BI and DW – Concepts and Fundamentals

Designing and developing a DW/BI solution is no easy feat. Its takes a solid foundation based on fundamentals to create a solution that works. Clearing the fog of unanswered questions that initially befalls most projects provides clarity that emphasizes a focus on project goals. Equipped with the fundamentals of data warehousing and business intelligence, you’ll see the destination clearly and reach it faster.

concept

This course provides business and information technology professionals an overview that builds confidence to launch and contribute to a business intelligence and data warehousing movement in their organization.

  • We begin with business drivers for business intelligence and technology drivers for data warehousing, to explain how using DW/BI can affect your business.
  • Next, we discuss users and the different uses of business intelligence, including applications and tools that may surround it.
  • Following this, we introduce data integration and data warehousing, the heart of successful business intelligence systems.

Tools alone do not extract strategic value from business intelligence. The right set of users is required to complete a successful system. This course covers staffing and planning, along with best practices in design, development and implementation. Practical examples clarify technical concepts, techniques and theories. In-class exercises accentuate and underline functions and tasks that support project success.

With key pieces in play, we climb up to a high level discussion of how to develop a business intelligence application, create a data warehouse that supports it, and build an organizational structure to use it. We’ll discuss roles and responsibilities that contribute to successful operations and the skills required for each. Understanding critical factors that affect project success will help you plan strategically.

Throughout the project, there are several deliverables that will be produced. It’s important to understand what they are and why you need them.  This will enable better planning, and we’ll show you how to identify your deliverables and deliver them effectively using best practices.

We instruct on:

  • Fundamentals of business intelligence and data warehouse
  • Industry terminology
  • Critical success factors and possible risks
  • Business intelligence applications and usability
  • Data Integration Framework (DIF)
  • Development processes for DW and BI
  • Organizational culture and politics
  • Best practices
  • Industry trends

This course is designed for:

  • Business and technical management responsible for the design and implementation of business intelligence or data warehousing.
  • People who wish to better understand what is involved in managing business intelligence or data warehouse projects.

Prerequisites

None.

Course Outline:

Section 0: Introductions

Section 1: What is Business Intelligence and Data Warehousing?

  • Brief History on Data Access, Reporting and Analysis
  • Data to Information Lifecycle
  • Business Intelligence (BI) Definition
  • Data Warehousing Definition
  • Corporate Performance Management (CPM) Definition

Section 2: Business Intelligence and Data Warehousing – How they are Used

  • Business Drivers for BI
  • Business and IT Drivers For DW
  • Applications that use BI and DW
  • Data Shadow Systems
  • Industry terminology

Section 3: Business Intelligence and Data Warehousing – Architectures

  • Four Types of Architectures
  • How do business intelligence and data warehousing work together?

Section 4: Information Architecture – BI applications and usage

  • Business applications for BI
  • BI Categories – Reporting to Analytics
  • OLAP Architectures
  • Classifying BI users

Section 5: Data Integration

  • Overview
  • Data modeling concepts
  • Data Integration Framework (DIF)

Section 6: Data Architecture

  • Processes
  • Transforming data to information
  • Process management
  • Data Stores
  • Data Warehouse, Data Marts, Operational Data Stores, Cubes
  • Architectures
  • Data staging options
  • Implementation choices
  • Standards
  • Tools
  • Resources & Skills

Section 7: Technology Architecture

  • Overview
  • Data Integration
  • Business Intelligence
  • Databases
  • Deployment & Operational Tools

Section 8: Product Architecture

  • Major data warehouse and BI vendors
  • Market positioning

Note: Start with brief overview positioning vendors within market. Not intended to evaluate or endorse vendors

Section 9: Culture, Politics and Organization

  • Overview
  • Sponsorship and Governance
  • Program Organization and Management
  • Project Organization and Management
  • Project Methodologies

Section 10: Industry Trends

  • Overall Software Industry
  • Enterprise Applications
  • Data Integration
  • Business Intelligence

Section 11: Best Practice Overview

  • Data Integration
  • Business Intelligence

Section 12: Conclusions

  • Highlights
  • References and Resources