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Data science

Data science is using data, statistics and code to answer questions and make predictions, like which customers are about to cancel or how much a store will sell next month.

Select any words here to ask your Maestro about them.

Two models predict which of 1,000 customers will cancel; 50 of them do. Model A is right 95.5% of the time, Model B 91%. Which one finds more of the 50?

Two models tested on the same 1,000 customers. Example data.

What data scientists do: turn a business question into one data can answer, gather and clean the data with SQL or Python, explore it, build and test machine learning models when they help, and explain the result so someone can act on it.

Data science or data analytics: data analytics mostly explains what happened and why; data science adds predicting what will happen and building models that do it on their own. In many jobs the two overlap.

What you need to start: SQL to get the data, Python to analyze it, statistics to know when a difference is real, and enough of the business to ask good questions.

How it's used

A project, start to finish

Predicting cancellations

  1. The question: which customers will cancel next month, so the team can call them first
  2. The data: a year of usage, plans and support tickets, pulled with SQL
  3. marked: The model: trained on last year's customers, tested on ones it never sawTesting on new customers is what tells you how it will do for real.
  4. The result: a weekly list of the 100 customers most likely to cancel
The model is one step out of four. Most of the value comes from asking the right question and getting the result to someone who acts on it.

When to look closer

Great in testing, useless live

A model too good to be true

  1. Columns: plan, logins last month, support tickets and cancellation reason
  2. marked: Accuracy in testing: 99%

Your churn model is 99% accurate in testing but useless live. Which of its four columns is the problem, and why?

Ask your Maestro about Data science

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You: What does "Data science" mean, in plain words?

Your Maestro: I'll explain it with a case of yours: it sticks better than a definition. What would you like to be able to predict at work?

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Related terms

  • Machine learning

    Machine learning has a program learn rules from examples that come with answers, instead of someone writing them, so it can predict new cases.

  • Data analytics

    Data analytics is the work of turning data into answers: asking a question, cleaning the data, running the numbers, and explaining what happened, why, and what to do next.

  • Python

    Python is a free programming language with short, readable code. People use it to clean and analyze data, make charts, automate tasks and build AI agents.

  • SQL

    SQL is the language for asking a database for data: which columns, from which table, which rows and how to summarize them. You get a table back.

The whole glossary