Industrial revolution design principles lessons for commercial advanced analytics
New tools and methodologies show up every day, so how can your analytics team stay vigilant? A thought on the 4 pillars of the industrial revolutions: standardization, modularization, automation, and scalability
Throughout history, we have gone through three industrial revolutions, and many believe that we are currently experiencing the 4th. From the 1st revolution with coal and steam; the 2nd with mass production, the 3rd with computers to the latest 4th with artificial intelligence and internet-of-things, there are many lessons that humanity learned with sweats and tears, some times even with blood [1]. As “Industry 4.0” is around the corner, adapting previous lessons and best practices into daily works would be crucial not only for us as individuals but also for organizations.
For many people in the commercial advanced analytics field, “industry 4.0” can be simplified as the process of pooling data from various sources into a warehouse or a data lake, then deploy the necessary analytics, artificial intelligence, machine learning to generate actionable insights. That being said, the other part of the job of any analytics-related team would be preparing documentation, onboarding colleagues, securing supports as well as dealing with stakeholders.
In this article, I will discuss my ideas on the concepts of 4 industrial revolution design principles: standardization, modularization, automation, and scalability; how related they are, and how to integrate them into our daily works in any analytics organizations.
Table of contents
Standardization
Modularization
Automation
Scalability
Standardization
What is it?
Standardization, by meaning, is the process of making something conform to a standard. In technical terms, it means implementing and developing standards based on the consensus of different parties (e.g: firms, users, interest groups…
