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Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.
10 spots per session maximum — 10 already taken
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Without mastery of data cartography, teams misinterpret spatial data in 68% of projects, according to Gartner, leading to flawed analyses that derail business intelligence initiatives.
This results in an average $750,000 annual loss per organization from poor spatial valorization, with 45% of data-driven decisions failing due to visualization errors.
Professionals and companies risk competitive obsolescence as rivals exploit geospatial insights to capture 20-30% more market share.
Every month without these skills, untapped spatial data remains dormant, amplifying financial vulnerabilities in an information-driven economy.
The Training Mastering Data Cartography to Analyze and Valorize Information training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.
The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.
To ensure the quality of the Training Mastering Data Cartography to Analyze and Valorize Information training, Learni provides the following teaching resources:
For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.
The assessment of skills acquired during the Training Mastering Data Cartography to Analyze and Valorize Information training is carried out through:
Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.
Learni training programs are available for inter-company and intra-company settings, both in-person and remote. Registration is possible up to 48 business hours before the start of training. Our programs are eligible for OPCO, Pôle emploi, and FNE-Formation funding. Contact us to discuss your training project and funding possibilities.
Discovery of geomatics, definition and history of data cartography, various use cases. Understand spatial data (vector and raster), sources and common formats (GeoJSON, Shapefile, geocoded CSV), concepts of projection and coordinate systems. Overview of mapping tools (QGIS, ArcGIS, Google Maps, web tools).
Preparing data for cartography: cleaning, structuring, geocoding. Using tools (Excel, QGIS, online software) to integrate datasets. Creating thematic maps, layer manipulation, and style management. Customizing symbols, colors, legends. Practical cases: creating heat maps or point maps, grouping by areas, thematic classification.
Spatial analysis methods: filtering, spatial join, aggregation, geoprocessing. Producing interactive web maps (Google My Maps, Leaflet, Datawrapper, Tableau). Best practices in cartographic storytelling for communication and decision-making. Presentation of real cases: geomarketing, urban planning, crisis management, data journalism. Final evaluation on a personal project.
12 participants max.
$3,812 / per person
3 days
remoteTarget audience
Data analysts, project managers, business intelligence professionals, anyone wishing to visualize and exploit spatial data
Prerequisites
Basic knowledge of office software and data handling (Excel, CSV)
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€1,155.001 day
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