Simple Column Chart for Analysis Services Data

This article focuses upon Column
charts
, and extends the examination of Reporting
Services
charts for Analysis Services data sources
that we began in an earlier article of my MSSQL Server
Reporting Services
series, Introducing
Reporting Services Charts for Analysis Services
. In that
article we summarized the many different chart (or chart
data region
) types that are available, and looked ahead to
individual articles surrounding each type, where we would specify details – and
real world innovations – involving the use of each in reporting Analysis
Services
data. We noted that the focus of these related articles,
interspersed among other topics within my MSSQL Server Reporting Services series over
time, would be the design and creation of Analysis
Services chart
reports of various types, and the
exploitation of the rich and flexible features contained in Reporting
Services
that enable us to make report data more meaningful,
and easier to understand, from the perspective of our information consumer
audiences.

In
many cases, which I try to outline in my articles at appropriate junctures, the
functionality of well-established, but expensive, solutions, such as Cognos (PowerPlay,
Impromptu, and other applications), Business Objects, and myriad
other reporting / OLAP applications can be met in most respects by Reporting
Services
– at a tiny fraction of the total cost of ownership. And the
flexibility and richness of the chart data regions alone in Reporting
Services
exceed, in many ways, the rather fixed options available in other
enterprise reporting solutions.

As I
have repeated in many of my articles in this column, one of the first things
that become clear to “early adopters” of Reporting Services is that the
“knowledgebase” for Analysis Services reporting with this tool is, to
say the least, sparse. The vacuum of documentation in this arena, even
taking into consideration the release of several books surrounding Reporting
Services
in recent years, continues to represent a serious “undersell” of Reporting
Services
, from an Analysis Services reporting perspective. I hope
to contribute to making this space more accessible for everyone, and to share
my implementation and conversion experiences as the series evolves. In the
meantime, we can rest assured that the Analysis Services potential in Reporting
Services
will contribute significantly to the inevitable commoditization of
business intelligence, via the integrated Microsoft BI solution.

Note: For more
information about my MSSQL Server Reporting Services column in general,
see the section entitled “About
the MSSQL Server Reporting
Services Series” that follows the
conclusion of this article.

Overview

As we observed in Introducing Reporting Services Charts
for Analysis Services
, Reporting
Services
enables us to present both summarized and detailed data in
colorful, easy-to-read charts of various
designs, from which we can chose the layout and type that best meets any given
business requirement. Among the types offered, the simple Column
chart
type is perhaps one of the most popular. In this article,
we will introduce the simple Column chart type
and get some hands-on exposure to its creation and its general characteristics.
This will serve as a basis for other, more in-depth, practical exercises in
coming articles, where we will extend the value of our chart-enhanced reports in
myriad ways. Among these ways, just for starters, are the capability to format
chart and other objects within a host of
options, to drill down to see the details behind the
graphical / numerical summaries, to combine
chart reports with other types of reports,
and to access many other options in the powerful Reporting
Services
tool set.

My objective within this article is to assist the reader in
quickly assembling a report containing a working simple Column chart
(relying upon, for instance, already assembled datasets and other
underlying support within an existing sample report), and to move efficiently
into targeted reporting nuances that meet real world needs. While this initial
introduction will focus more on the creation of a simple Column chart, the
report we create will serve as a basis, in prospective articles, to demonstrate
more detailed intricacies that I have found useful in meeting business
requirements of my own clients and readers. The ultimate objective, as is
typically the case within my various series, is to provide hands-on
opportunities to learn overall, start-to-finish procedures, before homing in on
specific options of interest (although we will certainly deal with many of
these options in even our early exercises, as a part of completing the stated
objectives of these sessions).

Introducing Column Charts for Analysis Services

In Introducing Reporting
Services Charts for Analysis Services
, we learned that the Column chart type is available in the
following variants:

  • Simple Column
  • Stacked Column
  • 100% Stacked
    Column

In
this article we will focus upon the Simple Column variant, although we
will take up the other variants within relevant contexts in sister articles of
the MSSQL Server Reporting
Services

series.

We noted in our introductory
article that Column charts are typically used to
compare values between categories. In generally describing the type, we observed that the Column chart
presents values and series groups as sets of
vertical columns that are grouped by category. Values, within
this chart type, are represented by the height of the columns (as
measured by the y-axis). Category labels are displayed on the x-axis.

In this article, we will introduce
the simple Column chart data region in detail, and
gain practical exposure to the creation of a basic example of such a chart that
is employed in reporting from an Analysis Services data source. In
introducing the basic simple Column chart, we will:

  • Perform a
    brief overview of the Column chart type, discussing its variants and
    typical uses;
  • Open the
    sample Report Server project, AdventureWorks Sample Reports, and ascertain
    connectivity
    of its shared Analysis Services data source;
  • Create a clone
    of an existing sample Analysis Services report, containing a matrix data
    region, with which to launch our overview;
  • Examine the simple
    Column chart type from the standpoint of the existing report, noting how
    we add it to an open report (and thus save time in leveraging existing datasets
    and other support structures) in the Layout tab;
  • Modify the
    existing primary dataset within the sample report clone, adding a filter
    to limit the size of the data presentation;
  • Make
    modifications to the report layout to support the stated client
    reporting needs and practice session objectives;
  • Create a complete,
    working sample of a simple Column chart data region, within the existing
    report, which will allow us to verify its accuracy and completeness once we
    have the chart in place;
  • Examine all
    relevant property settings within each of the General, Data,
    X Axis, Y Axis, Legend, and 3D Effect tabs;
  • Discuss the
    results obtained with the development techniques that we exploit throughout our practice session.

Objective and Business Scenario

In this article, we will
perform a relatively straightforward examination of the simple Column chart type, from within
a copy of an existing sample Reporting Services 2005 report that we will
create for this purpose. Our focus will be to create a working simple Column
chart
, using an Analysis
Services

data source (the
Adventure Works DW sample OLAP database / Adventure Works cube
that accompanies the installation of Reporting Services), while discussing various characteristics
of this chart type as we progress.

We will examine relevant chart properties, and get some initial
hands-on exposure to the manipulation of those properties to support the delivery
of information to meet the needs of a hypothetical group of
organizational information consumers. Other articles within the MSSQL Server Reporting
Services

series will advance beyond the practice session that we undertake here, using
the simple Column
chart

we create as a basis from which we can concentrate on in-depth procedures and
nuances that we can use to achieve precision in meeting specific requirements,
and delivering data presentation effects, that we might encounter within the
environments of our respective employers and / or clients.

The Business Need

For purposes of our
practice procedure, we will assume that a group of report developers and
analysts, composed of members of the Sales, Marketing, Information
Technology
, and other departments of the Adventure Works
organization, have expressed the need to present some of the information displayed
in the existing Sales
Reason Comparisons
OLAP
report through a new
Column chart report. The group has stated that they want to leverage
this “conversion” process to learn more about the construction and
characteristics of simple Column chart reports in general. Moreover, they
assure us that they will extrapolate the techniques they learn to scenarios
where they will design, create and deploy reports of this type in the future.

Once
we understand the business need, we propose using a copy of the existing Sales Reason Comparisons report (which, among other samples,
accompanies the installation of Reporting Services). Our tandem
objectives here, we explain, are 1) to streamline our procedures (by using existing connections, datasets,
and other structures that are already in place within the pre-existing report),
and 2) to provide a ready means of verifying at least some of the accuracy and
completeness of the new report (a feature that might be useful in initial
report testing). We mention, as an aside, that we can always delete the
existing matrix data region prior to deploying the final report.

Once
we obtain agreement on this approach, we begin the process of creating the simple Column chart
report to satisfy the information consumers.

William Pearson
William Pearson
Bill has been working with computers since before becoming a "big eight" CPA, after which he carried his growing information systems knowledge into management accounting, internal auditing, and various capacities of controllership. Bill entered the world of databases and financial systems when he became a consultant for CODA-Financials, a U.K. - based software company that hired only CPA's as application consultants to implement and maintain its integrated financial database - one of the most conceptually powerful, even in his current assessment, to have emerged. At CODA Bill deployed financial databases and business intelligence systems for many global clients. Working with SQL Server, Oracle, Sybase and Informix, and focusing on MSSQL Server, Bill created Island Technologies Inc. in 1997, and has developed a large and diverse customer base over the years since. Bill's background as a CPA, Internal Auditor and Management Accountant enable him to provide value to clients as a liaison between Accounting / Finance and Information Services. Moreover, as a Certified Information Technology Professional (CITP) - a Certified Public Accountant recognized for his or her unique ability to provide business insight by leveraging knowledge of information relationships and supporting technologies - Bill offers his clients the CPA's perspective and ability to understand the complicated business implications and risks associated with technology. From this perspective, he helps them to effectively manage information while ensuring the data's reliability, security, accessibility and relevance. Bill has implemented enterprise business intelligence systems over the years for many Fortune 500 companies, focusing his practice (since the advent of MSSQL Server 2000) upon the integrated Microsoft business intelligence solution. He leverages his years of experience with other enterprise OLAP and reporting applications (Cognos, Business Objects, Crystal, and others) in regular conversions of these once-dominant applications to the Microsoft BI stack. Bill believes it is easier to teach technical skills to people with non-technical training than vice-versa, and he constantly seeks ways to graft new technology into the Accounting and Finance arenas. Bill was awarded Microsoft SQL Server MVP in 2009. Hobbies include advanced literature studies and occasional lectures, with recent concentration upon the works of William Faulkner, Henry James, Marcel Proust, James Joyce, Honoré de Balzac, and Charles Dickens. Other long-time interests have included the exploration of generative music sourced from database architecture.

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