What do you really need to know to work effectively with data?
Published in · 5 min read · May 30, 2022
--
The financial industry uses a lot of data, and many analysts have to pick up tech skills on the job. If you work in this field, you’ve likely inherited several poorly maintained Excel workbooks that have been passed down for generations. Everybody knows that there are better ways to store data and maintain models, but I don’t think most people realize how long a little coding can go.
I entered the financial industry with zero programming knowledge, and started learning on the job. It’s had a very positive impact on my career satisfaction. I’ve gathered some insights throughout my journey, and they might be useful to anyone in a similar position.
What languages should you learn (and which ones should you skip)?
Let’s start by talking about the languages you should skip. Since Excel is still widely used throughout the industry, it’s tempting to learn VBA. There are some limited situations where VBA might be the right tool, but it’s a frustrating language to use. Further, it keeps you dependent on Excel. Matlab is another language that’s been used quite a bit in the industry, but I think there are much better options these days.
I believe for most analysts in the investment industry, you should learn two languages: SQL and either Python or R (There are definitely some benefits to know both Python and R).
SQL is arguably the most important language for analysts, but it often gets omitted from the list. SQL definitely isn’t as sexy as Python, but there are a lot of good reasons to make it your first language. You will learn the basics of how data is modeled, and how to perform all the common transformations. This will make learning libraries like Pandas or dplyr more intuitive when you dive into Python or R.
In my experience, data management gets overlooked on many investment teams. Too many teams rely on Excel workbooks for storing data, and it creates a lot of problems. If you can learn even a little bit about databases and SQL, you can start migrating away from Excel into safer and more scalable solutions.
