Chapter 1: Business Intelligence Overview

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CHAPTER 1: BUSINESS INTELLIGENCE OVERVIEW Objectives

The objectives are:

• Define business intelligence. • Examine the Business Analytics architecture. • Provide insight into the online analytical processing technology. • Get acquainted with the business intelligence terminology.

Introduction Business analysts often need to get an overview of the business, to see broader trends based on aggregated data, and to see these trends broken down by any number of variables. Business intelligence (BI) is a broad category of applications, and technologies used for gathering and analyzing data to help analysts make better business decisions, and ultimately improve business performance. Common functions of business intelligence applications are reporting, analytics, data mining, and predictive analysis.

The Microsoft vision of the business intelligence is to help drive businesses to better performance by empowering all employees throughout the organization to make better decisions on the strategic, tactical, and operational level. This vision is achieved by providing cross-product integration, delivering business intelligence capabilities within Microsoft Office, and making its business intelligence offerings scalable.

The goal of this training manual is to demonstrate advanced ways on how IT professionals can transform data from a Microsoft Dynamics® NAV 2009 database into business intelligence information. This BI information then helps decision-makers to gain the insight required to optimize performance across the entire organization.

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Business Intelligence Overview Business intelligence has become an essential part of strategic and tactical business management. Companies often lack resources and appropriate software to process the data and information generated by their Enterprise Resource Program (ERP) and other applications into meaningful business insight. The role of business intelligence is to help access the right information at the right time and transform it into insight, knowledge, and smart decisions.

On a broad scale, business intelligence can be described as any technology that enables companies to gain insight into the business. In this context, business intelligence comprises all solutions, tools, and features which allow users to make better decisions about their current and future activities. In the narrow sense, business intelligence comprises processing data, reporting, analysis, and online analytical procession (OLAP) cubes.

Business Intelligence and Microsoft Dynamics NAV

Microsoft Dynamics NAV has integrated business intelligence capabilities, such as standard reports, report wizard and report design tools, account schedules and analysis reports, analysis by dimensions, and transaction navigation. In addition to the built-in functionalities, Microsoft Dynamics NAV can benefit from working also with external business intelligence tools and applications. These include the following:

• Microsoft® Office Excel®. Account schedules, analysis reports, and analysis by dimensions within Microsoft Dynamics NAV can be exported to Microsoft Office Excel for further processing.

• Business Analytics for Microsoft Dynamics NAV (basic and advanced). This is a powerful application which turns data into business information.

• Microsoft® Office Business Scorecard Manager® (BSM). This is a business performance management application designed to help companies to move forward with a common purpose and direction by making key performance indicators (KPIs) fully available throughout an organization. This scorecard application is designed for defining, building, deploying and using scorecards and KPIs. With this application, users can consolidate data from a variety of sources. BSM supports the task of linking defined strategies to specific measures and actions throughout all levels of the organization.

• Microsoft® FRx®. This is an easy to use and install, financial reporting application that helps you to quickly and easily build and maintain financial reports and complex ad-hoc management reports.

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• Microsoft SQL Server Analysis Services. This is a part of the Microsoft SQL server that performs online analytical processing (OLAP) in Microsoft Dynamics NAV. OLAP is a technology that pre-processes a company’s data into an information unit called a cube. When a company runs Microsoft Dynamics NAV on Microsoft SQL Server, they will benefit from a lot of analysis capabilities that can be leveraged along with the rest of the Microsoft stack such as Microsoft Excel and Microsoft SQL Server Reporting Services. Once the cubes are defined, users can access them through a variety of applications to see different views of the data.

• Microsoft SQL Server Reporting Services. This is a comprehensive, server-based solution that allows the user to create, manage, and deliver both traditional, paper-oriented reports and interactive, Web-based reports. An integrated part of the Microsoft business intelligence framework, Reporting Services combines the data management capabilities of Microsoft® SQL Server® and Microsoft® Windows® Server with familiar and powerful Microsoft Office System applications to deliver real-time information to support daily operations and drive decisions. Microsoft SQL Server Reporting Services supports the full reporting life cycle, including: report authoring, management, delivery and security.

• Employee Portal for Microsoft Dynamics NAV is an easy way for company employees to work with all their business information on the company intranet. Using the Web-based interface, users can basically view all company data online instead of in the back-end application. The framework is intuitive and requires little training since it looks and feels like the other Microsoft applications. Because access is role-based, users see only the data relevant to their jobs.

Business Analytics Architecture This section outlines the architecture of one of the external business intelligence tools that works with Microsoft Dynamics NAV 2009 - Business Analytics.

Overview

Business Analytics for Microsoft Dynamics NAV is a tool that provides interface between Microsoft Dynamics NAV and Microsoft SQL Server Analysis Services. Microsoft® SQL Server® 2005 or Microsoft® SQL Server® 2008 is used for the Business Analytics part, while Microsoft Dynamics NAV itself can be either with Microsoft SQL Server, or with Database Server.

Technically, Business Analytics makes it possible to populate cubes in Microsoft SQL Server Analysis Services automatically with data from Microsoft Dynamics NAV. Any OLAP client that can access Analysis Services can be used to analyze the data on Analysis Services, create reports, and so forth.

Business Analytics for Microsoft Dynamics NAV has two versions, Basic and Advanced, and both will be described in this section.

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Basic Version

The Basic version is the starting point, and must be installed to run Business Analytics. The main features of the Basic version are as follows:

• Configurator - This tool sets up Analysis Services on the basis of a set of definitions created within Microsoft Dynamics NAV. This means that the Configurator creates cubes, dimensions, and measures. It also performs other essential tasks that are required to use Analysis Services, such as setting up an Analysis Services database role which defines access to objects and data in an Analysis Services database. Finally, it creates a SQL Agent job to retrieve data from Microsoft Dynamics NAV automatically. Meaning, the Configurator creates a data mart on Analysis Services.

• Microsoft Dynamics NAV contains a set of predefined cubes, dimensions, and measures that can be used out-of-the-box to start working with Business Analytics. The user can modify these default cubes, dimensions, and measures or create new ones.

Advanced Version

The Advanced version of Business Analytics builds on top of the cubes built with the Basic version. The main features available are:

• A Web client that provides a Web-based interface, making it possible to perform analyses from a Web browser.

• A Business Analytics client that makes setting up access to the data mart easy and intuitive by means of generating reports, dashboards, analyses, performing datamining, and so forth.

• A server component (the ANTServer) that allows the user to set up security in an easy way, so that the access to the data can be controlled. The ANTServer can also work with other data marts, so that a fully-fledged data warehouse can be created, where the Microsoft Dynamics NAV data mart is one component, and the Advanced client gives uniform access to all these data marts.

You can also use other OLAP clients, different from the one that comes with the Advanced version to access the data mart. For example, Microsoft Excel can be used.

When you specify a database or a .cub file the Advanced version works with, and add the proper role permissions in SQL Server Management Studio, no further setup is necessary for the Business Analytics Advanced client.

NOTE: When using the Business Analytics client that comes with the Advanced version, and when accessing the ANTServer through a Web browser and the Analysis.NET application, a dedicated query language is used.

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Interaction of Business Analytics Components

The following diagram shows how Business Analytics components interact with each other.

FIGURE 1.1 INTERACTION OF BUSINESS ANALYTICS COMPONENTS

OLAP technology This section gives a brief overview of the online analytical processing technology and explains how the technology is related to business intelligence.

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OLAP Concept

Effective decisions of a business analyst depend on how rapidly he or she can retrieve data for analysis and how flexible the analysis can be. To meet these business intelligence needs, an online analytical processing (OLAP) technology has been developed. This technology is used to organize large business databases and support business intelligence. OLAP databases are divided into one or more cubes, and each cube is organized and designed by a cube administrator to fit the way one can retrieve and analyze data with an OLAP client, such as Microsoft Office Excel or Business Analytics for Microsoft Dynamics NAV. The end user sees the cube as a multidimensional dynamic table, which automatically processes data (facts) in various dimensions, and allows the user to interactively manipulate the calculations and the reporting form.

The OLAP database technology is optimized for querying and reporting, instead of processing transactions. The source data for OLAP is online transactional processing (OLTP) databases. OLAP data is retrieved from this source data and aggregated into structures that permit sophisticated analysis. OLAP data is organized hierarchically and stored in cubes instead of tables. This OLAP technology uses multidimensional structures to provide rapid access to data for analysis.

OLAP databases contain two types of data:

• Measures - are numeric data, the quantities and averages that an analyst uses to make business decisions.

• Dimensions - are the categories that an analyst uses to organize measures. Thus, measures are categorized by dimensions.

Measures and dimensions constitute cube metadata that is typically created from a star schema or a snowflake schema of tables in a relational database. Measures are derived from the records in the fact table and dimensions are derived from dimension tables.

The output of an OLAP query is typically displayed in a matrix (or pivot) format, such as pivot table reports in Microsoft Office Excel. The dimensions form the rows and columns of the matrix; the measures form the values.

OLAP Server

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An OLAP server is a high-capacity, multi-user data manipulation engine specifically designed to support and operate on multi-dimensional data structures. The structure of the OLAP server is multi-dimensional and is arranged so that every data item is located and accessed based on the intersection of the dimension members which define that item. The design of the server and the structure of the data are optimized for rapid ad-hoc information retrieval in any orientation, and for fast, flexible calculation and transformation of raw data based on formulaic relationships. The OLAP server may either physically stage the processed multi-dimensional information to deliver consistent and rapid response times to end users, or it may populate its data structures in real-time from relational or other databases, or offer a choice of both.

Terminology This section gives a list of terms you will come across reading this manual. The terms are meant to help you get a better understanding of the OLAP technology and BI procedures covered in the further chapters.

Cube - is a core of an OLAP system, a data structure that aggregates the measures by the levels and hierarchies of each of the dimensions that an analyst wants to analyze. Cubes combine several dimensions, such as time, geography, product lines, and so forth, with summarized data, such as sales or inventory figures.

Measure - is a set of values in a cube that are based on a column in the cube's fact table and that are usually numeric values. Measures are the central values in the cube that are preprocessed, aggregated, and analyzed. Common examples include sales, profits, revenues, and costs.

Dimension - is a set of one or more organized hierarchies of levels in a cube that a user understands and uses as the base for data analysis. For example, a geography dimension might include levels for Country/Region, State/Province, and City, or, a time dimension might include a hierarchy with levels for year, quarter, month, and day.

Member - is an item in a hierarchy representing one or more occurrences of data. Members can be either unique or non-unique. For example, 2008 and 2009 represent unique members in the year level of a time dimension, whereas January represents non-unique members in the month level because there can be more than one January in the time dimension if it contains data for more than one year. A calculated member is a member of a dimension while value is calculated at run time by using an expression.

Hierarchy - is a logical tree structure that organizes the members of a dimension such that each member has one parent member and zero or more child members.

Level - within a hierarchy, data can be organized into lower and higher levels of detail. For example, Year, Quarter, Month, and Day are levels in a Time hierarchy.

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Data Warehouse - is a repository of an organization's electronically stored data. The purpose of data warehouses is to facilitate reporting and analysis in business intelligence.

Fact Table - is a central table on the basis of which a cube is build. This table comprises measurements, metrics or facts of a business process. The fact table is often located in the centre of a star schema, surrounded by dimensional tables. There are usually two types of columns in a fact table: the ones containing facts, and those that are foreign keys to dimensional tables.

Star Schema - is the simplest type of the data warehouse schema. The star schema consists of one or few fact tables that reference any number of dimension tables. The star schema is an important element of a snowflake schema.

Snowflake Schema - is a logical arrangement of tables in a relational database in such a way the entity relationship resembles a snowflake in shape.

Summary Business intelligence can be considered in the broad and in the narrow senses. Generally, business intelligence is any technology, skills, and applications that help companies gain a comprehensive and integrated view of their business and facilitate better and more effective decision-making. On a small scale, BI is processing data and information, reporting, analysis, and working with OLAP cubes.

Microsoft Dynamics NAV 2009 has integrated business intelligence capabilities; also, there are a big number of external tools that can facilitate business intelligence functionality for Microsoft Dynamics NAV. Among the most sophisticated and user-friendly BI tools available for Microsoft Dynamics NAV is Business Analytics, which has two versions: Basic and Advanced. The distinguishing features of the Basic version are: the Configurator; predefined cubes, dimensions, and measures to be used out-of-the-box. The Advanced version can work only on the condition that the Basic version is installed. The Advanced version adds the following features: a server component (the ANTServer) and a client that provides the intuitive and user-friendly GUI for business intelligence.

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Test Your Knowledge

1. What is the main purpose of the business intelligence technologies and applications?

( ) Organize business data into a logical hierarchy ( ) Make business decisions on the basis of gathered and analyzed data ( ) Facilitate rapid data transfer between the data warehouse and data

processing applications ( ) Maintain a database to ensure the data is consistent and ready to be

processed

2. What is a core informational unit in the OLAP technology that the data is pre-processed into?

( ) Measure ( ) Cube ( ) Dimension ( ) Item

3. Where does Business Analytics for Microsoft Dynamics NAV make it possible to populate cubes with data from Microsoft Dynamics NAV?

4. For which operations is the OLAP technology optimized for? (Select all that apply)

( ) Querying ( ) Reporting ( ) Storing data ( ) Processing transactions

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Quick Interaction: Lessons Learned Take a moment and write down three Key Points you have learned from this chapter

1.

2.

3.

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Solutions Test Your Knowledge

1. What is the main purpose of the business intelligence technologies and applications?

( ) Organize business data into a logical hierarchy (•) Make business decisions on the basis of gathered and analyzed data ( ) Facilitate rapid data transfer between the data warehouse and data

processing applications ( ) Maintain a database to ensure the data is consistent and ready to be

processed

2. What is a core informational unit in the OLAP technology that the data is pre-processed into?

( ) Measure (•) Cube ( ) Dimension ( ) Item

3. Where does Business Analytics for Microsoft Dynamics NAV make it possible to populate cubes with data from Microsoft Dynamics NAV?

MODEL ANSWER:

In Microsoft SQL Server Analysis Services

4. For which operations is the OLAP technology optimized for? (Select all that apply)

(√) Querying (√) Reporting ( ) Storing data ( ) Processing transactions

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