Were you always curious to find out what happens during the first week at Data School?

 

 

The Beginning: The Offer
Ever since I was made an offer to take part in Data School, I have been really excited about starting a great career journey.
For me personally, it was an achievement as I have pivoted from media. After 3.5 years, I wanted something different and Covid allowed me to take a small break. I took this as an opportunity to upskill myself in data analytics and help out my family’s restaurant. I was really ecstatic for August the 2nd, my first day at Data School. And now with the chance to start fresh in a growing industry from the ground up.

The Initial Glance
For me, the first day at Data School was a memorable day, for I have never started a new job online and at home. And being at home does have its technical challenges and the Data School team have tried their best to accommodate and streamline the induction process as much as possible, and it could not have been any smoother. It was great to hear and learn about MIP, the Data School program, the history, culture and values. More importantly, not only was it great to meet my fellow cohort, but it was also a pleasure to experience meeting previous and existing data schoolers because it was great to actually see other like-minded individuals who also share similar experiences and interests in data.

The Intense Alteryx Training
The rest of the week was devoted to intense Alteryx training. Alteryx is the 2nd program(the Other being Tableau) that all data school applicants would have been told about. Fundamentally, it is a versatile program that is used to clean, blend and manage data. It is a very underrated tool and the benefits are enormous. For someone who used to manage media data via excel, data preparation meant manually extracting data, manually replacing program names and repeating for multiple iterations. All that was a week’s worth of work and Alteryx with a click of “Run” can do the same within seconds…


Over the course of three days my cohort learnt about Alteryx on/in:
-Blending, joining and transforming data
-Data Parsing
-Spatial Analytics
-Workflow developments to various database outputs i.e tableau hyper Excel, CSV
-and how to continue the analytics journey with Alteryx

The Key takeaway: The need to be dynamic
All in all, this formed the core data cleaning skills for us to tackle any data set. And more importantly, these skills have instilled in us strong confidence in approaching any data set. For me, the key takeaway was to manage Alteryx workflows to be dynamic as opposed to static. I used to work in a high-intensity work environment. Media is a dynamic and ever-changing industry that requires strong reactive responses i.e this needs to be done with an emphasis on URGENTLY. I’ve produced workflows and even my data school application with anticipation that these would be one-offs, meaning let’s finish it and come back to it later. This is not the approach to have. Because what may work today might not work again tomorrow. So it’s better to spend a little more time debugging a robust and rigorous workflow rather than come a month later trying to figure out what went wrong… 

Anthony Wong
Author: Anthony Wong