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Course Outline
Foundations of Data-Driven Thinking
- The role of data within an organization
- Data as support for operational and strategic decisions
- Data-driven vs. intuition-driven organizations
- Common pitfalls in data handling
2. Data sources and characteristics
- Transactional, operational, and reference data
- Internal and external data
- Structured and unstructured data
3. Data quality and its impact on decision-making
- Completeness, consistency, timeliness, and accuracy
- Typical data quality issues
- The impact of flawed data on analytical conclusions
4. Fundamental data analysis techniques
- Descriptive analysis
- Comparative analysis
- Trends and seasonality
- Data segmentation
5. KPIs and business metrics
- The distinction between a KPI and a metric
- Selecting the appropriate indicators
- The traps of KPI overload (excessive metrics)
Insights and Business Recommendations
- Interpreting analysis results
- Business context of data
- Distinguishing correlation from causation
- Identifying patterns and anomalies
2. Advanced analytical approaches
- Scenario analysis
- Root cause analysis (RCA)
- Inference based on incomplete data
3. Data visualization
- Principles of clear visualization
- Choosing the right format for the data type
- Common mistakes in presenting results
4. Formulating insights
- Defining a business insight
- From data to conclusion
- The structure of a logical insight
5. Data-Driven recommendations
- Bridging data with business context
- Risks and limitations of recommendations
- Communicating recommendations to decision-makers
Requirements
- Fundamental proficiency in Microsoft Excel or comparable spreadsheet software.
- Experience with business or operational reporting.
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Basic understanding of descriptive statistics is beneficial.
Target Audience
- Business and Systems Analysts.
- Consultants and Strategy Specialists.
- Managers and Team Leaders who rely on data-backed decisions.
- Reporting and Business Intelligence (BI) Specialists.
14 Hours
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the lessons