A catechesis is the systematic practice of teaching and, in this case, that teaching is about data science. While there are no formal catechisms (questions to invoke reflection and response) in the field of science to draw upon, we can nevertheless begin to compose some of the more important expositions of existing doctrine to as a start.
The first pillar is composed of three of the essential elements that form data economics:
No. 1: Data is the energy source of business transformation.
Question: Why is data the fundamental energy source of transformation and not people, processes, or technology?
Question: What does transformation mean and why is it the basis of value?
No. 2: Data Science is the organic and systematic practice of transforming hypotheses and data into actionable predictions
Question: What does it mean that data science is both organic and systemic?
Question: Why are hypotheses an important part of the process of data science?
Question: Why do predictions need to be actionable and whom should they act upon?
No. 3: A Data Scientist is a person who is better at mathematics and statistics than any software engineer and better at software engineering than any mathemician or statistician.
Question: What kind of mathematics and statistics is important in the discovery of revelations in data?
Question: What are the necessary elements of software engineer needed to systematically produce actionable predictions?
Question: What programming languages does a data scientist need to know?
This is just a start, so please reply with your reflections and other relevant questions for this first pillar.