Total study time: 25 hours
What happens when you combine the power of Sparklyr, Tableau, and R in a single data-driven workflow? In this 1-on-1 course, you’ll learn how to extract insights from complex data—fast—and present them in visually impactful ways. With personal guidance, interactive online modules, and hands-on assignments, you’ll build essential skills that today’s data analysts use every day.
If you work with geospatial data or multiple data sources, you know how tricky it can be to bring everything together in a clear and meaningful way. That’s where Sparklyr, Tableau, and R come in—a smart, flexible combination built for serious data work.
With Sparklyr, you can easily merge data sources like satellite images and geographic files. It’s ideal for cleaning and preparing messy data so it’s ready for analysis.
Tableau helps you turn that cleaned data into interactive dashboards that make trends and patterns easy to see. These visuals are great for sharing insights with your team or clients.
R is a programming language used for deep statistical analysis. Whether you’re building predictions, spotting patterns, or classifying data, R gives you the power and flexibility to go deeper—especially when working with geospatial datasets.
Used together, these tools give you a complete, visually engaging workflow for making sense of complex data—even if you’re new to data analysis or coding.
In this blended learning course, you’ll build real, practical skills that you can apply right away in geospatial and data analysis projects. Step by step, you’ll learn how to prepare, process, and present data using both open-source and commercial tools.
You’ll begin with ESA SNAP for pre-processing satellite imagery, then move on to GRASS GIS, a powerful open-source tool for spatial analysis. These platforms help you clean and enhance raw geodata for further use.
Next, you’ll dive into the Semi-Automatic Classification Plugin (SCP) in QGIS—a free plugin created by Luca Congedo that helps you classify remote sensing images. From downloading satellite data to performing raster calculations, you’ll learn to build a complete workflow—even without a remote sensing background.
Then it’s time to combine and clean your data using Sparklyr. With a solid data foundation in place, you’ll use Tableau to create dashboards that clearly communicate your insights. Finally, in R, you’ll write your own scripts to analyze trends, build models, and uncover hidden patterns.
This course doesn’t just teach you tools—it helps you build a skillset that mirrors how professionals work. Whether you’re handling satellite data, spatial analysis, or big statistical datasets, you’ll gain confidence and competence across the board.
Blended learning gives you the best of both worlds—live interaction and flexible, self-paced study—so you can build job-ready skills on your own terms. In this course, you’ll learn how to turn raw, complex data into powerful visual stories using Sparklyr, Tableau, and R.
We start with a live session where you’ll get hands-on with real geospatial data. You’ll clean and structure datasets using Sparklyr and R, and see firsthand how Tableau brings them to life through interactive dashboards.
Then, move at your own pace through our step-by-step online modules. These cover the full process—from combining data with Sparklyr to building predictive models in R and designing dashboards in Tableau. You’ll also strengthen your understanding of statistical analysis and data storytelling along the way.
Later in the course, we’ll reconnect for a second live session. You’ll apply everything you’ve learned to a realistic project, troubleshoot challenges, and get personal feedback to sharpen your final result.
One of the biggest strengths of this course is its real-world, case-based approach. You won’t just learn each tool—you’ll use them together in a complete workflow that mirrors real projects.
By combining expert instruction with hands-on practice, this course prepares you to confidently handle data from end to end. You’ll leave with the skills to prepare, analyze, and visualize data—and the confidence to make smarter decisions with it.
After completing this course, you’ll be able to:
Do you have questions about the course content? Not sure if the course aligns with your learning objectives? Or would you prefer a private session or in-company training? We’re happy to assist—feel free to get in touch.
We aim to make our courses accessible to as many people as possible. If the course fee is a concern, instead of registering directly, you can indicate on the registration form that you’d like to receive a quote tailored to your needs. In many cases, we can offer flexible solutions. For instance, we can adjust the course content for large groups, shorten the course based on existing knowledge, or offer daily rates to suit your requirements.
Yes, you can reach out to the instructor with questions for up to 2 weeks after the course. Since the instructor is likely teaching other courses, we recommend emailing your questions to info@geo-ict.com. We’ll forward your inquiry to the instructor, and you’ll receive a response within 24 hours. After the 2-week period, we recommend using our Personalized Online Support for continued assistance.
Yes, we offer on-site training regularly throughout the Netherlands. Our instructor will bring laptops for the participants, and all you need to do is arrange a suitable room at your location.
Please send your requirements to info@geo-ict.com, and we will provide a customized quote, which will include travel and accommodation costs. Once the quote is confirmed, our course coordinator will reach out to schedule the training days.
After each course, participants receive a link to our evaluation portal where you can share your feedback on what you liked and didn’t like. We strive to provide a great experience for all our participants, but if you have a complaint, please click on ‘Complaints Procedure’ in the portal. This document will guide you through the steps to take. Geo-ICT Training Center, Netherlands, is a member of the Dutch Council for Training and Education (NRTO), ensuring a fair and transparent process.
Courses are typically scheduled according to the Dutch time zone, with sessions running from 9:00 AM to 12:00 PM and 1:00 PM to 4:00 PM. For participants in different time zones, we adjust the course times in consultation with you.