SSIS - SQL Server Integration Services
Q: What is SSIS? How it related with SQL Server.
SQL Server Integration Services (SSIS) is a component of SQL Server which can be used to perform a wide range of Data Migration and ETL operations. SSIS is a component in MSBI process of SQL Server.
This is a platform for Integration and Workflow applications. It is known for a fast and flexible OLTP and OLAP extensions used for data extraction, transformation, and loading (ETL). The tool may also be used to automate maintenance of SQL Server databases and multidimensional data sets.
SQL Server Integration Services (SSIS) is a component of SQL Server which can be used to perform a wide range of Data Migration and ETL operations. SSIS is a component in MSBI process of SQL Server.
This is a platform for Integration and Workflow applications. It is known for a fast and flexible OLTP and OLAP extensions used for data extraction, transformation, and loading (ETL). The tool may also be used to automate maintenance of SQL Server databases and multidimensional data sets.
Q: What are the tools associated with SSIS?
We use Business Intelligence Development Studio (BIDS) and SQL Server Management Studio (SSMS) to work with Development of SSIS Projects.
We use SSMS to manage the SSIS Packages and Projects.
We use Business Intelligence Development Studio (BIDS) and SQL Server Management Studio (SSMS) to work with Development of SSIS Projects.
We use SSMS to manage the SSIS Packages and Projects.
Q: What are the differences between DTS and SSIS
Data Transformation Services
| SQL Server Integration Services
|
Limited Error Handling
| Complex and powerful Error Handling
|
Message Boxes in ActiveX Scripts
| Message Boxes in .NET Scripting
|
No Deployment Wizard
| Interactive Deployment Wizard
|
Limited Set of Transformation
| Good number of Transformations
|
NO BI functionality
| Complete BI Integration
|
Q: What is a workflow in SSIS ?
Workflow is a set of instructions on to specify the Program Executor on how to execute tasks and containers within SSIS Packages.
Q: What is the control flow?
Workflow is a set of instructions on to specify the Program Executor on how to execute tasks and containers within SSIS Packages.
Q: What is the control flow?
A control flow consists of one or more tasks and containers that execute when the package runs. To control order or define the conditions for running the next task or container in the package control flow, we use precedence constraints to connect the tasks and containers in a package. A subset of tasks and containers can also be grouped and run repeatedly as a unit within the package control flow. SQL Server 2005 Integration Services (SSIS) provides three different types of control flow elements: Containers that provide structures in packages, Tasks that provide functionality, and Precedence Constraints that connect the executables, containers, and tasks into an ordered control flow.
Q: What is a data flow?
A data flow consists of the sources and destinations that extract and load data, the transformations that modify and extend data, and the paths that link sources, transformations, and destinations The Data Flow task is the executable within the SSIS package that creates, orders, and runs the data flow. A separate instance of the data flow engine is opened for each Data Flow task in a package. Data Sources, Transformations, and Data Destinations are the three important categories in the Data Flow.
A data flow consists of the sources and destinations that extract and load data, the transformations that modify and extend data, and the paths that link sources, transformations, and destinations The Data Flow task is the executable within the SSIS package that creates, orders, and runs the data flow. A separate instance of the data flow engine is opened for each Data Flow task in a package. Data Sources, Transformations, and Data Destinations are the three important categories in the Data Flow.
Q: How does Error-Handling work in SSIS
When a data flow component applies a transformation to column data, extracts data from sources, or loads data into destinations, errors can occur. Errors frequently occur because of unexpected data values.
Type of typical Errors in SSIS:
-Data Connection Errors, which occur incase the connection manager cannot be initialized with the connection string. This applies to both Data Sources and Data Destinations along with Control Flows that use the Connection Strings.
-Data Transformation Errors, which occur while data is being transformed over a Data Pipeline from Source to Destination.
-Expression Evaluation errors, which occur if expressions that are evaluated at run time perform invalid
When a data flow component applies a transformation to column data, extracts data from sources, or loads data into destinations, errors can occur. Errors frequently occur because of unexpected data values.
Type of typical Errors in SSIS:
-Data Connection Errors, which occur incase the connection manager cannot be initialized with the connection string. This applies to both Data Sources and Data Destinations along with Control Flows that use the Connection Strings.
-Data Transformation Errors, which occur while data is being transformed over a Data Pipeline from Source to Destination.
-Expression Evaluation errors, which occur if expressions that are evaluated at run time perform invalid
Q: What is environment variable in SSIS?
An environment variable configuration sets a package property equal to the value in an environment variable.
Environmental configurations are useful for configuring properties that are dependent on the computer that is executing the package.
An environment variable configuration sets a package property equal to the value in an environment variable.
Environmental configurations are useful for configuring properties that are dependent on the computer that is executing the package.
Q: What are the Transformations available in SSIS?
AGGEGATE - It applies aggregate functions to Record Sets to produce new output records from aggregated values.
AUDIT - Adds Package and Task level Metadata - such as Machine Name, Execution Instance, Package Name, Package ID, etc..
CHARACTER MAP - Performs SQL Server level makes string data changes such as changing data from lower case to upper case.
CONDITIONAL SPLIT – Separates available input into separate output pipelines based on Boolean Expressions configured for each output.
COPY COLUMN - Add a copy of column to the output we can later transform the copy keeping the original for auditing.
DATA CONVERSION - Converts columns data types from one to another type. It stands for Explicit Column Conversion.
DATA MINING QUERY – Used to perform data mining query against analysis services and manage Predictions Graphs and Controls.
DERIVED COLUMN - Create a new (computed) column from given expressions.
EXPORT COLUMN – Used to export a Image specific column from the database to a flat file.
FUZZY GROUPING – Used for data cleansing by finding rows that are likely duplicates.
FUZZY LOOKUP - Used for Pattern Matching and Ranking based on fuzzy logic.
IMPORT COLUMN - Reads image specific column from database onto a flat file.
LOOKUP - Performs the lookup (searching) of a given reference object set against a data source. It is used for exact matches only.
MERGE - Merges two sorted data sets into a single data set into a single data flow.
MERGE JOIN - Merges two data sets into a single dataset using a join junction.
MULTI CAST - Sends a copy of supplied Data Source onto multiple Destinations.
ROW COUNT - Stores the resulting row count from the data flow / transformation into a variable.
ROW SAMPLING - Captures sample data by using a row count of the total rows in dataflow specified by rows or percentage.
UNION ALL - Merge multiple data sets into a single dataset.
PIVOT – Used for Normalization of data sources to reduce analomolies by converting rows into columns
UNPIVOT – Used for demoralizing the data structure by converts columns into rows incase of building Data Warehouses.
AGGEGATE - It applies aggregate functions to Record Sets to produce new output records from aggregated values.
AUDIT - Adds Package and Task level Metadata - such as Machine Name, Execution Instance, Package Name, Package ID, etc..
CHARACTER MAP - Performs SQL Server level makes string data changes such as changing data from lower case to upper case.
CONDITIONAL SPLIT – Separates available input into separate output pipelines based on Boolean Expressions configured for each output.
COPY COLUMN - Add a copy of column to the output we can later transform the copy keeping the original for auditing.
DATA CONVERSION - Converts columns data types from one to another type. It stands for Explicit Column Conversion.
DATA MINING QUERY – Used to perform data mining query against analysis services and manage Predictions Graphs and Controls.
DERIVED COLUMN - Create a new (computed) column from given expressions.
EXPORT COLUMN – Used to export a Image specific column from the database to a flat file.
FUZZY GROUPING – Used for data cleansing by finding rows that are likely duplicates.
FUZZY LOOKUP - Used for Pattern Matching and Ranking based on fuzzy logic.
IMPORT COLUMN - Reads image specific column from database onto a flat file.
LOOKUP - Performs the lookup (searching) of a given reference object set against a data source. It is used for exact matches only.
MERGE - Merges two sorted data sets into a single data set into a single data flow.
MERGE JOIN - Merges two data sets into a single dataset using a join junction.
MULTI CAST - Sends a copy of supplied Data Source onto multiple Destinations.
ROW COUNT - Stores the resulting row count from the data flow / transformation into a variable.
ROW SAMPLING - Captures sample data by using a row count of the total rows in dataflow specified by rows or percentage.
UNION ALL - Merge multiple data sets into a single dataset.
PIVOT – Used for Normalization of data sources to reduce analomolies by converting rows into columns
UNPIVOT – Used for demoralizing the data structure by converts columns into rows incase of building Data Warehouses.
Q: How to log SSIS Executions?
SSIS includes logging features that write log entries when run-time events occur and can also write custom messages. This is not enabled by default. Integration Services supports a diverse set of log providers, and gives you the ability to create custom log providers. The Integration Services log providers can write log entries to text files, SQL Server Profiler, SQL Server, Windows Event Log, or XML files. Logs are associated with packages and are configured at the package level. Each task or container in a package can log information to any package log. The tasks and containers in a package can be enabled for logging even if the package itself is not.
SSIS includes logging features that write log entries when run-time events occur and can also write custom messages. This is not enabled by default. Integration Services supports a diverse set of log providers, and gives you the ability to create custom log providers. The Integration Services log providers can write log entries to text files, SQL Server Profiler, SQL Server, Windows Event Log, or XML files. Logs are associated with packages and are configured at the package level. Each task or container in a package can log information to any package log. The tasks and containers in a package can be enabled for logging even if the package itself is not.
Q: How do you deploy SSIS packages.
BUILDing SSIS Projects provides a Deployment Manifest File. We need to run the manifest file and decide whether to deploy this onto File System or onto SQL Server [ msdb]. SQL Server Deployment is very faster and more secure then File System Deployment. Alternatively, we can also import the package from SSMS from File System or SQ Server.
BUILDing SSIS Projects provides a Deployment Manifest File. We need to run the manifest file and decide whether to deploy this onto File System or onto SQL Server [ msdb]. SQL Server Deployment is very faster and more secure then File System Deployment. Alternatively, we can also import the package from SSMS from File System or SQ Server.
Q: What are variables and what is variable scope ?
Variables store values that a SSIS package and its containers, tasks, and event handlers can use at run time. The scripts in the Script task and the Script component can also use variables. The precedence constraints that sequence tasks and containers into a workflow can use variables when their constraint definitions include expressions. Integration Services supports two types of variables: user-defined variables and system variables. User-defined variables are defined by package developers, and system variables are defined by Integration Services. You can create as many user-defined variables as a package requires, but you cannot create additional system variables.
Variables store values that a SSIS package and its containers, tasks, and event handlers can use at run time. The scripts in the Script task and the Script component can also use variables. The precedence constraints that sequence tasks and containers into a workflow can use variables when their constraint definitions include expressions. Integration Services supports two types of variables: user-defined variables and system variables. User-defined variables are defined by package developers, and system variables are defined by Integration Services. You can create as many user-defined variables as a package requires, but you cannot create additional system variables.
Q: Can you name five of the Perfmon counters for SSIS and the value they provide?
- SQLServer:SSIS Service
- SSIS Package Instances
- SQLServer:SSIS Pipeline
- BLOB bytes read
- BLOB bytes written
- BLOB files in use
- Buffer memory
- Buffers in use
- Buffers spooled
- Flat buffer memory
- Flat buffers in use
- Private buffer memory
- Private buffers in use
- Rows read
- Rows written
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).
Q: What is the difference between a derived measure and a calculated measure?
The difference between a derived measure and a calculated measure is when the calculation is performed. A derived measure is calculated before aggregations are created, and the values of the derived measure are stored in the cube. A calculated measure is calculated after aggregations are created, and the values of a calculated measure aren’t stored in the cube. The primary criterion for choosing between a derived measure and a calculated measure is not efficiency, but accuracy.
The difference between a derived measure and a calculated measure is when the calculation is performed. A derived measure is calculated before aggregations are created, and the values of the derived measure are stored in the cube. A calculated measure is calculated after aggregations are created, and the values of a calculated measure aren’t stored in the cube. The primary criterion for choosing between a derived measure and a calculated measure is not efficiency, but accuracy.
Q: What is a partition?
A partition in Analysis Services is the physical location of stored cube data. Every cube has at least one partition by default. Each time we create a measure group, another partition is created. Queries run faster against a partitioned cube because Analysis Services only needs to read data from the partitions that contain the answers to the queries. Queries run even faster when partition also stores aggregations, the pre calculated totals for additive measures. Partitions are a powerful and flexible means of managing cubes, especially large cubes.
A partition in Analysis Services is the physical location of stored cube data. Every cube has at least one partition by default. Each time we create a measure group, another partition is created. Queries run faster against a partitioned cube because Analysis Services only needs to read data from the partitions that contain the answers to the queries. Queries run even faster when partition also stores aggregations, the pre calculated totals for additive measures. Partitions are a powerful and flexible means of managing cubes, especially large cubes.
Q: While creating a new calculated member in a cube what is the use of property
called non-empty behavior?
Nonempty behavior is important property for ratio calculations. If the denominator Is empty, an MDX expression will return an error just as it would if the denominator Were equal to zero. By selecting one or more measures for the Non-Empty Behavior property, we are establishing a requirement that each selected measure first be evaluated before the calculation expression is evaluated. If each selected measure is empty, then The expression is also treated as empty and no error is returned.
called non-empty behavior?
Nonempty behavior is important property for ratio calculations. If the denominator Is empty, an MDX expression will return an error just as it would if the denominator Were equal to zero. By selecting one or more measures for the Non-Empty Behavior property, we are establishing a requirement that each selected measure first be evaluated before the calculation expression is evaluated. If each selected measure is empty, then The expression is also treated as empty and no error is returned.
Q: What is a RAGGED hierarchy?
Under normal circumstances, each level in a hierarchy in Microsoft SQL Server 2005 Analysis Services (SSAS) has the same number of members above it as any other member at the same level. In a ragged hierarchy, the logical parent member of at least one member is not in the level immediately above the member. When this occurs, the hierarchy descends to different levels for different drilldown paths. Expanding through every level for every drilldown path is then unnecessarily complicated.
Under normal circumstances, each level in a hierarchy in Microsoft SQL Server 2005 Analysis Services (SSAS) has the same number of members above it as any other member at the same level. In a ragged hierarchy, the logical parent member of at least one member is not in the level immediately above the member. When this occurs, the hierarchy descends to different levels for different drilldown paths. Expanding through every level for every drilldown path is then unnecessarily complicated.
Q: What are the roles of an Analysis Services Information Worker?
The role of an Analysis Services information worker is the traditional "domain expert" role in business intelligence (BI) someone who understands the data employed by a solution and is able to translate the data into business information. The role of an Analysis Services information worker often has one of the following job titles: Business Analyst (Report Consumer), Manager (Report Consumer), Technical Trainer, Help Desk/Operation, or Network Administrator.
Q: What are the different ways of creating Aggregations?
We can create aggregations for faster MDX statements using Aggregation Wizard or thru UBO – Usage Based Optimizations. Always, prefer UBO method in realtime performance troubleshooting.
We can create aggregations for faster MDX statements using Aggregation Wizard or thru UBO – Usage Based Optimizations. Always, prefer UBO method in realtime performance troubleshooting.
Q: What is WriteBack? What are the pre-conditions?
The Enable/Disable Writeback dialog box enables or disables writeback for a measure group in a cube. Enabling writeback on a measure group defines a writeback partition and creates a writeback table for that measure group. Disabling writeback on a measure group removes the writeback partition but does not delete the writeback table, to avoid unanticipated data loss.
The Enable/Disable Writeback dialog box enables or disables writeback for a measure group in a cube. Enabling writeback on a measure group defines a writeback partition and creates a writeback table for that measure group. Disabling writeback on a measure group removes the writeback partition but does not delete the writeback table, to avoid unanticipated data loss.
Q: What is processing?
Processing is a critical and resource intensive operation in the data warehouse lifecycle and needs to be carefully optimized and executed. Analysis Services 2005 offers a high performance and scalable processing architecture with a comprehensive set of controls for database administrators.
We can process an OLAP database, individual cube, Dimension or a specific Partition in a cube.
Processing is a critical and resource intensive operation in the data warehouse lifecycle and needs to be carefully optimized and executed. Analysis Services 2005 offers a high performance and scalable processing architecture with a comprehensive set of controls for database administrators.
We can process an OLAP database, individual cube, Dimension or a specific Partition in a cube.
Q: Name few Business Analysis Enhancements for SSAS?
The following table lists the business intelligence enhancements that are available in Microsoft SQL Server 2005 Analysis Services (SSAS). The table also shows the cube or dimension to which each business intelligence enhancement applies, and indicates whether an enhancement can be applied to an object that was created without using a data source and for which no schema has been generated.
The following table lists the business intelligence enhancements that are available in Microsoft SQL Server 2005 Analysis Services (SSAS). The table also shows the cube or dimension to which each business intelligence enhancement applies, and indicates whether an enhancement can be applied to an object that was created without using a data source and for which no schema has been generated.
| Enhancement | Type | Applied to | No data source |
| Time Intelligence | Cube | Cube | No |
| Account Intelligence | Dimension | Dimension or cube | No |
| Dimension Intelligence | Dimension | Dimension or cube | Yes |
| Custom Aggregation | Dimension | Dimension (unary operator) or cube | No |
| Semiadditive Behavior | Cube | Cube | Yes> |
| Custom Member Formula | Dimension | Dimension or cube | No |
| Custom Sorting and Uniqueness Settings | Dimension | Dimension or cube | Yes |
| Dimension Writeback | Dimension | Dimension or cube | Yes |
Q: What MDX functions do you most commonly use?
This is a great question because you only know this answer by experience. If you ask me this question, the answer practically rushes out of me. “CrossJoin, Descendants, and NonEmpty, in addition to Sum, Count, and Aggregate. My personal favorite is CrossJoin because it allows me identify non-contiguous slices of the cube and aggregate even though those cube cells don’t roll up to a natural ancestor.” Indeed, CrossJoin has easily been my bread and butter.
This is a great question because you only know this answer by experience. If you ask me this question, the answer practically rushes out of me. “CrossJoin, Descendants, and NonEmpty, in addition to Sum, Count, and Aggregate. My personal favorite is CrossJoin because it allows me identify non-contiguous slices of the cube and aggregate even though those cube cells don’t roll up to a natural ancestor.” Indeed, CrossJoin has easily been my bread and butter.
Q: Where do you put calculated members?
The reflexive answer is “in the Measures dimension” but this is the obvious answer. So I always follow up with another question. “If you want to create a calculated member that intersects all measures, where do you put it?” A high percentage of candidates can’t answer this question, and the answer is “In a dimension other than Measures.” If they can answer it, I immediately ask them why. The answer is “Because a member in a dimension cannot intersect its own relatives in that dimension.”
The reflexive answer is “in the Measures dimension” but this is the obvious answer. So I always follow up with another question. “If you want to create a calculated member that intersects all measures, where do you put it?” A high percentage of candidates can’t answer this question, and the answer is “In a dimension other than Measures.” If they can answer it, I immediately ask them why. The answer is “Because a member in a dimension cannot intersect its own relatives in that dimension.”
Q: How do I find the bottom 10 customers with the lowest sales in 2003 that were not null?
A: Simply using bottomcount will return customers with null sales. You will have to combine it with NONEMPTY or FILTER.
SELECT { [Measures].[Internet Sales Amount] } ON COLUMNS ,
BOTTOMCOUNT(
NONEMPTY(DESCENDANTS( [Customer].[Customer Geography].[All Customers]
, [Customer].[Customer Geography].[Customer] )
, ( [Measures].[Internet Sales Amount] ) )
, 10
, ( [Measures].[Internet Sales Amount] )
) ON ROWS
FROM [Adventure Works]
WHERE ( [Date].[Calendar].[Calendar Year].&[2003] ) ;
Q: How in MDX query can I get top 3 sales years based on order quantity?
By default Analysis Services returns members in an order specified during attribute design. Attribute properties that define ordering are "OrderBy" and "OrderByAttribute". Lets say we want to see order counts for each year. In Adventure Works MDX query would be:
SELECT {[Measures].[Reseller Order Quantity]} ON 0
, [Date].[Calendar].[Calendar Year].Members ON 1
FROM [Adventure Works];
Same query using TopCount:
SELECT
{[Measures].[Reseller Order Quantity]} ON 0,
TopCount([Date].[Calendar].[Calendar Year].Members,3, [Measures].[Reseller Order Quantity]) ON 1
FROM [Adventure Works];
By default Analysis Services returns members in an order specified during attribute design. Attribute properties that define ordering are "OrderBy" and "OrderByAttribute". Lets say we want to see order counts for each year. In Adventure Works MDX query would be:
SELECT {[Measures].[Reseller Order Quantity]} ON 0
, [Date].[Calendar].[Calendar Year].Members ON 1
FROM [Adventure Works];
Same query using TopCount:
SELECT
{[Measures].[Reseller Order Quantity]} ON 0,
TopCount([Date].[Calendar].[Calendar Year].Members,3, [Measures].[Reseller Order Quantity]) ON 1
FROM [Adventure Works];
Q: How do you extract first tuple from the set?
Use could usefunction Set.Item(0)
Example:
SELECT {{[Date].[Calendar].[Calendar Year].Members
}.Item(0)}
ON 0
FROM [Adventure Works]
Use could usefunction Set.Item(0)
Example:
SELECT {{[Date].[Calendar].[Calendar Year].Members
}.Item(0)}
ON 0
FROM [Adventure Works]
Q: How can I setup default dimension member in Calculation script?
You can use ALTER CUBE statement. Syntax:
ALTER CUBE CurrentCube | YourCubeName UPDATE DIMENSION , DEFAULT_MEMBER='';
You can use ALTER CUBE statement. Syntax:
ALTER CUBE CurrentCube | YourCubeName UPDATE DIMENSION , DEFAULT_MEMBER='';
