Why Datellx Exists
Data modeling should be accessible to every student. Here's the evidence showing why no-code education is urgently needed.
The Skills Gap Crisis
Demand for data skills is exploding, but traditional education puts coding barriers in the way
Degree Programs Exploding
Data science degrees jumped from 84 students (2020) to 897 students (2022) in just 2 years
Source: Inside Higher Ed (2024)
Jobs Growing Fast
Government predicts 36% more data science jobs needed by 2030 - much faster than most jobs
Source: U.S. Bureau of Labor Statistics
Skills Gap Crisis
Only 11 out of 100 workers feel confident using data - but 58 out of 100 know they need these skills
Source: Qlik Data Literacy Report
The Coding Barrier Problem
Students struggle with syntax when they should be learning concepts
Traditional Approach
Coding Prerequisites
Students must learn Python/R before understanding models
Syntax Overload
Focus shifts from concepts to debugging code
Excludes Non-Coders
Biology, business, social science majors are shut out
"Many professors advise against [teaching coding] in intro data science for non-majors, considering it a distraction from important statistical topics."
— Mukherjee & Bien (2024), arXiv:2401.17647
Datellx Approach
No-Code Interface
Visual drag-and-drop modeling without programming
Concept-Focused
Students learn how models work, not syntax
Inclusive for All Majors
Biology, business, social science students can participate
"With the no-code approach, I got the opportunity to try experiments... I could focus on the problem I wanted to solve... I think I learned more about AI... and that is without any code."
— Student from Umeå University Study (JISE 2024)
2.2M+
Students take statistics/data courses annually
17%
K-12 teachers trained to use data in instruction
89%
Improvement in student engagement with no-code tools
Research-Backed Solution
Academic studies prove no-code platforms improve learning outcomes
Umeå University Study
Students from diverse backgrounds (business, behavioral science, CS) successfully completed full ML workflows:
- Data collection & preprocessing
- Model training & evaluation
- Deeper understanding of the process
Results showed students could focus on problem-solving and concepts rather than getting stuck on programming syntax.
Source: Journal of Information Systems Education (JISE), Vol 35, 2024
Key Learning Outcomes
Experiential Learning
Students experiment with real modeling techniques without code barriers
Conceptual Understanding
Learners see how changing inputs affects outcomes
Higher Engagement
Greater confidence and enthusiasm for AI/ML when they can actually experiment
The Market Opportunity
Datellx addresses a critical gap in data science education
High Schools
K-12 schools need tools to introduce data science without technical prerequisites. Only 17% of teachers have data science training.
23,000+
Public High Schools in US
~15M high school students
Source: National Center for Education Statistics
Undergraduate Non-CS
Business, biology, psychology, economics departments need accessible analytics tools for their majors.
2.2M+
Students Taking Data Courses
Each year in the US
Source: National Center for Education Statistics
New Data Science Programs
Colleges launched 897 new data science degree programs/courses in 2022 alone - showing huge demand for these skills.
897
New Programs Launched (2022)
New courses & degrees added
Source: Inside Higher Ed (2024)
The Solution Is Clear
Datellx removes coding barriers so students can focus on learning data modeling concepts and making data-driven decisions.