In REA, we have a list of highly sought after internal courses available on various topics including AWS, Docker and Elasticsearch. On 7th and 8th May 2018, we added Scala to the list, with over 20 people attending!
How did this all start?
Scala and functional programming have always had some mystique surrounding it. There is this idea that it is too hard or not pragmatic enough. Existing courses are very technical and many people including myself have struggled to complete them.
“Do we (still) need QAs?”
… and flavours thereof, is a question I have been hearing for years now.
The same has been asked of Tech Leads, Operations Engineers, “Front End” devs, “Back End” devs, Security, Iteration Managers/Scrum Masters, Business Analysts, etc. Anything that is not a full-stack dev. The #NoOps conversation is interesting research material.
It seems to me that this question stems from a misinterpretation of agile and lean startup materials.
Idealistic hopes of cutting costs, removing waste (and blindly classifying some roles as such), delivering faster, etc., have caused some to think that role specialisations can all be generalised into being “Engineers” and that we can all self-organise and just do it all.
Having been a female my entire life and interested in numbers for nearly as long, I’m passionate about getting more women to work with data. We know that there’s a gender imbalance in data analysis roles across the industry. Even at REA Group, only about 30% of our data analyst roles are currently held by women. With data roles projected to grow by nearly 20% over the next five years and data becoming increasingly important in fields from marketing to HR to agriculture, it’s a great time to encourage more women to enter the field.
One of the ways we’re doing this at REA Group is to partner with Datadriven.sg to run full-day Data Girls workshops, designed to give an overview of tools and techniques for data analysis and how data is used to drive business decisions. In our first two workshops we’ve hosted over 120 women from many different industries, including education, music, medicine, and marketing–all with a range of experience in using data.