Business Intelligence and Analytics Principles and Practices: Charting the Course to BI and Analytic Success Training in Hong Kong

• Business, data, integration and technology architects involved in business analytics and intelligence programs
• Business Analytics and Intelligence program and project managers that need a basic understanding of the fundamental components of successful analytics and BI programs
• Business Analytics and Intelligence team members that need a better understanding of the big picture of the systems they work with

• The full scope of architectural objectives – structural integrity, standardization, reusability, environmental fit, esthetics, and sustainability
• A framework to ensure overall architectural completeness and success - business purpose, organization, integrated information, process and technology platforms
• A framework to organize business components - performance, stakeholders, processes, rules and information
• A framework to organize the organization - people, purpose, process and structure
• A framework to organize information components and capabilities- collection, storage, operational data integration, data warehousing, big data integration, distribution/access/applications and data modeling/metadata management
• A framework to organize the processes associated with business analytics and intelligence - methdologies, data governance, data modeling/metadata management, data flow, business processes and operations/support
• A framework to organize technology platform components - servers, data sourcing, databases, storage, data integration, business analytics and data management

Module 1 - BI and Analytics—Then and Now

• Definitions
  • Data Warehousing
  • Business Intelligence
  • Business Analytics
• Evolution
  • Achieving Business goals
  • Emphasis
• Components
  • People and Applications
  • Systems and Processes
  • Data and Technology
• Perspectives
  • Points of View
• Program Orientation
  • BI and Analytics Lifecycle
  • Evolving Environment
  • Parallel Paths
• Assessment
  • Purpose and Approach
  • Maturity Models
• Roadmap
  • Continuous Planning
• Mistakes to Avoid
  • When Validating Direction
  • When Delivering Business-Driven BI
• Summary and Discussion
  • Key Points
  • Discussion

Module 2 - Supporting the Organization

• BI and Analytics Stages
  • Purpose
• Descriptive BI and Analytics
  • Definitions and Benefits
  • Query Services
  • Data Feeds and Downloads
  • On-Demand Reporting
  • Scheduled Reporting
  • Basic Data Visualization
• Diagnostic BI and Analytics
  • Definition and Benefits
  • Online Analytical Processing
  • Dimensional Data Marts and Star Schema
  • The OLAP Cube
  • Performance Management: Definitions and Concepts
  • Performance Management
  • Scorecards and Dashboards
  • Continuum
  • Casual Analysis
  • Analysis Types
• Discovery BI and Analytics
  • Definitions and Benefits
  • Analytic Modeling
  • Advanced Data Visualization
  • Data Mining
  • Geospatial Analytics
  • Text Analytics
  • Storytelling
• Predictive BI and Analytics
  • Definition and Benefits
  • Forecasting and Prediction
• Prescriptive BI and Analytics
  • Definitions and Benefits
  • Simulation and Optimization
  • Decision Management
• Roadmap
  • Expanding Your Roadmap
• Mistakes to Avoid
  • In Predictive Analytics Efforts
  • In Data Storytelling
• Summary and Discussion
  • Key Points
  • Discussion

Module 3 - Architecture and Methodology

• Data Integration Architecture
  • Integration Strategy
  • The Purpose of Architecture
  • Architecture and Data
  • Components and Structures
  • Integration Techniques and Technologies
• Data Types
  • Data Properties
  • Data Characteristics
  • Data Structure
  • Big Data Defined
  • Big Data Sources
  • Big Data Characteristics
  • Physical Storage
• Ecosystem
  • Building Blocks
  • Traditional Architecture
  • Data Lakes
  • Analytics Sandboxes
  • Expanded Architecture
• Data Warehouse Implementation
  • Agile Development
  • Data Warehouse Automation
  • What Can You Automate?
  • Data Warehouse Operation
  • Components
• Evolution
  • Project Selection
• Roadmap
  • Expanding Your Roadmap
• Mistakes to Avoid
  • When Using Data Federation
  • In Your Big Data Implementation
• Summary and Discussion
  • Key Points
  • Discussion

Module 4 - Data Management

• Data Governance
  • Data Governance Concepts
  • Data Governance Roles and Responsibilities
  • Data Stewardship
• Data Quality
  • Data Quality Concepts
  • Data Quality Assessment
  • Data Quality Improvement
• Data Profiling
  • Purpose and Processes
  • Profiling Techniques
  • Analyzing Data Profiles
  • Tools and Technology
  • Application
• Roadmap
  • Continuous Planning
• Mistakes to Avoid
  • When Creating Your Data Strategy
  • When Building a Data Quality Program
• Summary and Discussion
  • Key Points
  • Discussion

Module 5 - BI Technology

• The Technology Stack
• Technology Layers
  • Functions and Services
• Technology Architecture
  • The Right Technology-Present and Future
  • Technology Management
  • Reliable Platforms
• Roadmap
  • Continuous Planning
• Mistakes to Avoid
  • When Adopting New Technologies in BI
  • In Hadoop Implementations
• Summary and Discussion
  • Key Points
  • Discussion

Module 6 – Summary

• Summary
  • Key Points