What Is Attribute Relationships, Why We Need It?
Attribute relationships are the way of telling the analysis service engine that how the attributes are related with each other. It will help to relate two or more attributes to each other.Processing time will be decreased if proper relationships are given. This increases the Cube Processing performance and MDX query performance too.
In Microsoft SQL Server Analysis Services, attributes within a dimension are always related either directly or indirectly to the key attribute. When you define a dimension based on a star schema, which is where all dimension attributes are derived from the same relational table, an attribute relationship is automatically defined between the key attribute and each non-key attribute of the dimension.
When you define a dimension based on a snowflake schema, which is where dimension attributes are derived from multiple related tables, an attribute relationship is automatically defined as follows
Between the key attribute and each non-key attribute bound to columns in the main dimension table.
Between the key attribute and the attribute bound to the foreign key in the secondary table that links the underlying dimension tables.
Between the attribute bound to foreign key in the secondary table and each non-key attribute bound to columns from the secondary table.
What Is Data Source View Or Dsv?
A data source view is a persistent set of tables from a data source that supply the data for a particular cube. BIDS also includes a wizard for creating data source views, which you can invoke by right-clicking on the Data Source Views folder in Solution Explorer.
Datasource view is the logical view of the data in the data source.
Data source view is the only thing a cube can see.
What Is Named Calculation?
A named calculation is a SQL expression represented as a calculated column. This expression appears and behaves as a column in the table. A named calculation lets you extend the relational schema of existing tables or views in a data source view without modifying the tables or views in the underlying data source.
Named calculation is used to create a new column in the DSV using hard coded values or by using existing columns or even with both.
What Is A Data Source Or Ds?
The data source is the Physical Connection information that analysis service uses to connect to the database that host the data. The data source contains the connection string which specifies the server and the database hosting the data as well as any necessary authentication credentials.
Explain The Flow Of Creating A Cube?
Steps to create a cube in ssas
Create a data source.
Create a datasource view.
Create Dimensions
Create a cube.
Deploy and Process the cube.
What Is Amo?
The full form of AMO is Analysis Management Objects. This is used to create or alter cubes from .NET code.
After Creating The Cube, If We Added A New Column To The Oltp Table Then How You Add This New Attribute To The Cube?
Just open the datasourceview and on right click we find the option REFRESH. Click the REFRESH then it will add new attributes to the table which can be added to Cube.
What Is A Cube?
The basic unit of storage and analysis in Analysis Services is the cube. A cube is a collection of data that’s been aggregated to allow queries to return data quickly.
For example, a cube of order data might be aggregated by time period and by title, making the cube fast when you ask Questions concerning orders by week or orders by title.
What Are The Types Of Processing And Explain Each?
They are 6 types of processing in ssas ,they are
Process Full
Process Data
Process Index
Process Incremental
Process Structure
UnProcess
What Are The Difference Between Data Mart And Data Warehouse?
Datawarehouse is complete data where as Data mart is Subset of the same.
Ex: All the organisation data may related to finance department, HR, banking dept are stored in data warehouse where as in data mart only finance data or HR department data will be stored. So data warehouse is a collection of different data marts.
What Is Data Mart?
A data mart is a subset of an organizational data store, usually oriented to a specific purpose or major data subject that may be distributed to support business needs. Data marts are analytical data stores designed to focus on specific business functions for a specific community within an organization.
Data marts are often derived from subsets of data in a data warehouse, though in the bottom-up data warehouse design methodology the data warehouse is created from the union of organizational data marts.
They are 3 types of data mart they are
Dependent
Independent
Logical data mart
What Is Data Warehouse In Short Dwh?
The data warehouse is an informational environment that
Provides an integrated and total view of the enterprise
Makes the enterprise’s current and historical information easily available for decision making
Makes decision-support transactions possible without hindering operational systems
Renders the organization’s information consistent
Presents a flexible and interactive source of strategic information
Attribute relationships are the way of telling the analysis service engine that how the attributes are related with each other. It will help to relate two or more attributes to each other.Processing time will be decreased if proper relationships are given. This increases the Cube Processing performance and MDX query performance too.
In Microsoft SQL Server Analysis Services, attributes within a dimension are always related either directly or indirectly to the key attribute. When you define a dimension based on a star schema, which is where all dimension attributes are derived from the same relational table, an attribute relationship is automatically defined between the key attribute and each non-key attribute of the dimension.
When you define a dimension based on a snowflake schema, which is where dimension attributes are derived from multiple related tables, an attribute relationship is automatically defined as follows
Between the key attribute and each non-key attribute bound to columns in the main dimension table.
Between the key attribute and the attribute bound to the foreign key in the secondary table that links the underlying dimension tables.
Between the attribute bound to foreign key in the secondary table and each non-key attribute bound to columns from the secondary table.
What Is Data Source View Or Dsv?
A data source view is a persistent set of tables from a data source that supply the data for a particular cube. BIDS also includes a wizard for creating data source views, which you can invoke by right-clicking on the Data Source Views folder in Solution Explorer.
Datasource view is the logical view of the data in the data source.
Data source view is the only thing a cube can see.
What Is Named Calculation?
A named calculation is a SQL expression represented as a calculated column. This expression appears and behaves as a column in the table. A named calculation lets you extend the relational schema of existing tables or views in a data source view without modifying the tables or views in the underlying data source.
Named calculation is used to create a new column in the DSV using hard coded values or by using existing columns or even with both.
What Is A Data Source Or Ds?
The data source is the Physical Connection information that analysis service uses to connect to the database that host the data. The data source contains the connection string which specifies the server and the database hosting the data as well as any necessary authentication credentials.
Explain The Flow Of Creating A Cube?
Steps to create a cube in ssas
Create a data source.
Create a datasource view.
Create Dimensions
Create a cube.
Deploy and Process the cube.
What Is Amo?
The full form of AMO is Analysis Management Objects. This is used to create or alter cubes from .NET code.
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| Datamatics Most Frequently Asked Latest SSAS Interview Questions Answers |
After Creating The Cube, If We Added A New Column To The Oltp Table Then How You Add This New Attribute To The Cube?
Just open the datasourceview and on right click we find the option REFRESH. Click the REFRESH then it will add new attributes to the table which can be added to Cube.
What Is A Cube?
The basic unit of storage and analysis in Analysis Services is the cube. A cube is a collection of data that’s been aggregated to allow queries to return data quickly.
For example, a cube of order data might be aggregated by time period and by title, making the cube fast when you ask Questions concerning orders by week or orders by title.
What Are The Types Of Processing And Explain Each?
They are 6 types of processing in ssas ,they are
Process Full
Process Data
Process Index
Process Incremental
Process Structure
UnProcess
What Are The Difference Between Data Mart And Data Warehouse?
Datawarehouse is complete data where as Data mart is Subset of the same.
Ex: All the organisation data may related to finance department, HR, banking dept are stored in data warehouse where as in data mart only finance data or HR department data will be stored. So data warehouse is a collection of different data marts.
What Is Data Mart?
A data mart is a subset of an organizational data store, usually oriented to a specific purpose or major data subject that may be distributed to support business needs. Data marts are analytical data stores designed to focus on specific business functions for a specific community within an organization.
Data marts are often derived from subsets of data in a data warehouse, though in the bottom-up data warehouse design methodology the data warehouse is created from the union of organizational data marts.
They are 3 types of data mart they are
Dependent
Independent
Logical data mart
What Is Data Warehouse In Short Dwh?
The data warehouse is an informational environment that
Provides an integrated and total view of the enterprise
Makes the enterprise’s current and historical information easily available for decision making
Makes decision-support transactions possible without hindering operational systems
Renders the organization’s information consistent
Presents a flexible and interactive source of strategic information
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