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Course Outline

1. From Data to Business Decisions
• The role of data analysis in decision-making
• From business questions to indicators and KPIs
• Raw data, information, and insight
• Stages of the data analysis process
• Tools used in the course: Power Query, Data Model, Power Pivot, and DAX

2. Preparing Data for Analysis
• Importing data from different sources
• Identifying data quality issues
• Cleaning and transforming data
• Combining and restructuring datasets
• Automating the data preparation and refresh process with Power Query

3. Organising and Modelling Data
• Why a single table is not always sufficient
• Organising data for analysis
• Creating the data model
• Relationships between tables
• Basic principles for building a clear and efficient model

4. Data Analysis with Power Pivot and DAX
• Using Power Pivot for data analysis
• Selecting relevant indicators for the analysed question
• Calculated columns and measures
• Understanding filter context
• Essential DAX functions for business analysis
• Calculating indicators and KPIs

5. Building a Dashboard for Decisions
• From analysis to dashboard
• Choosing the right visualisation for the analysed information
• Organising information and visual hierarchy
• Dashboard layout and logical structuring
• Adding context: evolution, targets, comparisons, and benchmark values
• Interactive dashboards and automatic refresh
• Interpreting results and formulating business conclusions

Requirements

This course is designed for:

  • Business users who work with operational reports and data.
  • Team Leaders and managers involved in the decision-making process.
  • Specialists from Financial, Human Resources, Sales, Operations, Procurement, and Support departments.
  • Professionals who need to interpret, analyse, and communicate data-based information.
  • Users without technical training who wish to develop their data analysis skills.

Recommended Prerequisites

  • Basic knowledge of using Microsoft Excel.
  • Experience working with tables, reports, or business data.
  • No programming knowledge is required.
 14 Hours

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