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Predictive Business Analytics Training

Courses Overview

This Predictive Business Analysis training is part of the initiative ‘’Digital Skills for Business Resilience in the EAC’’ under the Digital Skills for an Innovative East African Industry (dSkills@EA) project with the aim to support digital skills development for business resilience in times of COVID-19.

The dSkills@EA project is part of the technical development cooperation between the East African Community and the German Government, which aims to strengthen the employment and innovation-related digital skills of youth in the EAC and support the industry’s and society’s digital transformation.

The project is implemented by the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ), the Inter-University Council for East Africa (IUCEA) and the German Academic Exchange Service (DAAD) together with an East African-German academic consortium that forms part of the Centre of Excellence for ICT in East Africa (CENIT@EA).

  • Data Analysis Fundamentals using Excel

Create an Excel report, table, pivot table and chart, dashboard and analyse data, hierarchies, data model and connect to external data.

  • Analysing Data with Excel

Explore and extend a classic Excel dashboard, data model pre-format and import a .CSV file, Import data from a SQL Server database, data from a report. Create measures using advanced DAX functions, data visualizations in Excel and Power BI dashboard with Excel.

  • Analysing Data with Power BI

Ingest, clean, and transform data, model data for performance and scalability, design and create reports for data analysis, apply and perform advanced report analytics, manage, and share report assets and create paginated reports in Power BI.

  • Have a degree/ diploma in business information system/ computer science or in statistics.
  • Be an employee of a company in one of the EAC Partner states (Burundi, Kenya, Rwanda, and South Sudan, Tanzania, Uganda).
  • Have at least 3 years work experience.
  • Female candidates are strongly encouraged to apply.
  • All applications must be submitted by the 24th of March 2022.