After looking for a job for months, I finally got my first job. It wasn’t what I expected. Even though I’d been learning on my own for a while, I never thought I’d start as a trainer. But that’s exactly what happened.
I had the chance to lead my first training session on using R for data and Power BI for showing it. It was a big step for me. I was a little nervous, but I felt good about my skills in R and Power BI because I had used them a lot. This special course is a main part of what In-depth Research Institute offers, the company that hired me for this two-week training.
What made this experience unique was how personal it was. In-depth Research Institute (IRES) focuses on very detailed, one-on-one training, different from college classes. It was super personalized, with just one student for two intensive weeks.
In this article, I’ll explain more about the course and what I learned from my first training.
What the Course Was About: Becoming a Data Expert
The “Data Manipulation with R and Visualization with Power BI” course from In-depth Research Institute is designed to give data professionals all the tools they need. It teaches them how to get data ready and then create clear visuals to help make smart business decisions. This training is different because it covers everything.
The course has two main parts:
- Using R for Data: This part teaches important skills for cleaning, changing, and preparing even messy data using the powerful R programming language. We focused on making sure the work could be checked and repeated. We learned to use dplyr for tasks like picking out specific data, filtering, summarizing, and joining different data sets. We also spent time on ggplot2 to make professional and clear graphs that tell a data story.
- Analyzing and Showing Data with Microsoft Power BI: This second part moves to Microsoft’s main business intelligence tool. It covers the whole Power BI process, from connecting to different data sources (like Excel files, databases, and online sources) to cleaning and managing data using Power Query. Students also learn about data modeling with DAX (Data Analysis Expressions) to create detailed calculations. Then, they learn to make custom data visuals and reports using Power View. By the end, they can build, share, and manage interactive dashboards.
After finishing the program, students can connect to data, change it, build models, show it, and share their data insights within their organizations.
What I Did: Teaching One-on-One for Two Weeks
With only one dedicated student, my teaching became a close, one-on-one guide for the whole two weeks. This long and focused time was really helpful because it let me truly understand their learning needs, style, and what they already knew. This helped me adjust every explanation, example, and practice exercise so they could learn and remember the most. This was truly personalized data analysis training.
Here’s how I led them through the course:
Building a Strong Base in R
At the start, we built a strong and flexible foundation in R. This wasn’t just about learning commands; it was about learning how to do research that others could easily check and repeat. I showed them how R scripts make every step of data cleaning, changing, and analysis clear and repeatable, which is key for good analytical work. Then we covered:
- Understanding Tidy Data: I focused on why tidy data is so important for good analysis, not just what it looks like. This clear understanding is crucial.
- Smooth Workflows with “Piping”: I showed how to link many commands together using R’s powerful piping tool. This made our data tasks with dplyr logical, easy to read, and very efficient. We worked through many real-world examples of filtering rows, selecting columns, making summaries, and joining different data sets, making sure the student could confidently get any raw data ready.
- Making Advanced Visuals with ggplot2: This part was exciting. I taught them more than just how to make basic charts; I taught them the main “grammar of graphics.” This powerful approach lets users create any graph by understanding its basic parts – like axes, colors, shapes, and different sections. We went from simple charts to making complex, professional visuals that clearly told a data’s story.
Using Power BI for Business Insights
Once they had a strong base in R for preparing data, we moved smoothly to Power BI, focusing on its power for business intelligence. My approach was always practical and hands-on, following the goals of In-depth Research Institute’s course:
- Understanding ETL with Power Query: I guided the student through the whole Extract, Transform, Load process, focusing on Power BI’s easy-to-use Power Query Editor. We spent a lot of time on common, real-world data cleaning problems. This included using first rows as headers, renaming fields, replacing data, changing data types, reordering columns, and more advanced changes like un-pivoting columns, grouping, splitting columns, and pulling out specific features. I explained why each change was made, helping them fix their own complex data issues.
- Mastering Data Modeling and DAX: This is where the advanced power of Power BI really comes alive. I guided them through setting up correct table relationships and introduced them to DAX (Data Analysis Expressions). We actively created custom calculations and new columns, helping them go beyond simple totals to find complex, business-specific insights from their data.
- Making Strong Visuals (Power View): We explored Power BI’s many different visuals. My main focus wasn’t just how to drag and drop charts, but when to use each one – understanding which visual best shows trends, distributions, comparisons, or parts of a whole. We refined visuals using interactive options for maximum clarity, covering everything from bar charts to line charts, KPIs, and even advanced maps.
- Building and Sharing Useful Dashboards: The final goal was to create truly helpful and working dashboards. I showed them how to organize their data in Power BI, publish reports, and then build interactive dashboards that could be easily shared with others. We also covered important topics for companies, like setting up security to control who sees what data, and setting up automatic data refreshes, which are key for keeping data accurate and available.
- Mobile and Excel Connection: Finally, I showed how Power BI works on mobile devices for insights on the go, and how it connects smoothly with Excel, allowing for better analysis and reporting for those who like spreadsheets. This full training made sure they were ready for real-world tasks.
The Result: A Confident Data Professional Ready to Make an Impact
This personalized, two-week training in Kenya was a special chance to dive deep into ideas, practice hands-on, and get immediate answers to any questions. This level of focus is hard to achieve in bigger groups. By the end of our intense program, the student gained:
- Strong, Useful Skills: They are now good at using R for careful, repeatable data work and Power BI for creating dynamic, interactive dashboards and reports. This double skill set makes them very flexible and valuable in any job with a lot of data.
- Confidence in Solving Problems: Beyond just knowing how to use the tools, they learned how to approach raw, often messy data, understand its challenges, and then confidently use the right techniques in both R and Power BI to clean, change, analyze, and understand it on their own.
- The Art of Telling Stories with Data: They learned not just to make charts or tables, but to create strong stories with data, using the right visuals and insights to explain complex information clearly and convincingly to any audience.
- Being Self-Sufficient in Business Intelligence: By the end of the two weeks, they were fully ready to connect to different data sources, do complex transformations, build strong data models, create insightful visuals, and ultimately, confidently drive data-based decisions within their organization from start to finish.
My Own Growth: What I Learned from My First Training
Beyond the great feeling of seeing my student succeed, my first training job with In-depth Research Institute was a huge learning experience for me personally. It wasn’t just about teaching; it was about getting better at being an educator.
- Better Teaching Skills: Working one-on-one helped me improve my ability to explain complex technical ideas in many ways, changing my teaching style on the spot to fit the student’s understanding. It made me better at listening and solving problems during live sessions.
- Deeper Knowledge of the Subject: While I had researched the topics a lot, teaching them made me think about every idea from a student’s point of view. Remember, the student was a beginner who had never used R before. Explaining each step, guessing what questions they might have, and guiding hands-on exercises made my own understanding of R and Power BI even stronger.
- Improved Training Materials: The direct feedback and unique questions from a single student helped me find areas where explanations could be clearer, exercises more challenging, or examples more relevant. This valuable insight will directly help me make my future training materials better.
- Proof of My Passion: This experience clearly showed me my passion for teaching and helping others learn data skills. Seeing the “aha!” moments and the clear progress of my student was incredibly rewarding and has made me committed to a career in data education.
Conclusion
Leading my first training, especially in such a focused, one-on-one setting provided by In-depth Research Institute, was an incredibly rewarding experience. Seeing someone go from feeling overwhelmed by data to confidently using powerful analytical tools was truly inspiring. It strongly confirmed my belief in how much good, personalized, and practical data analysis training can do for professionals who want to do well in data jobs.
Overall, it was a truly rewarding experience that brought me into the world of being a corporate trainer. This was the first of many trainings I would lead.