Hi, I’m Cliff Weaver with a passion for improving existing businesses and discovering new opportunities using a pragmatic approach to business design and using data as a guiding hand in delivering salable technology solutions that are eagerly consumed by internal and external customers.

I have a long employment history where I have enjoyed many exciting and satisfying opportunities in defense aerospace, IT, consulting, healthcare, and data science.

If you are interested in my work history, you can find it on LinkedIn and on my most recent website.

Data has been a constant theme in my professional life - well before the 20212 HBR Article Data Scientist: The Sexiest Job of the 21st Century. My recognition that data can serve as a tool alongside human experience and expertise stated in the mid 1980’s when such efforts fell under the term enterprise information systems (EIS).

While data science continues the maintain its prominence today, I believe a more accurate term for the role and profession is business science. After all, isn’t what we do is to solve business problems using data as one tool in the overall tool set for problem solving?

What is this site?

This site was built using Quarto - an open-source scientific and technical publishing system built on Pandoc. The product is built by Posit, the same company that publishes popular tools supporting the R Programming language.

Quarto brings all the rich documentation publishing richness enjoyed for years by R data scientists and data analysts using RMarkdown to more developers. For example that rather plain and boring Python Notebook format can now be transformed into something engaging - a document business customer will embrace! Quarto can:

  • Create dynamic content with Python, R, Julia, and Observable.
  • Author documents as plain text markdown or Jupyter notebooks.
  • Publish high-quality articles, reports, presentations, websites, blogs, and books in HTML, PDF, MS Word, ePub, and more.
  • Author with scientific markdown, including equations, citations, crossrefs, figure panels, callouts, advanced layout, and more.

This site provides access to an array of documents. Most were originally written in RMarkdown but presented here in Quarto format. Others were written in Python Notebooks and also transformed in Quarto format. (The transformation process is super simple and fast.) The content includes a variety of subjects:

  • Data Analysis
  • Data Visualization & Storytelling
  • Machine learning
  • Statistics
  • Miscellaneous Discussions

I hope you find these documents useful in your pursuit of business science excellence.