About the Series ...
This
article is a member of the series Introduction
to MSSQL Server Analysis Services. The
series is designed to provide hands-on application of the fundamentals of MS
SQL Server Analysis Services, with each installment progressively
presenting features and techniques designed to meet specific real - world needs.
For more information on the series, please see my initial article, Creating Our First
Cube.
Note: To follow along with the steps we undertake, the following components,
samples and tools are recommended, and should be installed according to the
respective documentation that accompanies MSSQL Server 2005:
Microsoft SQL
Server 2005 Database Engine
Microsoft SQL
Server 2005 Analysis Services
Microsoft SQL
Server 2005 Integration Services
Business
Intelligence Development Studio
Microsoft SQL
Server 2005 sample databases
The Analysis Services
Tutorial sample project and other samples that are available with the installation
of the above.
To
successfully replicate the steps of the article, you may also need to have:
Membership
within one of the following:
Read permissions within any SQL
Server 2005 sample databases we access within our practice session, as
appropriate.
Note: Current Service Pack updates are assumed for the operating system, MSSQL
Server 2005 ("MSSQL Server"), MSSQL Server 2005 Analysis
Services ("Analysis Services"), MSSQL Server 2005 Reporting
Services ("Reporting Services") and the related Books
Online and Samples, as appropriate. Images are from a Windows
2003 Server environment, but the steps performed in the articles, together
with the views that result, will be quite similar within any environment that
supports MSSQL Server 2005 and its component applications.
About the Mastering Enterprise BI Articles ...
Having implemented, and developed within, most of the major
enterprise BI applications for over for fourteen years, and having
developed an appreciation for the marriage of ease of use and analytical
power through my background in Accounting and Finance, I have come to
appreciate the leadership roles Cognos and other vendors have played in the
evolution of OLAP and enterprise reporting. As I have stated repeatedly,
however, I have become convinced that the components of the Microsoft
integrated BI solution (including MSSQL Server, Analysis Services,
and Reporting Services) will commoditize business intelligence. It is
therefore easy to see why a natural area of specialization for me has become
the conversion of Cognos (and other) enterprise BI to the Microsoft solution. In addition to converting formerly
dominant enterprise Business Intelligence systems, such as Cognos, Business
Objects / Crystal, MicroStrategy, and others, to the Reporting Services
architecture, I regularly conduct strategy sessions about these conversions
with large organizations in a diverse range of industries – the interest grows
daily as awareness of the solution becomes pervasive. Indeed, the
five-to-six-plus figures that many can shave from their annual IT budgets
represent a compelling sweetener to examining this incredible toolset.
The purpose of the Mastering
Enterprise BI subset of my Introduction to MSSQL Server Analysis Services series is
to focus on techniques for implementing features in Analysis Services
that parallel those found in the more "mature" enterprise OLAP
packages. In many
cases, which I try to outline in my articles at appropriate junctures, the
functionality of the OLAP solutions within well-established, but expensive
packages, such as Cognos PowerPlay Transformer and Cognos PowerPlay (as
well as their Cognos 8 incarnations), can be met – often exceeded – in
most respects by the Analysis Services / Reporting Services combination
– at a tiny fraction of the cost. The vacuum of documentation comparing
components of the Microsoft BI solution to their counterparts among the
dominant enterprise BI vendors, to date, represents a serious "undersell"
of both Analysis Services and Reporting Services, particularly
from an OLAP reporting perspective. I hope to contribute to making this arena
more accessible to everyone, and to share my implementation and conversion
experiences as the series evolves – and, within the context of the Mastering
Enterprise BI articles, to demonstrate that the ease of replicating popular
enterprise BI features in Analysis Services will be yet another reason
that the Microsoft solution will commoditize Business Intelligence.
For
more information about the Mastering Enterprise BI articles, see
the section entitled "About the
Mastering
Enterprise BI Articles" in my article Relative
Time Periods in an Analysis Services Cube, Part I.
Introduction
In
this, the second half of a two-part article, we continue the examination of Named
Calculations we began in Mastering
Enterprise BI: Extend the Data Source with Named Calculations, Pt. I. In Part I, by way of introduction, we recalled ways of "extending" the
data source tables underlying our Analysis Services 2000 cubes which we
had examined in past articles of this series, as an introduction to this
article, where we explore yet another new feature where Analysis Services
2005 offers us more flexibility in this area. We noted that we were
limited, in the previous version of Analysis Services, to using SQL
expressions within the Member Key and Member Name columns (in the
case of dimension structures), and in the Source column (in the
case of measures) to achieving similar extensions. We referred to my
article Mastering Enterprise BI: Create Aging "Buckets"
in a Cube, where I proposed the use of an IIF
/ CASE scenario to build the necessary dimensional structure into a sample
cube to support aging buckets, as an example of such an extension, and we got a
glimpse of how, although the approach might work to help us deliver desired
results in our business environments, the use of SQL expressions within these
rather limited selectors might become cumbersome in many situations.
At this point in Part
I, we noted that, among many overall improvements, and added conveniences
in the design arena, Analysis Services 2005 offers us far more
flexibility in this area, as well. We stated that the advent of the Data
Source View represents a significant design and development enhancement
within Analysis Services, pointing to my article Introduction
to MSSQL Server Analysis Services: Introducing Data Source Views,
where we first introduced this new abstract layer within the design
environment. We noted, in review, that the Data Source View contains the logical model of the schema
used by database objects, including cubes, dimensions, and so forth, and that
it forms a central, unified view of the metadata within our Analysis
Services Project.
We recalled that, in
addition to being capable of representing one or more Data Sources (allowing
us to integrate data from multiple data stores within a single cube, or even
dimension), another of the many advantages offered by the Data Source View
layer is its capacity to contain logical objects, such as queries,
relationships, and calculated columns, that do not exist within (and, indeed,
are entirely separate from) the underlying data sources. This factor, as we
discovered, lies at the heart of our current focus upon Named Calculations,
which become quite useful to us when we cannot create, for whatever reason,
these "extending" objects within the data sources upon which we are
constructing our Analysis Services Projects
In
the first half of this article, we laid out our objective to examine Named
Calculations, and to get hands-on exposure to the process of adding them to
a basic cube we construct within the Business Intelligence Development
Studio. We overviewed the creation of Named Calculations, and
discussed ways in which they can offer flexibility in general cube design and
development. We then prepared Analysis Services, and our environment, by
creating an Analysis Services Project (which we called ANSYS045 Named
Calculations), to house our development steps, and to serve as a platform for the design
of a quick cube model, within which to perform subsequent procedures in our
session. Next, we created a Data Source containing the information Analysis
Services needs to connect to a database, and then we created a Data
Source View containing schema information. Finally, as the last step of Part I, we added examples of Named Calculations
within the Data Source View.
As a part of our continuing examination of Named
Calculations in this article, we will:
-
Create a Cube
containing data from our sample relational tables;
-
Create a Dimension
based upon two of our Named Calculations to support "aging buckets;"
-
Deploy our Analysis
Services Solution;
-
Browse the Cube,
focusing on the new aging dimension structures.
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