Data Wrangling
Reliable pipelines, schema validation, and scalable transformations that keep downstream analytics honest.
Spatial Intelligence • Analytics • Data Systems
Spatialitix
We are a world-class analytics and geospatial company. We build trusted pipelines, decision-ready intelligence, and products teams can use immediately.
Key metrics
4+
Years applied experience
25+
Pipelines & apps shipped
100%
Reproducible, documented
End‑to‑end
Ingest, model, visualize
Capabilities
What we do, end‑to‑end
Four pillars that turn noisy, scattered information into decisions your team can defend.
Analytics & Modeling
Reproducible analysis, hypothesis testing, and statistical models that move the KPIs leadership actually watches.
Geospatial & GIS
From TIGER roads to wildfire risk — we build spatial workflows in Earth Engine, ArcGIS, and Mapbox that answer where and why.
Visualization
Dashboards, Shiny apps, Quarto reports, and publication-ready charts that make complex findings feel obvious.
In Practice
Three moves we make on every engagement
Scroll each act to watch the before / after.
raw — before
| id | gender | age | weight |
|---|---|---|---|
| NA | "female" | "twenty-two" | NA |
| 34 | "M" | 34 | 78.2 |
| 999 | "male" | -7 | NA |
| 29 | "female" | 29 | 65.1 |
| NA | "male" | 41 | 9999 |
| 51 | "female" | 51 | 72.4 |
| -1 | "FEMALE" | NA | 61.8 |
| 38 | "male" | 38 | NA |
analysis-ready — after
| id | sex | age | weight | |
|---|---|---|---|---|
| 42 | F | 22 | 68.4 | imputed |
| 34 | M | 34 | 78.2 | |
| — | — | — | — | dropped · outlier |
| 29 | F | 29 | 65.1 | |
| 42 | M | 41 | — | dropped · outlier |
| 51 | F | 51 | 72.4 | |
| — | F | 46 | 61.8 | imputed |
| 38 | M | 38 | 68.4 | imputed |
brittle scripts — before
01_load.R Error in read.csv
setwd("C:/Users/dan/Desktop") · no one else can run this
cleaning FINAL.R object not found
depends on df_raw from a different session · never saved
model_v4_USE THIS.R package missing
library() calls buried mid-script · order matters
make_plots.R never reached
upstream failure · output files missing
reproducible pipeline — after
R/01_ingest.R ✓
here::here() paths · schema validated on load
R/02_clean.R ✓
pure functions · testthat coverage · logged
R/03_model.R ✓
set.seed() · renv.lock · targets DAG
R/04_visualize.R ✓
ggsave() · deterministic · quarto report
ggplot2 defaults
theme_custom()
and so much more.
Selected Work
Things we've built, shipped, and published
Interactive apps, open geospatial datasets, and reproducible analyses — live and in the wild.
Quick Plot
An accessible Shiny app for wrangling, analyzing, and visualizing tabular data — drop in a CSV, ship a chart. (opens in a new tab)
MapLab
Simple GIS environment built for non-GIS users who still need strong map interaction and layer-based exploration. (opens in a new tab)
Map Explorer
Gallery of interactive maps for ecoregions, counties, and other spatial layers designed for exploratory browsing. (opens in a new tab)
US Wildfire Risk
An interactive analysis of wildfire risk in the wildland-urban interface — suppression cost, structural damage, fatalities. (opens in a new tab)
TIGER Roads on GEE
Processed the US Census TIGER road network and published it to the Google Earth Engine community catalog for open, planetary-scale analysis. (opens in a new tab)
WUI Wildfire Explorer
Map-first app for exploring wildfire risk dynamics at the wildland-urban interface across regions and seasons. (opens in a new tab)
Stack
Skills & tools we use daily
The technical stack, organized by domain.
Languages
- R
- Python
- SQL
- JavaScript
- Bash
- HTML
- CSS
- Markdown
- LaTeX
Analytics & Stats
- Regression
- GLM / GAM
- Mixed models
- Time series
- Forecasting
- ANOVA / MANOVA
- PCA
- Clustering
- Bootstrapping
- Maximum likelihood
- Hypothesis testing
Geospatial & GIS
- Google Earth Engine
- ArcGIS / ESRI
- Mapbox
- MapLibre
- Leaflet
- OSM
- GDAL
- GeoPandas
- Spatial analysis
- Geoprocessing
Visualization & Apps
- Shiny
- ggplot2
- Quarto
- Jupyter
Data Engineering
- Tidyverse
- NumPy / Pandas
- Git / GitHub
- renv / targets
- Data wrangling
- Pipeline design
- Schema validation
Why Spatialitix
Why us
Not a consultant who hands you a slide deck — an operator who hands you the pipeline, the repo, and the docs.
Decision-ready narratives
We don't just crunch numbers — we translate them into the two or three sentences an executive needs to make the call.
Reproducible by default
Every analysis lands as a versioned repo: locked dependencies, tested functions, and a README your team can run from a cold start.
Geospatial fluency
Planet-scale raster, national vector, urban analytics — we've shipped against all of them and published open datasets to prove it.
Autonomy, not babysitting
We scope, communicate, unblock quickly, and surface tradeoffs early. You get a teammate, not another ticket in your queue.
About
About Spatialitix
Spatialitix is led by Noah Weidig, Founder of Spatialitix and geospatial data expert, helping organizations turn complex data into confident decisions.
Noah combines statistical rigor, spatial reasoning, and production-grade delivery so teams can trust every output, map, and recommendation.
Let's work
Got a data problem worth solving?
One email. Plain English. We'll tell you whether we're the right fit — and if we're not, who is.