The Data Lake and Data Pool are dirty, beware.
Wonder why it requires so much cleaning in order to become useful in Data Analytics?
It has been estimated that 70 to 90% of time is spent on cleaning dirty Data?
Maybe there is a market for an embedded Data cleaning agent?
Design Build Data may be an area for Design And Systems Thinking.
Structured, Semi-Structured and Un-Structured Data describe a spectrum of architectural solutions for the way data is design to fit together.
For the first time I looked at the city with all the buildings and began to visualize the similarity with data architecture!
Data is not something that we see everyday, yet for data to become useful, some architecture is required.
Design Build Data
Is the common point of entry to data science: modeling, simulation, analysis, and optimization actually the API development, instead of the GUI?