MDX tutorial
MDX (Multidimensional Expressions) is a query language for OLAP databases, much like
SQL is a query language ...
MDX tutorial

SELECT
[Measures].[Amount] ON COLUMNS
FROM
[Car Transactions]
Number of cars sold.
The SELECT clause defines...
MDX tutorial

SELECT
[Measures].[Price] ON COLUMNS,
[Cars].[Category].MEMBERS ON ROWS
FROM
[Car Transactions]
Total price ...
MDX tutorial
FROM
Car Transactions
Cube name contains a space, so it have to be enclosed by square brackets.
SELECT
[Cars]...
MDX tutorial
SELECT
[Measures].MEMBERS ON COLUMNS,
NONEMPTY([Cars].[Category].MEMBERS) ON ROWS
FROM
[Car Transactions]
The...
Upcoming SlideShare
Loading in …5
×

MDX introduction

857 views

Published on

MDX (Multidimensional Expressions) is a query language for OLAP databases, much like SQL is a query language for relational databases. Tutorial presents introduction to MDX. Watch video lesson, visit http://www.learn-with-video-tutorials.com/mdx-video-tutorial

Published in: Education, Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
857
On SlideShare
0
From Embeds
0
Number of Embeds
2
Actions
Shares
0
Downloads
36
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

MDX introduction

  1. 1. MDX tutorial MDX (Multidimensional Expressions) is a query language for OLAP databases, much like SQL is a query language for relational databases. It is also a calculation language, with syntax similar to spreadsheet formulas. MDX is used to interact with data in Microsoft SQL Server Analysis Services cubes. It is a versatile and powerful language but one that requires you to approach data in a whole new way. With relational databases, the SQL language is used to assemble sets of data. With Analysis Services, the MDX language is used to assemble tuples identifying points of data within an n-dimensional space. The Data Warehouse layer is the heart of the business intelligence environment. In this layer, data from across the enterprise is presented as a unifi ed whole and in a manner focused more on business processes and less on the source systems from which the data originates. The dimensional model has been widely embraced as the data model of choice within the Data Warehouse layer. Within the dimensional model, business processes and events are presented as facts. Measurements associated with these facts, known as fact measures, provide a means of evaluating the represented business process or event. Facts and their fact measures are of little value without their associated descriptive details. These details, referred to as attributes, provide the means by which facts are sliced (filtered) and diced (grouped). Attributes are organized in dimensions with closely related attributes residing in the same dimension. Within Analysis Services, the dimensional model is presented as an object referred to as a cube. Within the cube, facts are translated into measure groups. Measure groups contain one or more measures, corresponding to fact measures in the dimensional model. Through the cube, dimensions are presented as cube dimensions. Relationships between the measure groups and cube dimensions are maintained as metadata within the cube and are automatically employed as users interact with it. Within a cube dimension, attributes are presented as either attribute-hierarchies or properties. An attribute is presented as an attribute-hierarchy when the attribute is intended to be used to slice and dice the data. When an attribute is intended to provide supplemental information or to be used for simply filtering other attributes, it is best employed as a property. Relationships between attributes within a dimension are explicitly defined. As with the relationships between measure groups and cube dimensions, this information is maintained within the multidimensional database and automatically employed as users interact with the cube Here is the sample cube schema. http://www.learn-with-video-tutorials.com/mdx-video-tutorial
  2. 2. MDX tutorial SELECT [Measures].[Amount] ON COLUMNS FROM [Car Transactions] Number of cars sold. The SELECT clause defines which dimension members to include on each exis of the reprot and the FROM clause names the cube that is being queried. The query contains no dimension members. To display the number of transactions we should execute the following query. SELECT [Measures].[Transactions Facts Table Count] ON COLUMNS FROM [Car Transactions] If we create a query that has only one axis, it must be the column axis. http://www.learn-with-video-tutorials.com/mdx-video-tutorial
  3. 3. MDX tutorial SELECT [Measures].[Price] ON COLUMNS, [Cars].[Category].MEMBERS ON ROWS FROM [Car Transactions] Total price of cars sold by category The MEMBERS() function returns the set of members in a dimension, level or hierarchy. The query returns the total sales price in each category. SELECT [Cars].[Category].MEMBERS ON ROWS, [Measures].[Price] ON COLUMNS FROM [Car Transactions] If we create two axes, one must be the column axis and one must be the row axis, although it doesn't matter in which order they appear within the query. SELECT Cars.Category.MEMBERS ON ROWS, Measures.Price ON COLUMNS FROM [Car Transactions] The square brackets around a particular object identifier are optional as long as the object identifier is not one of reserver words and does not otherwise contain any characters other than letters, numbers or underscores. SELECT Cars.Category.MEMBERS ON ROWS, Measures.Price ON COLUMNS http://www.learn-with-video-tutorials.com/mdx-video-tutorial
  4. 4. MDX tutorial FROM Car Transactions Cube name contains a space, so it have to be enclosed by square brackets. SELECT [Cars].[Category].MEMBERS ON AXIS(0), [Measures].[Price] ON AXIS(1) FROM [Car Transactions] The terms COLUMNS and ROWS are simply aliases for the true names of the axes: Axis(0) and Axis(1) respectively. Technically, an MDX query can have up to 128 axes, with aliases for the first five: Columns, Rows, Pages, Sections and Chapters. This fact make it clearer to understand why a single-axis report must have a COLUMNS axis (Axis(0)) but not a ROW axis (Axis(1)). Although our query may be correct with three axes, SQL Server Management Studio can only render bidimensional results. SELECT [Cars].[Category].MEMBERS ON COLUMNS, [Cars].[Country].[Country] ON ROWS, [Measures].[Price] ON PAGES FROM [Car Transactions] If we want do display 3D results we need to find software that can present cube data more elaborately. SELECT [Measures].[Price] ON COLUMNS, NONEMPTY([Cars].[Category].MEMBERS) ON ROWS FROM [Car Transactions] The NONEMPTY() function returns the tuples that are non-empty. http://www.learn-with-video-tutorials.com/mdx-video-tutorial
  5. 5. MDX tutorial SELECT [Measures].MEMBERS ON COLUMNS, NONEMPTY([Cars].[Category].MEMBERS) ON ROWS FROM [Car Transactions] The MEMBERS() function can be used with measures dimension: returns only measures defined directly on the cube - calculated members are not displayed. SELECT ADDCALCULATEDMEMBERS([Measures].MEMBERS) ON COLUMNS, NONEMPTY([Cars].[Category].MEMBERS) ON ROWS FROM [Car Transactions] The ADDCALCULATEDMEMBERS() function returns all measures, even calculated members, from the measures dimension when the calculated members have not been explicitly specified in the query. SELECT [Measures].ALLMEMBERS ON COLUMNS, NONEMPTY([Cars].[Category].MEMBERS) ON ROWS FROM [Car Transactions] The ALLMEMBERS() function returns a set that consists of all members of the supplied level. Watch video lesson, visit http://www.learn-with-video-tutorials.com/mdx-video-tutorial http://www.learn-with-video-tutorials.com/mdx-video-tutorial

×