Course Outline
- Introduction: The Power of Data in Decision Making
- Importance of data-driven decision-making in modern businesses.
- Real-world examples of how data has transformed organizations.
- Ensuring Data Integrity: Trusting Your Data
- Definition of data integrity and why it's crucial.
- Factors affecting data integrity: accuracy, consistency, and timeliness.
- Steps to ensure and validate the credibility of data.
- Real-life consequences of decisions made on non-credible data.
- The Art and Science of Data Interpretation
- Introduction to Key Performance Indicators (KPIs): Definition and significance.
- Reading and understanding different types of graphs and charts.
- Identifying trends, patterns, and outliers in datasets.
- Practical exercises: Interpreting sample graphs and charts.
- Recording Performance Data: Starting from Scratch
- The need for recording data: Gap identification in the absence of data.
- Steps to begin recording data in departments.
- Deciding what metrics to record.
- Methods and tools for data recording.
- Ensuring consistency and standardization in the recording process.
- Data Storytelling: Turning Numbers into Narratives
- The importance of data storytelling in business communication.
- Basic data analysis techniques for effective storytelling.
- Overview of data visualization techniques: Using visuals to enhance your story.
- Case studies: Good and bad examples of data storytelling.
- Understanding KPIs: Leading vs. Lagging Indicators
- Definition and differences between leading and lagging KPIs.
- Benefits and limitations of each type of KPI.
- How to select the right KPI for your business objective.
- Examples of leading and lagging KPIs across various industries.
- Workshop: Aligning business goals with relevant KPIs.
- Course Wrap-up and Final Thoughts
- The integration of data in daily business processes.
- Encouraging a culture of data-driven decision making.
- Continuous learning and staying updated with data trends and technologies.
- Assessment/Feedback
- Short quiz to test knowledge retention.
- Feedback form to gauge course effectiveness and gather suggestions for improvement
Testimonials (5)
Hands-on examples allowed us to get an actual feel for how the program works. Good explanations and integration of theoretical concepts and how they relate to practical applications.
Ian - Archeoworks Inc.
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Tse Kiat - ST Engineering Training & Simulation Systems Pte. Ltd.
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All the topics which he covered including examples. And also explained how they are helpful in our daily job.
madduri madduri - Boskalis Singapore Pte Ltd
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I liked Pablo's style, the fact that he covered a lot of subjects from report design , customization with html to implementing simple ML algortithms. Good balance theoretical information / exercices. Pablo really covered all topics i was interested in and gave comprehensive answers to my questions.
Cristian Tudose - SC Automobile Dacia SA
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