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MS SQL

Posted May 8, 2006

Mastering Enterprise BI: Introduction to Key Performance Indicators

By William Pearson

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 within this series, 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 also need to have:

  • Membership within one of the following:

    • the Administrators local group on the Analysis Services computer

    • the Server role in the instance of Analysis Services

  • 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. 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, 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, 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

A Key Performance Indicator ("KPI") is a performance measure that specifies an emphasis intended to produce a desired result. As quantifiable measurements that gauge business success, KPIs can be diverse in nature, but they typically represent values, statuses, trends, or goals. KPIs often combine two or more of these into a single indicator. Because their purpose is to present high level, summary information to executives or other managers of the enterprise, who then use the information to steer an integrated organization, we typically limit the number of these vital measures to only a few.

KPIs are usually graphic in nature, and are collected into a dashboard, scorecard, or other central point of reference, where they can be easily accessed by the management team, to obtain a quick and accurate summary of business success or progress toward success. KPIs make it possible for management to make decisions and take action. Based upon the information the indicators convey, managers can pull the processes and activities that the KPIs represent into alignment with strategic goals and objectives.

KPIs can range from simple to complex, and they are often evaluated over time. A simple KPI (represented, say, by a smiling or frowning "Smiley" face image) might indicate a status of monthly employee turnover or headcount, either of which might represent a single, but important, key measure. A more complex KPI might combine multiple perspectives (a status, with regard to corporate market share for a given product, coupled with a trend, such as competitor market share over the past few months for a similar product) into a single graphic (say a directional arrow or a traffic signal), indicating that the enterprise is leading in share, that share is eroding, or even that it has been overtaken by its competition. KPIs can be used alone or in combination to support rapid management decisions and actions, and to provide an indication of progress toward the accomplishment of intended strategic outcomes.

In this article, we will examine KPIs, and get hands-on exposure to the process of adding them to a sample cube, within the Business Intelligence Development Studio. We will overview the creation of KPIs based upon measures and calculated measures, and discuss ways in which to use them to offer robust decision support capabilities. As a part of our examination of the steps, we will:

  • Discuss the concepts behind KPIs, and how we can leverage them within our business environments for decision support, analysis and reporting purposes;

  • Create a clone Analysis Services Database in SQL Server Management Studio, within which to conduct our practice exercises;

  • Access the Analysis Services Database from within Business Intelligence Development Studio to perform our practice exercises;

  • Create a calculated measure to partially support the KPI we create in our practice session;

  • Create a KPI, demonstrating examples of input for various expressions within its designer form;

  • Browse the KPI, to verify operation and overview basic features.

Introducing Key Performance Indicators

Overview and Discussion

In Analysis Services 2005, Key Performance Indicators are composed of calculations that are associated with a measure group (or, alternatively, all measure groups) within a cube. MDX expressions, regular measures and calculated measures, often in combination, are used to generate KPIs. Because KPIs in Analysis Services contain additional metadata, they can direct the way that the results of their underlying calculations can be displayed in client applications.

Different client applications can consume Analysis Services KPIs because they are server-based, offering advantages in presentation flexibility. Other strengths of the server-based indicators include the obvious performance benefits that accrue through the performance of what are often complex calculations on the server rather than on the client machines, as well as the fact that they clearly provide a "single version of the truth" versus separate, potentially differing versions in separate client applications.

Analysis Services KPIs are supported by measures or calculated measures, and, as we shall see in the practice section, they have multiple properties which we define as part of their creation. KPI properties include a Value Expression, a Goal Expression, a Status Indicator and a Status Expression, and a Trend Indicator, and a Trend Expression. (We will discuss each of these as we add them in our practice KPI later.) We can also define a Parent KPI, a Current Time Member, a Weight, and a Description. Moreover, we can logically group our KPIs through the use of a Display Folder.

The Goal and Value are usually the two most important properties of the KPI. The Value represents the "current state" of the measure, whereas the Goal represents the "desired state" of the measure, or the state toward which the organization is striving. As we shall see, the use and comparison of these two properties helps us to derive the Status and Trend of the Key Performance Indicator.

Considerations and Comments

For purposes of the practice exercises within this series, we will be working with samples that are provided with MSSQL Server 2005 Analysis Services. These samples include, predominantly, the Adventure Works DW Analysis Services database (with member objects). The Adventure Works DW Analysis Services database and companion samples are not installed by default in MSSQL Server 2005. The samples can be installed during Setup, or at any time after MSSQL Server has been installed. The topics "Running Setup to Install AdventureWorks Sample Databases and Samples" in SQL Server Setup Help or "Installing AdventureWorks Sample Databases and Samples" in the Books Online (both of which are included on the installation CD(s), and are available from www.Microsoft.com and other sources, as well), provide guidance on samples installation.

Important information regarding the rights / privileges required to accomplish samples installation, as well as to access the samples once installed, is included in the references I have noted.

Hands-On Procedure

Let's get some hands-on practice with the construction and use of KPIs. To prepare, we will create a new Analysis Services database, based upon the existing Adventure Works DW sample, to insulate the original sample database from modifications we will make. We will accomplish the creation of the "clone" database from within the SQL Server Management Studio, and then work with our new database from the Business Intelligence Development Studio.



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