Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 21 hours
Course Outline
Overview of Data Analysis Methodologies
- Introduction to Python, R, Power Query, and Power BI
- Strategic applications of data analytics across public and private sectors
- Configuration of technical environments and toolsets
Data Sanitization and Structuring
- Utilizing Python frameworks (Pandas) for data refinement
- Executing data cleaning and transformation processes via Power Query
- Managing null values and data inconsistencies
Statistical Assessment using R
- Core statistical functions and data manipulation capabilities in R
- Conducting exploratory data assessments
- Formulating and interpreting statistical models
Data Consolidation and Processing
- Merging disparate datasets using Power Query
- Synthesizing Python and R analytical workflows within Power BI
- Maintaining data integrity and quality standards
Visual Representation of Data via Power BI
- Designing interactive dashboards and visual outputs
- Leveraging Power BI to detect trends and derive strategic insights
- Distribution and publication of analytical reports
Practical Applications and Sector-Specific Examples
- Examination of real-world analytical case studies
- Construction of workflows for typical operational scenarios
- Practical exercise to reinforce acquired knowledge
Concluding Review and Future Directions
Requirements
- Foundational knowledge of statistical principles
- Working proficiency with spreadsheet software and data entry procedures
- No previous programming expertise is necessary
Intended Audience
- Business analysts
- Data specialists
- Project managers
- Administrative personnel
Testimonials (2)
The most valuable takeaway was learning how to apply the concepts in real-world scenarios and understanding the tools and processes.
Marcel Tansae - DB Technology
Course - Microsoft Power Automate
How to use relationships in Power BIand the differences between columns and measurements