Welcome to Decision Data

It was only two years after I graduated that I noticed an emergence of formal data science degrees. By then, I had already tutored a data mining class, completed two data analyst internships, and began full-time data analyst work. There is a part of me that wishes these data science degrees had emerged much sooner. Still, that early period of observation, exploration, perspiration and making juvenile mistakes (which I still make) was crucial to the development of my intuition.

Yes, “intuition” — that confusing concept describing how we approach and make decisions from our data. Developed individually through years of trial and error and reinforced by our various backgrounds and experiences, it seems that what we perceive to be “common sense” may not be that common.

Whilst there might be a plethora of ingestible materials out there, I am yet to find one dedicated to reducing decision fatigue — especially for all the budding data scientists whose first instincts are to “try everything and see what works”.

In my journey, I have learned that I make better decisions about which path is appropriate when I understand the properties of the data space, as it echoes the rulesets behind mathematical and statistical concepts. This blog aims to share what I have learnt in establishing my decision-making processes with all developing analysts.

Welcome to Decision Data.

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