Cascadia Analytics brings expert-level skills and a diverse toolbox to our projects.

R Ecosystem

  • Base R
  • Tidyverse (dplyr, purrr)
  • ETL / Data munging
  • ggplot2
  • Dashboards (Shiny, OpenCPU, flexdashboards, htmlwidgets)
  • Spatial packages (sp, rgdal/rgeos)

Machine Learning Techniques

  • Linear and Non-Linear Regression
  • Classification Models (Logistic Regression, Random Forest, SVM)
  • Factor / Cluster / Principal Component Analysis
  • Natural Language Processing

Software Engineering

  • Java / J2EE
  • Python
  • Javascript Frameworks (Node.js, jQuery, Angular)
  • Search (Lucene/Solr)
  • Integration/messaging (Apache Camel, Apache Karaf, Apache CXF)
  • Build/CI (Maven, Jenkins)

Databases and "Big Data" Technologies

  • SQL Databases (MySQL, Postgres, Oracle, Microsoft SQL Server)
  • No-SQL Databases (MongoDB)
  • Graph Databases (neo4j)
  • Apache Spark

Data Warehousing

  • Star Schema design and implementation
  • Pentaho stack (Kettle, Mondrian, Pentaho CTools)
  • ETL / Loading pipeline design and implementation

Docker Ecosystem

  • Docker image implementation
  • Microservices architecture
  • Docker networking and swarm/clustering