* All fees are exclusive of vat ** PREMIUM - Customize your learning experience
Successful organisations are ones that communicate effectively. Business reports and communications should be clear, concise and free of ambiguity. This course will help you develop business writing skills that convey a targeted message and project a professional image using data. The course will emphasize applications of data analytics in management practice; focus on the valid interpretation of data analytics findings; and create a clearer understanding of how to integrate quantitative reasoning into management and business reporting.
What Do Participants Learn?
Appreciate data analytics in a decision support role
Explain the scope and structure of data analytics
Apply a cross-section of useful data analytics
Interpret meaningfully and critically assess statistical evidence
Who Should Attend?
IT Support Staff
Any member of an the team responsible for reporting and IT
What Will the Learning Experience Include?
Comprehensive pre-program activities include:
Web-based information forms & surveys completed by attendee.
Direct consultation with the attendee about the expectations.
During the training, participants engage in data, activities, and conversations that lead to insight and knowledge.
Participants learn from expert trainers who have both academic and business experiences.
Highly applicable training content & instructive activities for adding depth to training topics.
**A half-day site visit for integrating the experience & plan next steps. Opportunities to provide connections, ideas & support.
Explore & Practice
Apply & sustain the learning experience by using this ongoing support:
To ensure participant has new skills or behavior progress.
Optional, fee-based mentoring & coaching with the trainer.
Training materials & additional documents (e-books, pdf files, presentations and articles)
Evaluate your training experience by giving us feedbacks and help us to reach our organizational goals.
The quantitative landscape in management
Thinking statistically about applications in management (identifying KPIs)
The integrative elements of data analytics
Data: The raw material of data analytics (types, quality and data preparation)
Exploratory data analysis using excel (pivot tables)
Using summary tables and visual displays to profile sample data