Business Information and Modern BI: Balancing OLAP, Analytics, and Performance Management Training

The dimensional data marts of yesterday are insufficient to meet the demands of a modern BI program.

Business expectations have expanded to include analytics and performance management. Enterprise initiatives call for data governance and master data management (MDM). New methods and technologies bring the possibility of virtualization, agile development, and big data initiatives.

This course will show you how to meet this expanding list of challenges, starting from a dimensional view of the business and building outward.

BI program managers; business sponsors and information consumers; business analysts; data architects and systems architects; developers of data marts, data warehouses, OLAP environments, semantic layers, or information products such as reports, dashboards, and scorecards.

• How to classify business requirements across key BI functions: business analytics, OLAP, and performance management
• Where data governance and MDM intersect with your BI program
• The impacts of big data technologies on your information architecture: virtualization, unstructured data, data mining, and visualization
• Dimensional modeling techniques that facilitate business interaction, support high-impact analytics, and synchronize with integrated performance management
• Best practices that ensure your data warehouse is a useful resource for business analytics
• Which parts of your information architecture should be subject to centralized development and control, and which parts can be entrusted to the business
• Multiple ways to enable the combination of enterprise dimensional data with local, external, or unstructured data
• How to match methodologies and technology standards to the unique requirements of each initiative

Module 1 Modern BI

• Modern Concerns
  • Traditional data architecture
  • Impact of new technologies and practices
• Who Has an Interest in Information
• Modern BI Services
  • The Three Pillars of Modern BI
  • Performance Management, OLAP and Analytics
• Modern Information Architecture
• Impact of new technology on each service category
• Information Requirements
  • Organizing information requirements by business process
  • Sorting requirements by BI service

Module 2 Performance Management

• Performance Management
  • Business performance
  • Dashboards and Scorecards
• Business Metrics and Data
  • Aligning metrics with business strategy
  • How to document business metrics
• Performance Management and Other Services
  • Linking dashboards to detail (PM and OLAP)
  • Targeting analytics and measuring ROI (PM and Analytics)
• Dynamic Nature of Performance Management
  • Project vs. operations
  • Adapting and evolving content of performance dashboards
• Visualization
  • Communicating the right message
  • Eliminating chart junk
  • High bandwidth visual elements

Module 3 Business Analytics

• Insight and Impact
  • What is an analytic model
  • Kinds of models
• Enabling Analytics
  • Identifying where analytics can have business impact
  • The makeup of project teams
  • Business analysts and analytic modelers
  • Methodologies for analytics
• Big Data
  • Sorting through the hype
  • Kinds of data structures
• Information Architecture
  • The place of unstructured data in your program
  • Capture & Explore
  • Discard / Deploy / Augment / Extend
• Analytics and Performance Management
  • Targeting metrics and measuring ROI
• Which Data to Use
  • Looking beyond enterprise data
  • The analytic sandbox
• Incorporating Unstructured Data
  • Augmenting the data warehouse
  • Linking dimensional data with machine data, semi structured data and key-value pairs

Module 4 OLAP and Reporting

• Analysis and Detail
  • Supporting ad hoc access, analysis and reporting
  • Integrated record of business performance
• Enterprise Perspective
  • Integrated data vs. stovepipes
  • Conformance
• Business Information Requirements
  • Capturing requirements through the Business Dimensional Model (BDM)
  • Fact groups & definitions
  • Dimensionality and hierarchies
  • Master Data Management
• Dimensional Design
  • Key characteristics of dimensional models
  • Handling history through “slow changes”
  • How to document a dimensional design
  • Quick overview of advanced concepts in dimensional modeling
• Governance and Master Data
  • Data governance
  • Governance roles
  • Master data management
  • Master data and conformed dimensions
• OLAP and Performance Management
  • Synchronizing perspectives on business metrics
• OLAP and Business Analytics
  • Making the data warehouse analytics-friendly
• Virtualization
  • Where virtualization may fit in the information architecture

Module 5 People, Process, and Technology

• Architecture
  • Components of architecture
  • Program management and planned evolution
• Process: One size does not fit all
  • Different nature of projects in OLAP, performance management and analytics
  • Adapting projects to scope and importance of business need
• Development Methods
  • Control vs. autonomy in each BI service category
  • The agile manifesto
  • Collaboration and frequent delivery in BI
• Organization: BI, IT and the Business
  • Evolution of BI and analytic capabilities
  • Cross-functional teams
  • Competency centers and the contract with IT
• Choosing Your Toolset
  • Program control vs. Business Autonomy
  • Policies for centralized and user-maintained toolsets

Module 6 Summary and Conclusions

• Summary of Key Points
• Recommended Reading