Overview
In our
previous article, Mastering
OLAP Reporting: Percent of Total - Two Perspectives, we examined two approaches to meeting a common
business requirement, the generation of percent of total values, within the integrated Microsoft
Business Intelligence solution - or, more specifically, a means for doing so at
two different levels within the layers of the solution. We explored an
approach to generating percent of total values within the Analysis
Services layer, before looking at meeting the same challenge at the Reporting
Services layer.
While
we examined a relatively simple set of business requirements, we noted at
several junctures that we do, indeed, have options for the placement of
structures supporting such capabilities among the multiple layers of the
architecture. We discussed the fact that these options, and the intelligent
selection among them for such placement, can become extremely important in
enterprise-level design and implementation. Our secondary objective within the
article, then, was to emphasize that determining the placement of components
among the layers requires far more than mere expertise in Reporting Services,
or in any other single layer of the integrated solution, alone. To summarize
our assertions once again, multi-level expertise is required to optimize a
multi-level solution.
In
this article, we will extend our percent of total solution to its
presentation within a chart, combining the concepts involved with a few
mechanical procedures about which I receive recurring questions via e-mails and
forum insertions. We will use a pie chart, as it offers more "surface
area" with regard to optional displays, but the same concepts apply in
most cases to other chart types. We will begin at the point of dataset
construction in the chart, and so I would recommend first creating the
supporting Analysis Services components for the exercise based upon our
previous article, Mastering
OLAP Reporting: Percent of Total -
Two Perspectives.
In
this article, we will:
-
Discuss a
common business need within the reporting environment, the requirement to
present percent of total values within a chart data region;
-
Discuss briefly
two options for supporting the calculation that we need, focusing upon the Analysis
Services layer as the home of one solution, and Reporting Services
as the layer containing the second, and referring to the construction of these
in our previous article;
-
Prepare for
our practice session by returning to the project that we created in the
previous article of this series, and by creating a "clone" report within
Reporting Services, within which we will perform our exercises;
-
Leverage the dataSet
from our previous article to "jumpstart" our practice session;
-
Work with a Pie
Chart data region to demonstrate user-friendly presentation options for percent
of total values.
-
Preview the
report in Report Designer, to verify the operation of the calculations
that form the scope of our practice exercise.
NOTE: The cube, reporting project and other components we
created in Mastering OLAP Reporting: Percent of
Total - Two Perspectives will be required to complete the
exercises we undertake in this article. Please ensure that the components we
created in our last session are intact before beginning the practice exercises
in this article. If necessary, create / recreate them per the steps of our last
session as preparation for a successful experience within the procedures of
this article.
Percent of Total - Chart Presentation Nuances
Introduction and Business Scenario
As I related in Percent of Total - Two Perspectives, a request for assistance that I often
receive, via e-mail, forums, and elsewhere, involves the need to calculate a percent
of a total, primarily to determine members' contribution to greater
wholes. Another common request deals with ways to show the percent of total
in combination with the values themselves in a chart data region. The idea is
to convey both the values, and the percents of totals they represent,
together in a unified, user-friendly view.
We will illustrate
this need within our usual context of a business scenario. We will assume that we have received a request,
once again, from a group of information consumers in the Budget and Planning
unit of the FoodMart 2000 organization. The request is for additional support
in the presentation of some data, housed within the Sales sample cube,
regarding USA Store Sales for 1997. The consumers wish to see,
as an extension to the information we provided before in a matrix data
region, the Sales values that are already available for each Store,
but within a separate pie chart. They add that, ideally, the
individual "pieces of the pie" will display the respective percentage
total sales value (that is, percentage contribution of each Store
to the total USA Store Sales), as well as showing total Sales
by Store, together with the corresponding percentage contribution
of each Store in a legend, which is color-keyed to the chart. Additionally,
the legend entries will sort by percentage sales in descending order. The
consumers feel that this presentation will afford compactness, while enhancing
the understanding of the report's intended audience.
As in the previous
article, the ultimate report will require no drilldown features, and will
concern itself with 1997 data only. Its use will be strictly limited to
a high-level analysis of store performance from a Store Sales
perspective.
As we
listen to the requirement, we realize that this is a common request. The
requirement is also easily met with Reporting Services, whose general
flexibility is reflected, as well, in the pie chart data region. We will first
examine the satisfaction of the request of the information consumers through reference
to the calculated member that we created in our last session, and then achieve the
same results using an approach from within Reporting Services. The differences
in the approaches are somewhat subtle, and consist predominantly of the source
of our percent of total calculation. Of additional interest is the
process of managing a function within the string we use to define our
pie chart labels, as we shall see.
In
addition to demonstrating these approaches to labeling the pie chart, we will
also offer an approach whereby we can achieve the same effects via the chart's legend,
as a means of presenting the data in a manner that might be clearer in
scenarios where the pie sections are perhaps too small to contain the
text that we wish to display. While the primary objective of our practice exercises will
be to illustrate approaches to a commonly expressed need, a secondary objective
is, as it was in our previous article, to illustrate the fact that we can
provide solutions based upon components that reside at different layers of the integrated
BI solution to meet the business requirements of our clients and employers.
Considerations and Comments
In our previous
article, we created a copy of the sample Sales cube, from which we
performed our practice exercises, to allow us to make changes to our cube while
retaining the original sample in a pristine state. We also created a copy of
the Foodmart Sales sample report, for the same reasons. In this
session, we will leverage the cube, together with the dataset for the
report from our last lesson, to save time in getting to the core concepts of
our article. This means that we will need to access the cube and Reporting
Services project that we assembled in our last session. If you are
joining the series at this article, and have not completed its predecessor, I urge
you to do so, both to make preparation for this article a breeze, and to gain
an understanding of the important "layering" concepts that we treated
in Percent of Total - Two Perspectives.