Top 10 Things for IT Professionals

These IT related lists are really quite accurate. I sound like a broken record sometimes when I repeat these things. The articles provides very good detailed descriptions, I’ve included the bullet points just to temp you to read more.

Top ten things ten years of professional software development has taught me.

  1. Object orientation is much harder than you think
  2. The difficult part of software development is communication
  3. Learn to say no
  4. If everything is equally important, then nothing is important
  5. Don’t over-think a problem
  6. Dive really deep into something, but don’t get hung up
  7. Learn about the other parts of the software development machine
  8. Your colleagues are your best teachers
  9. It all comes down to working software
  10. Some people are assholes

The Top 10 Things They Never Taught Me in Design School.

  1. Talent is one-third of the success equation.
  2. 95 percent of any creative profession is shit work
  3. If everything is equally important, then nothing is very important.
  4. Don’t over-think a problem.
  5. Start with what you know; then remove the unknowns.
  6. Don’t forget your goal.
  7. When you throw your weight around, you usually fall off balance.
  8. The road to hell is paved with good intentions; or, no good deed goes unpunished.
  9. It all comes down to output.
  10. The rest of the world counts.
Tagged with: General

Producing Skewness statistics with SQL

Skewness measures the asymmetry of a distribution. A perfectly symmetric distribution has a skewness of zero. A positive skew (right-skewed) means the tail extends to the right — a small number of high values pull the mean above the median.

Exploring the vsql-ai extension

The vsql-ai extension adds AI prompt capabilities and text embeddings directly in SQL queries, with support for Anthropic Claude , Google Gemini , OpenAI ChatGPT , or a local LLM such as Ollama .

Producing Chi-Squared statistics with SQL

The Chi-Squared test is one of the most widely used statistical tests for categorical data. It comes in two flavors: the goodness-of-fit test asks whether an observed frequency distribution matches an expected one, while the test of independence asks whether two categorical variables are associated with each other.