explore data by drilling, slicing or pivoting.
- Drilling refers to the process of exploring details of the data.
- Slicing refers to the process of placing data in rows and columns.
- Pivoting refers to switching categories of data between rows and columns.
- In OLAP, we will be using what are called as Dimensional Databases.
Q: What is FASMI ?
A database is called a OLAP Database if the database satisfies the FASMI rules :
A database is called a OLAP Database if the database satisfies the FASMI rules :
- Fast Analysis– is defined in the OLAP scenario in five seconds or less.
- Shared – Must support access to data by many users in the factors of Sensitivity and Write Backs.
- Multidimensional – The data inside the OLAP Database must be multidimensional in structure.
- Information – The OLAP database Must support large volumes of data..
Q: What languages are used in SSAS ?
- Structured Query Language (SQL)
- Multidimensional Expressions (MDX) - an industry standard query language orientated towards analysis
- Data Mining Extensions (DMX) - an industry standard query language oriented toward data mining.
- Analysis Services Scripting Language (ASSL) - used to manage Analysis Services database objects.
Q: How Cubes are implemented in SSAS ?
- Cubes are multidimensional models that store data from one or more sources.
- Cubes can also store aggregations
- SSAS Cubes are created using the Cube Wizard.
- We also build Dimensions when creating Cubes.
- Cubes can see only the DSV( logical View).
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