The (IBM) Big Data Analytics for Strategic Decision-Making course is a enterprise-focused training programme designed to equip professionals with the capability to formulate, integrate, and evaluate big data analytics strategies that directly support organisational decision-making and performance improvement. The course goes beyond technical exposure to big data concepts and places strong emphasis on strategic application, stakeholder influence, and governance-aware analytics adoption. Learners are guided to view big data not merely as a technology initiative, but as a business capability that shapes strategy, operations, and competitive advantage. Modern organisations require leaders and professionals who can:
- Translate complex data into strategic insight
- Support executive decisions with evidence-based analysis
- Balance analytical sophistication with usability and timeliness
This course embeds analytics within decision-making, stakeholder engagement, and organisational transformation contexts, ensuring relevance at leadership levels.
Learning Objectives
By the end of this program, participants will be able to:
- Develop a clear and structured understanding of Big Data Analytics as a strategic business capability
• Distinguish Big Data Analytics from traditional business analytics in terms of scope, data types, and decision impact
• Understand how Big Data Analytics transforms operational, tactical, and strategic decision-making
• Identify key drivers, trends, and organisational factors influencing Big Data adoption
• Interpret analytics insights in business and decision-making contexts rather than technical terms
• Recognise ethical, regulatory, and governance considerations associated with large-scale data and analytics usage
• Communicate the value of Big Data Analytics effectively to diverse stakeholders
Learning Outcomes
Upon successful completion of the course, participants will demonstrate:
- Enhanced conceptual literacy in Big Data Analytics suitable for decision-makers and business leaders
• Improved ability to integrate analytics insights into strategic and operational decisions
• Greater confidence in evaluating analytics initiatives and their organisational impact
• Readiness to engage in analytics-driven discussions with executives, technical teams, and stakeholders
• Increased capability to promote data-driven decision-making within their organisations
Course Code: TGS-2025061178
Course Duration: 3 days
Course Fee: $1950.00
| TYPE | Singapore Citizens and
Singapore Permanent Residents |
Employer-sponsored and self-sponsored Singapore Citizens aged 40 years old and above | SME-sponsored
Local employees (i.e Singapore Citizens and Singapore Permanent Residents) |
| SkillsFuture
Funding (Baseline) |
SkillsFuture
Mid-career Enhanced Subsidy |
SkillsFuture
Enhanced Training Support For SMEs |
|
| Course Fee | $1950.00 | $1950.00 | $1950.00 |
| SkillsFuture Funding | $975.00 | $1365.00 | $1365.00 |
| Total Nett Fee | $975.00 | $585.00 | $585.00 |
| GST (9% of Course fee) | $175.50 | $175.50 | $175.50 |
| Total Fee Payable to | $1150.50 | $760.50 | $760.50 |
Price indicated are the payable amount with GST, must be made before the commencement of the course.
-
Payment by Cash/Paynow/SkillsFuture Credit (for eligible Singaporeans), cheque or Giro Bank Transfers (for companies).
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Refund of course fees is applicable upon absence/withdrawal with a valid reason (e.g. production of mc)
*For more information on Course fee funding, please visit this link: https://www.myskillsfuture.gov.sg/content/portal/en/career-resources/career-resources/education-career-personal-development/skillsfuture-funding-changes.html
Absentee Payroll Funding Support is applicable for Employer sponsored SGs or PRs; standardised at $4.50/hr.
For more information go to: https://www.enterprisejobskills.gov.sg/content/upgrade-skills/course-fee-and-absentee-payroll-funding.html
Introduction to Big Data Analytics
- Definition and Scope of Big Data
- What Is Big Data?
- Scope of Big Data Analytics
- Big Data vs Traditional Analytics
- Key Drivers and Trends in Big Data Adoption
- Regulatory and Risk Requirements
- Technological Advancements
- Major Trends in Big Data Analytics
- Shift from Batch to Real-Time Analytics
- Integration with AI and Machine Learning
- Self-Service and Democratization of Analytics
- Cloud-Native Big Data Platforms
- Strategic Implications of These Trends
Transforming Decision-Making with Big Data
- From Intuition-Based to Data-Driven Decisions
- How Big Data Changes the Nature of Decisions
- Data-Driven Business Improvement Case Studies
- Decision Transformation:
Strategic Decision-Making with Big Data - From Descriptive Insight to Strategic Action
- Improving Decision Quality, Not Just Speed
- Organisational Implications of Data-Driven Decisions
- Challenges in Data-Driven Decision Transformation
- Business Focus: Decisions Before Data
Promoting Big Data in Organisations
- Big Data as an Organisational Capability
- Encouraging a Data-Driven Culture
- What Is a Data-Driven Culture?
- Leadership’s Role in Cultural Adoption
- Reducing Fear and Resistance to Analytics
- Building Data Literacy Across Roles
- Communicating the Value of Big Data Analytics
- Why Communication Matters
- Translating Analytics into Business Language
- Using Business Use Cases to Build Confidence
- Aligning Analytics with Business Priorities
- Managing Expectations and Limitations
- Organisational Structures Supporting Big Data Promotion
- Common Barriers to Promoting Big Data
- Business Focus: Adoption Before Sophistication
Big Data and Traditional Business Analytics
- Predictive, Prescriptive, and Big Data Analytics
- How Big Data Enables Prescriptive Analytics
Engaging Stakeholders in Big Data Initiatives
- Stakeholder Influence and Buy-In Strategies
- Understanding Stakeholders in Big Data Contexts
- Principles for Securing Stakeholder Buy-In
- Presenting Analytics Insights to Decision-Makers
- The Gap Between Insight and Impact
- Principles of Effective Insight Presentation
- Visualisation and Storytelling
- Managing Uncertainty and Risk in Presentations
- 3 Creating Synergies in Business Analytics
- Combining Structured and Unstructured Data
- Understanding Data Diversity in Enterprises
- Why Combining Data Types Matters
- Analytical Approaches for Integration
- Integrated Analytics Use Cases
- From Departmental Insights to Enterprise Intelligence
- Customer Experience Analytics
- Risk and Compliance Analytics (BFSI Context)
- Operational Performance Analytics
- Strategic Value of Synergy
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