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Cutting through the Cacophony

(1) Data tells you what's happening (Analytics, Descriptive Data Science)
(2) Data Science tells you 'why' its happening (Predictive Data Science)
(3) Machine Learning/AI, NLP, Vision, Deep Learning lets you model it and do something about it. But it rarely tells you why its happening. (Prescriptive Data Science)

Corollary(s)

(1) Descriptive Data Science is just Analytics.
(2) And Prescriptive Data Science is just Machine Learning/AI, NLP, Vision, Deep Learning "Modelling" and its Applications/Solutions.

Visualization

... is used in
(1) Descriptive Data Science to 'Describe' 'it'
(2) Predictive Data Science to 'Predict' 'it'
(3) Prescriptive Data Science to 'Describe the Prescriptions'

Domain Knowledge

(1) Helps you model the domain. And should be only used for that.
(2) But for any Analysis, any preconceived canned analysis or experience utilised from Domain Knowledge - Completely and Absolutely Destroys the Utility, Sanctity and Purity of Data Science.

Data Engineering

Deals with Software, Storage and Computations to Process and Prepare Data.
It shouldn't limit Data Science or Visualisation in any way..

Guranteed Success!!!

Honesty is the secret sauce of our success with Data Science. Beyond which its upto our customers to decide and act.

If this works for you. We are always there to help. Remember to help us help you!