Contents
Overview 1
Introducing Dimension and Cube Processing 2
Processing Dimensions 5
Processing Cubes 15
Lab A: Processing Dimensions and Cubes 27
Lab B: Updating Dimension Data 30
Lab C: Incrementally Updating Cubes 36
Optimizing Cube Processing 41
Troubleshooting Cube Processing 49
Review 54

Module 9: Processing
Dimensions and Cubes

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Module 9: Processing Dimensions and Cubes iii

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Instructor Notes
Multidimensional online analytical processing (OLAP) databases include
schema and data, both of which change and need updating from the relational
database management system (RDBMS) on a regular basis. In this module,

students learn to manage dimension and cube processing with Microsoft
®
SQL
Server
™
2000 Analysis Services.
After completing this module, students will be able to:
!
Understand the difference between OLAP schema and data.
!
Process dimensions.
!
Perform the three types of cube processes.
!
Optimize cube processing.
!
Troubleshoot cube processing.

Materials and Preparation
This section lists the required materials and preparation tasks that you need to
teach this module.
Required Materials
!
To teach this module, you need Microsoft PowerPoint
®
file

2074A_09.ppt

Preparation Tasks

To prepare for this module, you should:
!
Read all the student materials.
!
Read the instructor notes and margin notes.
!
Complete all the demonstrations.
!
Practice the lecture presentation and demonstration.
!
Complete the lab.
!
Review the Trainer Preparation presentation for this module on the Trainer
Materials compact disc.
!
Review any relevant white papers that are located on the Trainer Materials
compact disc.

Presentation:
75 Minutes

Lab:
75 Minutes
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Demonstration: Rebuilding the State Dimension
The following demonstration procedures provide information that will not fit in
the margin notes or is not appropriate for student notes.
In this demonstration, you will rebuild the State dimension and will show
students the impacts to the Sales Units cube after the rebuild.
!
To restore a new database and define a data source
1. In Analysis Manager, right-click the server, click Restore Database, click
the Look in list, click the file C:\Moc\2074A\Labfiles\L09\Module
09.CAB, click Open, click Restore, and then click Close.
2. Double-click Module 09 to expand the database.
3. Below Module 09, double-click the Data Sources folder, right-click the
Module 09 data source, and then click Edit.
4. Click the Connection tab of the Data Link Properties dialog box, and then
verify that localhost is selected in step 1.
5. In step 2, verify that Use Windows NT Integrated security is selected.
6. In step 3, verify that Module 09 is selected.
7. Click Test Connection and verify that the test succeeded. Click OK twice.

!
To browse the Sales Units cube
1. In the Module 09 database, browse the Sales Units cube.
2. Show students that the cube contains two dimensions—State and Time—
and one measure—Sales Units.
3. Point out that the cube is processed and able to accept queries.

!
To rebuild the State dimension
1. In the Module 09 database Shared Dimensions folder, right-click the State
dimension, and then click Process.

The Process a Dimension dialog box opens.
Here you see two options for processing a dimension—incrementally
updating the dimension and rebuilding the dimension.
2. Click Rebuild the dimension structure, and then click OK.
The Process dialog box opens and steps through the dimension rebuild.
3. After the dimension finishes processing, double-click the line in the Process
dialog box that begins with a yellow SQL icon.
Here you see the SQL that executes to rebuild the State dimension:
SELECT DISTINCT "dbo"."State"."Country",
"dbo"."State"."Region", "dbo"."State"."STATE_ID",
"dbo"."State"."State_Name" FROM "dbo"."State"

4. Close the View Trace Line window, and then click Close.

Demonstration:
10 Minutes
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!
To attempt to browse the Sales Units cube
1. In the Module 09 database, right-click the Sales Units cube, and then click
Browse Data.
2. Notice that you receive the following error:
“Unable to browse the cube ‘Sales Units’. Cube not processed. To browse
sample data for this cube, open Cube Editor, and then on the View menu,
click Data.”
You did not change the State source data, and therefore the dimension did
not require a rebuild. However, if the dimension is rebuilt, the Sales Units

cube is unavailable.
After you rebuild a shared dimension, all cubes containing the shared
dimension are unavailable for user access.
3. Click Close.


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Other Activities
Difficult Questions
Below are difficult questions that students may ask you during the delivery of
this module and answers to the questions. These materials delve into subjects
that are within the scope of the module but are not specifically addressed in the
content of the student notes.
1. How are incremental updates useful if the Analysis Server is unaware of
data warehouse loads and it therefore does not know what data to load from
a table?
You can create a column in the fact table that has an identifying record,
such as a time stamp or a batch number. You can include the unique
record in the WHERE clause of the associated partition definition and
filter records based on that identifier.
2. Are multiple partitions of a cube processed sequentially, even if they reside
on different computers?
Yes, unless you specify that you want certain partitions to be built in
parallel. You can do this by using Decision Support Objects (DSO).

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Module Strategy
Use the following strategy to present this module:
!
Introducing Dimension and Cube Processing
Define the term processing and explain that Analysis Server creates SQL
statements to extract information from the data source. Next, define the
terms schema and data as they are used in Analysis Services.
!
Processing Dimensions
Explain to students that dimensions must be processed when they are first
designed and whenever there are changes or updates in the source
dimension tables. Describe the interface and the steps to follow to process a
shared dimension. Explain that there are two ways to process a shared
dimension—a rebuild or an incremental update. Describe when to use each
type of processing and the implications of doing so. Explain that private
dimensions are created and manipulated in single cubes, and that to process
a private dimension, the entire cube must be processed. Finally, define
relational OLAP (ROLAP) dimensions and changing dimensions and
explain when to use them.
!
Processing Cubes
Begin with an explanation of when to process a cube and how to get to the
Process a Cube dialog box. Describe the three options available in the
dialog box—full process, refresh, and incremental update. Describe when to
use each option and the implications of doing so. Introduce the Incremental
Update Wizard and the steps involved in performing an incremental
update—specifying the data source and specifying the filter expression.
Explain what happens behind the scenes when using a filter. Discuss

available properties that affect cube and dimension processing.
!
Optimizing Cube Processing
Explain to students that, while query performance is obviously a high
priority when using OLAP cubes, processing time is also important.
Describe several ways to improve cube processing performance—
optimizing the data source, optimizing the cube schema, optimizing cube
design, and optimizing Analysis Server. Explain how to perform each of
these types of optimization.
!
Troubleshooting Cube Processing
Describe the three most common cube problems related to processing—
missing data, processing errors, and insufficient memory and disk space.
Give tips and techniques for solving each type of problem.


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Overview
!
Introducing Dimension and Cube Processing
!
Processing Dimensions
!
Processing Cubes
!
Optimizing Cube Processing
!

Troubleshooting Cube Processing


Multidimensional online analytical processing (OLAP) databases include
schema and data, both of which change and need updating from the relational
database management system (RDBMS) on a regular basis. In this module, you
will learn to manage Analysis Server dimension and cube processing with
Microsoft
®
SQL Server
™
2000 Analysis Services.
After completing this module, you will be able to:
!
Understand the difference between OLAP schema and data.
!
Process dimensions.
!
Perform the three types of cube processes.
!
Optimize cube processing.
!
Troubleshoot cube processing.

Topic Objective
To provide an overview of
the module topics and
objectives.
Lead-in
In this module, you will learn

about dimension and cube
processing and the various
ways to perform processes.
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#
##
#

Introducing Dimension and Cube Processing
!
Definition of Processing
!
Overview of Schema and Data


In this section, you are introduced to dimension and cube processing, and will
learn the difference between OLAP schema and OLAP data.
Topic Objective
To introduce the concept of
cube and dimension
processing.
Lead-in
In this section, you are
introduced to dimension and
cube processing, and will
learn the difference between

OLAP schema and OLAP
data.
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Definition of Processing
!
Processing Must Occur Prior to Users Querying the
Cube
!
Dimension Processing Loads Dimension Data
!
Cube Processing Loads Cube Data and Creates
Aggregations
!
Processing Uses SQL Queries to Populate Dimension
and Cube Data


Before users can access data from an OLAP cube, some form of processing
must occur in the cube. In Analysis Services, the term processing means
loading dimensions and cube data from the RDBMS data source.
When you process dimensions and cubes, Analysis Server creates SQL
statements to extract the necessary information from the data warehouse
dimension and fact tables. In addition, Analysis Server creates any aggregations
in the cube that were designed previously.

Topic Objective
To define the term

processing, as used in
Analysis Services.
Lead-in
Before users can access
data from a cube, some
form of processing must
occur in the cube.
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Overview of Schema and Data
!
OLAP Schema
$
Consists of dimensional hierarchies and members
$
Comes from dimension tables
$
Is commonly referred to as OLAP metadata
!
OLAP Data
$
Consists of numeric information
$
Comes from fact table


To master various dimension and data load processes, it is important to
understand the difference between schema and data. Definitions of the two

terms as used in Analysis Services may differ from what you are accustomed to
when using other databases and technologies.
OLAP Schema
Unlike relational databases, where member names are considered data, member
names in Analysis Services are considered part of the schema.
The following is true of OLAP schema:
!
The schema consists of the dimensional hierarchies and the members that
populate these hierarchies.
!
OLAP schema comes from the dimension tables in the source RDBMS.
!
Member names, for example Quarter 1, Canada, and Bread, are
commonly referred to as OLAP metadata in multidimensional databases.
OLAP Data
The data in Analysis Services is the numeric information, such as units sold,
prices, inventory levels, or dollar revenues.
The following is true of OLAP data:
!
This numeric information, or data, is commonly referred to as the measures.
!
OLAP data comes from the fact table in the source RDBMS.
Understanding the distinction between schema and data is important for
database administrators and OLAP architects.
Topic Objective
To describe the differences
between OLAP schema and
OLAP data.
Lead-in
It is important to understand

the difference between the
terms schema and data as
they are used in Analysis
Services.
Module 9: Processing Dimensions and Cubes 5

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#
##
#

Processing Dimensions
!
Dimension Processing Overview
!
Rebuilding Dimensions
!
Incrementally Updating a Dimension
!
Processing Private Dimensions
!
Understanding ROLAP and Changing Dimensions


A cube consists of one or more dimensions combined with one or more
measures. The dimensions form the structure or organization for the data values
in the cube. Before the Analysis Server can process a cube, it must have already
processed each dimension that is used in the cube.
In this section, you will learn about dimension processing and the various ways

to process dimensions.



Topic Objective
To introduce dimension
processing.
Lead-in
In this section, you will learn
about dimension processing
and the various ways of
processing dimensions.
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Dimension Processing Overview
!
Purpose of Dimension Processing
$
Creates a new dimension
$
Maintains an existing dimension
!
Shared Dimension Processing Mechanics
$
Right-click a single dimension
$
Right-click the Shared Dimensions folder

!
The Process Dialog Box
$
Opens at time of dimension process
$
Contains dimension processing information


Before data can be loaded into a cube, you must first create and process the
dimensions of the cube. Once you process the dimensions, the Analysis Server
can load data from the fact table into the cube and can create aggregations.
Purpose of Dimension Processing
You process a dimension when you first create it, when you modify its
structure, and when data updates occur in the source data dimension tables.
After the initial dimension process, you must maintain dimensions on an
ongoing basis to reflect changes in the underlying dimension tables—for
example, new products are added to the product line, sales representatives
change sales regions, and so on. Dimensions must reflect the changes in the
business structure.
Two methods are available to the Analysis Server developer for processing
shared dimensions:
!
Rebuild the dimension structure completely rebuilds and constructs a
dimensional structure.
!
Incremental update imports new members into an existing dimensional
structure.
Analysis Server creates multidimensional OLAP (MOLAP) dimension
structures in the Data folder located on the server, except in those cases when
you use ROLAP dimensions. Non-ROLAP dimensional structures are created

on the server for cubes that use the MOLAP, hybrid OLAP (HOLAP), and
relational OLAP (ROLAP) storage modes.
Topic Objective
To explain the purpose and
mechanics of dimension
processing.
Lead-in
Before data can be loaded
into a cube, you must first
create and process the
dimensions of the cube.
Key Point
Analysis Server creates
multidimensional OLAP
(MOLAP) dimension
structures in the Data folder
located on the server,
except in those cases when
you use ROLAP
dimensions. Non-ROLAP
dimensional structures are
created on the server for
cubes that use the MOLAP,
hybrid OLAP (HOLAP), and
relational OLAP (ROLAP)
storage modes.
Do not spend too much time
here describing dimension
rebuilds and incremental
updates because they are

discussed in detail later in
this section.
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Shared Dimension Processing Mechanics
You can initiate the processing of a shared dimension in either of two ways:
!
Expand the Shared Dimensions folder, right-click the dimension, and then
click Process to display the Process a Dimension dialog box. This interface
lets you choose between an incremental update and a dimension structure
rebuild.
!
Right-click the Shared Dimensions folder and click Process All
Dimensions. There is no choice about which type of process will occur
when you choose this option. The Analysis Server determines the type of
process applied to dimensions by determining which dimensions contain
structure changes and which dimensions maintain their original structure.
The Process Dialog Box
When you process a dimension in Analysis Manager, a Process dialog box
opens that steps through each of the processing phases. The dialog contains the
following information that you can use to troubleshoot errors or determine the
success or failure of the process:
!
Start time, end time, and process duration.
!
Number of RDBMS rows processed.
!
Initialization and committal information.

!
SQL statements performed on the RDBMS to access member and
dimension data.
!
Information on the success or failure of the dimension build.


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Rebuilding Dimensions
!
Situations in which to Rebuild a Dimension
$
A level is added or deleted
$
A member is deleted
$
A member is renamed
$
A child is moved from one parent to another
!
Implications of Rebuilding a Dimension
$
Dimensional structure is rebuilt
$
Cubes become unavailable to clients until the cubes are
reprocessed

$
Rebuilding takes time


The Rebuild the dimension structure option in the Process a Dimension
dialog box entirely recreates the dimension structure. It is the most
comprehensive method for processing dimensions.
Situations in which to Rebuild a Dimension
The following situations require a rebuild of the dimension structure to reflect
the structural dimension changes:
!
Adding or deleting a level.
!
Deleting a member.
!
Renaming a member.
!
Moving a child from one parent to another. This movement is commonly
called re-parenting. For example, if you move a product from one business
unit to another, the dimensional structure must reflect the change.
Implications of Rebuilding a Dimension
Rebuilding a dimension is not a minor action. The following are implications of
rebuilding a shared dimension:
!
The Analysis Server erases and rebuilds the dimensional structure that is
stored on the Analysis Server.
!
Cubes that depend on the given dimension are unavailable to clients until
the cubes are reprocessed. In other words, clients cannot connect to cubes
that depend on a rebuilt dimension until the cubes are reprocessed.

!
The rebuilding of the dimensional structure can be a time-consuming
process if the dimension contains an abundance of members.
Topic Objective
To describe the process of
rebuilding a dimension.
Lead-in
The Rebuild the
dimension structure option
entirely recreates the
dimension structure. It is the
most comprehensive
method for processing
dimensions.
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Incrementally Updating a Dimension
!
Situations in which to Incrementally Update a Dimension
$
Members are added
$
Member properties are added
!
Implications of Incrementally Updating a Dimension
$
Cubes remain available

$
New members appear
$
Existing members remain intact
$
New associated fact table data requires a cube update


The other option of the Process a Dimension dialog box is Incremental
update. This option allows you to add members and member properties to a
shared dimension when no structural changes have occurred.
Incremental updates do not force a reprocessing of the cube. Therefore, perform
incremental updates of dimensions instead of dimension rebuilds when
possible.
Situations in which to Incrementally Update a Dimension
You can perform incremental updates in the following situations:
!
Adding a member to a dimension.
!
Adding a member property to a dimension.
Implications of Incrementally Updating a Dimension
Though the implications are not as severe as dimension rebuilds, it is still
important to understand what happens when an incremental update occurs:
!
Cubes that use the given dimension are available to clients during this
process.
!
The dimension hierarchy reflects the member updates when the incremental
update is complete.
!

Existing members are left intact.
!
New fact table data associated with the new members requires an
incremental cube update.

When you process a cube, you have the option to incrementally update
Topic Objective
To describe dimension
incremental updates.
Lead-in
Incremental updates allow
you to add members and
member properties to a
shared dimension when no
structural changes have
occurred.
Note
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all shared dimensions found in the cube. You do this by selecting the
Incrementally update the shared dimensions used in this cube check box
found in the Process a Cube dialog box.

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Processing Private Dimensions

!
Exist in Single Cubes
!
Cannot Be Processed Independently
!
Are Processed When The Cube Is Processed
$
Incremental update of cube
$
Refresh of cube
$
Full process of cube


You create and manipulate private dimensions in single cubes. Because they
exist in single cubes, you do not affect other cubes by processing private
dimensions. Therefore, you can isolate cube-processing needs by defining
dimensions as private.
You cannot process private dimensions without also processing the cubes in
which they reside, and no options or commands exist that process private
dimensions independently.
There are two methods of processing private dimensions:
!
Perform an incremental update or a refresh of a cube. An incremental
update or a refresh of a cube performs an incremental update of all private
dimensions in the cube. In other words, an incremental update or a refresh
of a cube adds new members and member properties in private dimensions
in the cube.
!
Perform a full process of a cube. A full process of a cube performs a rebuild

of all private dimensions in the cube. In other words, a full process of a cube
updates the structure and all members in private dimensions in the cube.



For more information on cube refreshes and full processes, refer to the
next section in this module, Processing Cubes.


Topic Objective
To discuss the processing of
private dimensions.
Lead-in
In this section, you will learn
about private dimension
processing.
Note
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Understanding ROLAP and Changing Dimensions
!
ROLAP Dimensions
$
Store dimension data in dimension tables
$
Can support tens of millions of members
$
Force you to define their cubes as ROLAP cubes

$
Require SQL Server 2000 Enterprise Edition
$
Are also considered changing dimensions
!
Changing Dimensions
$
Are optimized for frequent data source changes
$
Permit more types of changes with incremental updates
$
Include virtual, parent-child, and ROLAP dimensions
$
Are set within the Dimension Editor


When you create a dimension, its structure is stored, by default, in
multidimensional structures on the Analysis Server computer. You maintain its
dimensional structure based on the processing rules presented in the preceding
pages of this section. These dimensions are considered MOLAP dimensions.
Alternatively, you can define dimensions as ROLAP dimensions to allow for
millions of members in your dimension, or you can create changing dimensions
to allow for more frequent changes to the dimension structure.
ROLAP Dimensions
A ROLAP dimension’s data is stored in the dimension table or tables.
Therefore, there is no need to build the multidimensional dimension structures
that MOLAP dimensions create on the Analysis Server.
By defining a dimension as ROLAP, you can maintain a dimension with tens of
millions of members. If you attempt to store tens of millions of members in a
MOLAP dimension, you receive errors when you process the dimension.

Because of the query performance degradation you receive when using ROLAP
dimensions, you usually define a dimension as ROLAP only if the dimension
contains millions of members.
When you add a ROLAP dimension to a cube, the cube must use the ROLAP
option for its cube storage mode. You are not given the option to define the
cube as MOLAP or HOLAP in the Storage Design Wizard.
ROLAP dimensions require SQL Server 2000 Enterprise Edition.
All dimensions that use the ROLAP storage mode are also considered to be
changing dimensions.
Topic Objective
To discuss ROLAP and
changing dimensions.
Lead-in
You can define dimensions
as being ROLAP or
changing.
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Changing Dimensions
A changing dimension is optimized for frequent changes. It allows certain types
of changes to be made by using incremental updates instead of rebuilding the
dimension and fully processing the cube. Therefore, users can access the cubes
without interruption when making these changes.
The following types of dimensions are always changing dimensions:
!
Virtual dimensions
!
Parent-child dimensions

!
ROLAP dimensions
You can define any dimension as changing by setting its Changing property to
True in the Properties pane of the Dimension Editor or Cube Editor.
In a changing dimension, because aggregations are not stored at intermediate
dimension levels, levels and members below the top level and above the bottom
level of the dimension can be added, moved, changed, or deleted, and an
incremental update applies the changes when you save the dimension. You do
not need to rebuild the dimension, a process that makes the cube unavailable to
clients during the rebuild process.
Changing dimensions provide for more flexibility in updating dimension
structures. However, queries that use changing dimensions are slower than
queries that use non-changing dimensions.

For more information on ROLAP and changing dimensions, see SQL
Server Books Online.



Note
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Demonstration: Rebuilding the State Dimension


In this demonstration, you will learn how to rebuild the State dimension and
will see the impacts to the Sales Units cube after the rebuild.
Topic Objective

To demonstrate how to
rebuild a dimension.
Lead-in
In this demonstration, you
will learn how to rebuild the
State dimension and will
see the impacts to the Sales
Units cube after the rebuild.
Delivery Tips
The steps for this
demonstration are included
in the Instructor Notes.
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#
##
#

Processing Cubes
!
Cube Processing Overview
!
The Full Process
!
Refreshing a Cube
!
Incrementally Updating a Cube

!
The Incremental Update Wizard
!
Processing Options


After you design a cube, you must process the cube to populate it with data.
MOLAP cubes, ROLAP cubes, and HOLAP cubes all require processing. There
are three different processes for cubes, the mechanics and logic of which are
described in the next section.

Topic Objective
To introduce cube
processing.
Lead-in
After you design a cube, you
must process the cube to
populate it with data.
The topics in this section are
very complex. If students
are confused, tell them that
the following labs contain
exercises that include each
of the processing types.
16 Module 9: Processing Dimensions and Cubes

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Cube Processing Overview
!

Cube Processing Mechanics
!
Using the Process Dialog Box


An OLAP cube is a fast and flexible representation of the information stored in
a data warehouse. When the information in the data warehouse changes, you
must update the cube so that the data in the cube is accurate. Updating an
OLAP cube to accurately represent the relational data warehouse is called
processing the cube. Different types of changes can occur in the data
warehouse, and the Analysis Server provides different techniques for
synchronizing the OLAP cube with the relational data warehouse.
Cube Processing Mechanics
To initiate cube processing, right-click a cube and then click Process to display
the Process a Cube dialog box. Here, you decide if you want to perform an
incremental update, a data refresh, or a full process.
Using the Process Dialog Box
When you process a cube in Analysis Manager, the process dialog box opens
with processing information. This is the same dialog you saw earlier when
processing dimensions. However, there are more steps documented. These
include:
!
Start time, end time, and duration of entire process, as well as the times and
duration of each of the steps of the process.
!
Number of RDBMS rows processed at each step.
!
Initialization and committal information.
!
SQL statements used to access data from the RDBMS.

!
Statistics on aggregations created.
!
Information on the success or failure of the process.

Topic Objective
To introduce the mechanics
of cube processing.
Lead-in
To contain accurate data, a
cube must be processed
when the data in the data
warehouse changes.
Module 9: Processing Dimensions and Cubes 17

BETA MATERIALS FOR MICROSOFT CERTIFIED TRAINER PREPARATION PURPOSES ONLY


The Full Process
!
Situations in which to Perform a Full Process
$
The cube is new
$
A dimension is added or deleted
$
A dimension is rebuilt
$
A measure is added, deleted, or modified
!

Implications of Performing a Full Process
$
Cube data, including aggregations, is erased and rebuilt
$
Dependent virtual cubes become unavailable until reprocessed
$
Partition data is read into the cube from the data source
$
Private dimensions and changed shared dimensions are rebuilt


A full process is the most comprehensive cube process you can perform. To
initiate a process, click the third option in the Process a Cube dialog box. All
cube structures and cube data is rebuilt.
Situations to Perform a Full Process
Because a full process is the most time consuming method of processing, it is
important to understand the situations that require a full process. These include:
!
Creating a new cube.
!
Adding or deleting dimensions.
!
Rebuilding any shared dimension belonging to the cube.
!
Adding, deleting, or modifying cube measures.
Implications of Performing a Full Process
The following are important implications of performing a full process on a
cube:
!
If the cube is MOLAP, it is erased and rebuilt.

!
Regardless of cube storage—MOLAP, ROLAP, or HOLAP—aggregations
are erased and rebuilt.
!
Any virtual cubes based on the cube are unavailable after the process until
they are reprocessed themselves.
!
All partition data is read into the cube from the RDBMS data sources.
!
All private dimensions are rebuilt.
Topic Objective
To describe when to
perform a full process and
the implications of doing so.
Lead-in
A full process is the most
comprehensive cube
process you can perform.