Business Intelligence and Analytics Principles and Practices: Charting the Course to BI and Analytic Success, Singapore

We can host this training at your preferred location. Contact us!

Business analytics and intelligence architecture is a set of frameworks to organize the data, management and technical components used to build BI systems and analytical capabilities. Architecture plays an important role in business analytics and intelligence programs and projects, ensuring that the development efforts of multiple projects and teams fit together to form a cohesive and valuable whole. Comprehensive architecture addresses business purposes, organizational structure and roles/responsibilities, integrated information resources, various types of key processes and a wide array of technology components.

There is no prerequisites for this course.

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

Why have you chosen us?

I have attended a training from Bilginc IT Academy before and I was satisfied.

I have attended a training from a different provider and it was not helpful.

Other

How many employees do you have in your IT department?

0 – 50

50 – 250

250 – 1000

1000+

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

Singapore, which is known officially as the Republic of Singapore, is a sovereign island city-state in maritime Southeast Asia and it consists of Singapore island and 60 islets. The capital city of Singapore is Singapore and the population of the island city-state is approximately 5,709,000. The official languages of Singapore are English, Chinese (Mandarin), Malay and Tamil.

Singapore is a year-round destination, but the best time to visit Singapore is from December to June. Between February to April, Singapore has the least amount of rain and the most sunshine, since it's the dry season. Singapore offers more than just luxury hotels and high-end shopping malls; there are many family-friendly attractions and historic places. Marina Bay Sands, Gardens by the Bay, Botanic Gardens and Singapore Flyer are the most popular tourist attractions.

Take advantage of our diverse IT course offerings, spanning programming, software development, business skills, data science, cybersecurity, cloud computing and virtualization. Our knowledgeable instructors will provide you with practical training and industry insights, delivered directly to your chosen venue in Singapore.

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

Upcoming Trainings

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

Prerequisites

Who Should Attend

What You Will Learn

Outline

BUSINESS INTELLIGENCE TERMS: A TO Z GLOSSARY

Upcoming Trainings