1. Digvendra Singh

2.  Introduction
◦ What is MDX
◦ Where MDX is required
 Syntax and examples on MDX
 Basics of MDX
 Axis
 Member Reference
 Tuple
 Partial Tuple
 Sets
 Calculated Members
 Calculated Sets
 Functions
 Different reporting scenarios

3.  MDX is a language used for querying and
manipulating data stored in OLAP Cubes (or say
multi-dimensional databases)
 Concept is same as “SQL is a querying language”.
◦ SQL  Relational Database
◦ MDX  Multidimensional Database
 MDX return multidimensional cell-sets that contain
the cube's data

5. OLAP Cube Result (multidimensional
Cube-Sets)
MDX
Reporting Services
(SSRS, SAP TM1, Oracle Essbase,
Microstrategy, Tableau, Cognos etc.)

6. Syntax:
[ WITH <SELECT WITH clause> [ , <SELECT WITH clause>
... ] ]
SELECT [ * | ( <SELECT query axis clause>
[ , <SELECT query axis clause> ... ] ) ]
FROM <SELECT subcube clause>
[ <SELECT slicer axis clause> ]
[ <SELECT cell property list clause> ]
Simplest Syntax:
SELECT {set} ON AXIS(0)
, {set} ON AXIS(1)
FROM [Cube]
WHERE <<data is sliced by some coordinates>>

7. Before getting into details, you should be familiar with basics of Cube
terminology. This include Cube, Measures, Attribute Hierarchy,
Members, Level etc.
For revision please refer the link below:
http://bistuffwithdigven.wordpress.com/2012/10/10/cube-browsing/

8. a. Axis
b. Member Reference
c. Tuple
d. Partial Tuple
e. Sets
f. Calculated Members
g. Calculated Sets

9.  Axes in MDX defines representation plane for data of result
set. Sometimes we put one dimension representing one axis.
For e.g. in 3-D space x,y,z are three axes (figure below)
 In SELECT statement we specify what data on which axes of
result-set, is required
 SELECT statement support 128 axes (i.e. 0 to 127)
 Important axes in MDX are listed below (most used are 0 and
1):
Formal Name Short Name Alias
Axis(0) 0 COLUMNS
Axis(1) 1 ROWS
Axis(2) 2 PAGES
Axis(3) 3 SECTIONS
Axis(4) 4 CHAPTERS

10.  Fully qualified name for each member in Cube
 Multiple ways to give member reference:
 [Dimension].[Attribute Hierarchy].[Attribute].[Member]
 Without user hierarchy (Attribute Hierarchy is Attribute itself)
 E.g.
◦ [Time].[Year].[Year].[2001]
◦ [Time].[Year].[Year].&[2001]
◦ [Time].[Year].[Year].&[1]
 With user hierarchy
 E.g.
◦ [Time].[Fiscal].[Year].[2001]
◦ [Time].[Calendar].[Year].&[2001]
◦ [Time].[Fiscal].[Year].&[1]
 We need not Attribute name sometimes
 E.g.
◦ [Time].[Year].[2001]
◦ [Time].[Calendar].[Year].[2001]

11.  Ordered list of members from each dimensions of cube
 Represent a point in the Cube space
 A cell can be representation of a tuple
 For e.g.
◦ In 3-D space (x1, y1, z1) is a tuple
◦ In a cube with 3 dimensions (2 dimensions and 1 for measures)
([Time].[Year].[Year].[2001], [Product].[Category].[Category].[Bikes], [Measures].[Sales Amount]) is a tuple
• In 3-D space, a tuple represent list of one member from
each axis. So an ordered members list says (x1, y1, z1) .
<In Red>
• In Cube a tuple is ordered list of member from each
dimension (more specifically each attribute of cube). In
this example we believe there are 2 Dimension only and 1
member from Measures Dimension is necessary. <In Blue>

12.  Part of the tuple with less member reference, where rest of
the member reference are taken care with Analysis Services to
understand
 That is, no need to list for all the members from each
dimension
 Default member from dimension is used in place of Omitted
members
 For e.g.
◦ In 3-D space, if we want to omit an axis tuple will be (0, y1, z1) i.e. with
zero
◦ In Cube space, if we omit Time dimension tuple will be
([Product].[Category].[Category].[Bikes], [Measures].[Sales Amount])

13.  Ordered collection of tuples with the same
dimensionality, or hierarchality
 E.g.
 Sets with tuple having single member:
 {[Time].[Year].[2001], [Time].[Year].[2007], [Time].[Year].[2009]}
 Sets with tuple having multiple members:
 { (Time.[Year].[Year].[2001], [Product].[Category].[Category].[Bikes]),
(Time.[Year].[Year].[2002], [Product].[Category].[Category].[Clothing]) }
 Sets with hierarchy involved:
 { (Time.[Fiscal].[Year].[2001], [Product].[Category].[Category].[Bikes]),
(Time.[Fiscal].[Year].[2002], [Product].[Category].[Category].[Clothing]) }

14.  MDX provide way to create and query calculated members in
result set
 Use WITH MEMBER clause before SELECT statement
 Create a member in any dimensional attribute and Measures
dimension as well.
 E.g. Dimensional Member:
WITH MEMBER [Product].[Category].[Popular] AS
[Product].[Category].[Category].[Bikes]+[Product].[Category].[Category].[Clothing
]
 E.g. Measures member (new calculated measure):
WITH
MEMBER [Total Sales] AS
([Measures].[Reseller Sales Amount]+ [Measures].[Internet Sales Amount])

15.  Same as Named Sets in Cube, we can create Calculated Sets in
MDX while querying
 Sets are always collection of Tuples, so is a calculated set
 Use WITH SET clause before SELECT statement
 E.g. Calculated set for two members of Product Category:
WITH SET [Best Products] AS
{[Product].[Category].[Category].[Bikes],[Product].[Category].[Cat
egory].[Clothing]}

16.  About 12-13 categories and more than 50
Functions
 Functions eases the calculations and provide
desired results
 Need to understand function with examples and
their uses
 Broad categories are :
◦ Set Functions
◦ Navigation Functions
◦ Metadata Functions
◦ Time Functions
◦ String Functions
◦ UI Functions

17.  Different reporting requirements needs different MDX
query manipulation
 For example:
◦ We list all or selected members of one attribute to fill filter values of report
◦ We CROSSJOIN different attributes to get multiple columns or fields
required in report
◦ We use NON EMPTY to filter unnecessary rows from results
◦ We use STRTOSET, STRTOMEMBER to manipulate string as cube members
◦ We create calculated members and sets when desired fields are not
available in cube
◦ We use SUBCUBE functions and queries in MDX to avoid unwanted totals
There are many different scenarios coming across reporting needs.
But I am sure little hands on experience with MDX, can help you
find solution for all. That’s the beauty of MDX, its flexible and vast.

18.  Please add all your queries and doubt here or
my blog:
 http://bistuffwithdigven.wordpress.com/
 For further details on functions and MDX please
comment on the blog posts.