TDWI Analytics Fundamentals Training in Hong Kong

  • Learn via: Classroom / Virtual Classroom / Online
  • Duration: 1 Day
  • Price: Please contact for booking options
We can host this training at your preferred location. Contact us!

Analytics is a hot topic, but also a complex topic. This continuously growing field now includes descriptive, diagnostic, predictive, and prescriptive analytics. Applied analytics including optimization, simulation, and automation expand the scope. Data growth also fuels the complexity – unstructured data, big data, social data, data streams, and more. Advanced analytics continues to expand with complex event processing, machine learning, cognitive computing, etc.

In the growing and evolving world of analytics we’re also experiencing a shift of roles and responsibilities. The “data things” that were once seen as IT responsibilities have become critical business skills. Analytics spans a continuum that encompasses IT departments, data scientists, data analysts, business analysts, business managers, and business leadership. It seems that everyone has a stake in analytics. Coordination, cross-functional analysis, data sharing, and governance all become important skills.

There are no prerequisites for this course.

  • Business leaders and managers seeking to understand business dynamics through analytics
  • IT leaders and managers responsible to deliver and to support analytics initiatives
  • BI and analytics architects guiding the design, development, and deployment of analytics
  • BI and analytics designers and developers
  • Business analysts, data analysts, data scientists and those who aspire to these roles

  • The concepts and practices of analytic modeling
  • An analytics topology to make sense of the variety of analytic types and techniques
  • The data side of analytics including data sourcing, data discovery, data cleansing, and data preparation
  • Analytic techniques for exploration, experimentation, and discovery
  • The human side of analytics: communication, conversation, and collaboration
  • The organizational side of analytics: self-service, central services, governance, etc.
  • A bit about emerging techniques and technologies shaping the future of analytics

Module One: Concepts of Analytics

  • Analytics Defined
  • Data Analytics and Business Analytics
    • Variations of Purpose
    • Variations of Skills
  • Why Analytics
    • Cause and Effect
    • Strategy and Analytics
    • Tactics and Analytics
    • Operations and Analytics
    • Systemic Analytics
  • Analytics Processes
    • Problem Framing
    • Problem Modeling
    • Solution Modeling
    • Visualization and Presentation
    • Understanding and Action
  • Analytics Foundations
  • Data
    • Scope of Data
    • Finding Data
    • Observations and Populations
    • Raw Data vs. Summary Data
    • Data Preparation
  • Statistics
    • Histograms
    • Distribution and Deviation
    • Correlation
    • Regression
  • Visualization
    • Visual Design
    • Choosing Charts and Graphs
  • Business Impact
    • Simulation
    • Optimization
    • Automation

Module Two: The Analytics Environment

  • Analytics Stakeholders
  • The Participants
    • Business Stakeholders
    • Analytic Modelers and Data Scientists
    • IT and Data Organizations
  • Analytic Culture
  • Values, Beliefs, and Competencies
    • Numeracy
    • Collaboration
    • Conversation
    • Decision Styles
  • Analytics Organizations
  • Organization Models
    • Self Service
    • Shared Services
    • Central Services
    • Hybrid Organizations
  • Analytics and Governance
  • Analytics Capabilities
  • Business Capabilities
    • Planning
    • Executing
    • Adapting
    • Innovating
  • Analysis Capabilities
    • Evaluating
    • Detecting
    • Predicting
    • Classifying
    • Recommending
    • Monitoring
  • Data Capabilities
    • Measuring
    • Searching and Acquiring
    • Blending and Integrating
    • Securing
    • Provisioning
  • A Capability-Based Framework
    • Discovery Analytics
    • Descriptive Analytics
    • Diagnostic Analytics
    • Predictive Analytics
    • Prescriptive Analytics

Module Three: Analytics Architecture

  • The Big Picture
  • Data Architecture
    • Data Sources and Types
    • Data Acquisition
    • Data Ingestion
    • Persistence
    • Data Management Topology
    • Data Quality and Utility
    • Data Usage / Information Delivery
  • Process Architecture
  • Next Generation BI
    • Extending BI
  • Basic Data Analysis
    • Statistical Analysis
    • Time-Series Analysis
  • Discovery and Prediction
    • Data Mining
    • Predictive Modeling
    • Ensemble Modeling
  • Text and Language Analysis
    • Natural Language Processing
    • Text Mining o People and Behaviors
    • Sentiment Analysis
    • Behavioral Analytics
  • People and Social Media
    • Social Network Analysis
    • Social Media Analytics
  • Events and Data Streams
    • Stream Processing
    • Complex Event Processing
  • Smart Machines
    • Machine Learning
    • Cognitive Computing
  • Technology Architecture
  • Connectivity
    • SQL
    • Messaging
    • Services
    • Replication
    • Virtualization
  • Data Stores
    • RDBMS
    • Columnar
    • MPP
    • MDDB
    • NoSQL
    • In Memory
  • Data Analysis
    • Data Mining
    • Analytic Modeling
    • Big Data Analytics
    • Streaming Analytics
    • Event Processing
    • Machine Learning etc.
  • Data Flow
    • Batch
    • Real-time
    • Streams
  • Management
    • Workflow
    • Service Levels
  • Platforms
    • Servers
    • Appliances
    • Cloud

Module Four: Analytic Modeling

  • The Roles of Models
    • Understanding the Problem Space
    • Understanding the Data
    • Understanding the Language
    • Understanding the Business Dynamics
  • Kinds of Models
    • Framing Models
    • Questioning
    • Kernel Seeking
  • Cause-Effect Models
    • Influence Models
    • Causal Loop Models
  • Data Models
    • Physical Models
    • Logical Models
    • Conceptual Models
  • Language Models
    • Ontology
    • Taxonomy
    • Lexicon
    • Semantics
  • Solution Models
    • Formula Based
    • Algorithm Based
  • Problem Modeling
    • Framing the Problem
    • Influence Diagramming
    • Causal Modeling
  • Solution Modeling
  • Formula Based Modeling
    • Structuring
    • Defining
    • Documenting
    • Developing
    • Parameterizing
    • Visualizing
  • Algorithm Based Modeling
    • Business Understanding
    • Data Understanding
    • Data Preparation
    • Model Building
    • Evaluation
    • Deployment

Module Five: Applied Analytics

  • Discovery Analytics
  • Description
  • Techniques
    • Experimental Design
    • Rule Discovery
    • Data Mining
    • Regression Models
  • Enabled Business Capabilities
  • Examples
  • Descriptive Analytics
    • Description
    • Techniques
    • Statistical Models
    • Probability Distribution Models
    • Monte Carlo Models
  • Enabled Business Capabilities
  • Examples
  • Diagnostic Analytics
  • Description
  • Techniques
    • Control Charts
    • Classification Models
    • Abnormal Condition Models
  • Enabled Business Capabilities
  • Examples
  • Predictive Analytics
  • Description
  • Techniques
    • Regression Models
    • Neural Network Models
    • Time Series Forecasting Models
    • Bayes Theorem Models
  • Enabled Business Capabilities
  • Examples
  • Prescriptive Analytics
  • Description
  • Techniques
    • Discrete Event Models
    • Continuous Simulation Models
    • Optimization Models
    • Linear Programming Models
  • Enabled Business Capabilities
  • Examples

Module Six: Summary and Conclusion

  • Summary of Key Points
  • References and Resources


Contact us for more detail about our trainings and for all other enquiries!

Upcoming Trainings

Join our public courses in our Hong Kong facilities. Private class trainings will be organized at the location of your preference, according to your schedule.

01 January 2025 (1 Day)
Hong Kong, Kowloon, Tsuen Wan
Classroom / Virtual Classroom
18 January 2025 (1 Day)
Hong Kong, Kowloon, Tsuen Wan
Classroom / Virtual Classroom
18 January 2025 (1 Day)
Hong Kong, Kowloon, Tsuen Wan
Classroom / Virtual Classroom
21 January 2025 (1 Day)
Hong Kong, Kowloon, Tsuen Wan
Classroom / Virtual Classroom
01 January 2025 (1 Day)
Hong Kong, Kowloon, Tsuen Wan
Classroom / Virtual Classroom
18 January 2025 (1 Day)
Hong Kong, Kowloon, Tsuen Wan
Classroom / Virtual Classroom
18 January 2025 (1 Day)
Hong Kong, Kowloon, Tsuen Wan
Classroom / Virtual Classroom
21 January 2025 (1 Day)
Hong Kong, Kowloon, Tsuen Wan
Classroom / Virtual Classroom
TDWI Analytics Fundamentals Training Course in Hong Kong

Hong Kong is officially known as the Hong Kong Special Administrative Region of the People's Republic of China (HKSAR) and is a city and special administrative region of China on the eastern Pearl River Delta in South China. Hong Kong is one of the most densely populated places in the world, with over 7.5 million population. The official languages of the HKSAR are Chinese and English. Hong Kong is a highly developed territory and ranks fourth on the United Nations Human Development Index and the residents of Hong Kong have the highest life expectancies in the world.

The best time to visit Hong Kong is from September to December, since the temperatures, averaging between 19 to 28 degree Celsius. During this outdoor activities-friendly travelling season, you can take a walk along Victoria Harbour, visit the islands of Lantau, Lamma and Cheung Chau and participate in the Mid-Autumn Festival. Top choices of the tourists to visit in Hong Kong are Big Buddha statue, Wong Tai Sin Temple, Repulse Bay and the Beaches and Hong Kong Disneyland.

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