A 4-step method and concrete examples to apply right away
September often calls for new resolutions. Summer vacations are over, activity is picking up again. Why not use this time to set up new habits — or improve current ones — about staying up to date with the latest developments in the field of data science?
When I started my career as a data analyst I didn’t really take the measure of the amount of resources available out there. I had my freshly taken courses in mind and I could apply my knowledge at my job. It was only later that I realized I could learn even more by myself, get some help from others and discover new topics I had never heard about. For free! Online! I rapidly saw the risk of getting overwhelmed by the diversity of content available. So I developed some sort of ritual to stay up to date without spending countless hours reading articles, listening to podcasts or watching videos related to data science.
In this article I want to share some of the best practices I find to be most effective to keep track of everything going on in the field of data. On a more personal note I will detail some of my personal tricks and provide examples of how I apply these best practices to my own habits.
As the data world keeps expanding, the volume and variety of online resources available grow exponentially. Most of them are free; for others one should see if the return on investment (of buying an online training, of becoming a paying subscriber to a newsletter…) is worth it.
You should start by defining the type of topics you are most interested in. Of course keeping an open mind is crucial. But narrowing the scope of your interests will allow you to avoid wasting time and effort being informed about not so relevant topics for yourself. Here is a list of sub-domains within the wide area of data science:
- data engineering
- machine learning
- programming (particularly in your favorite language)
- data analytics
- data visualization
- data team management
Once you have a clearer idea of the topics you want to be informed about, it is time to look for dedicated resources online. The first way to stay up to date is to subscribe to specialized newsletters. As I am currently interested in building data best practices at a company, I particularly appreciate Benn’s newsletter. But there are several other newsletters out there like the Modern Data Stack’s newsletter and Blef’s Data News.
Another way to hear about the latest news is to look for data companies’ resources. Obviously one must systematically have in mind that there is a potential bias towards the company’s own products. Yet I found some really good reads in the “Data Insights” part of Airbyte’s blog and in the Analytics Engineering Roundup newsletter by dbt.
A third way to learn more about data news is to join communities and to connect with data practitioners. Whether it is on Medium or on LinkedIn, find and follow the persons who share content about data. Through their posts and articles you will learn what they are currently reflecting on, which may lead you to investigate further the topics that resonate with you. You can find a list of data content creators in the Data creators’ club. Personally this is how I could connect with other data practitioners who face similar challenges as I do.
Finally some companies regularly organize events like dbt Coalesce and Snowflake Summit. Whether you want (and can) invest into a physical trip to these events or not, the announcements made there are communicated online. You can also find some webinars and online trainings if you want to learn how a specific tool works. As an example I recently took dbt Fundamentals course and I learned a lot about data transformation — even beyond the specific tooling solution that dbt offers.
Now that you have found great resources to stay up to date, how do you dedicate time for them? At first sight it seems to be time-consuming and impossible to fit this R&D time into a regular day. Well, who said you had to read every article and listen to every podcast?
With all that content available you are spoiled for choice. The first way to choose what to read or listen to is simply by following your instinct: what would you most like to learn about today? This is at least how I prioritize between topics because I know that the topics I will best keep in memory are the ones that caught my attention intuitively.
With this pre-selection of resources in mind, how do you fit them into your day or week? What works best for me is to keep slots for my data science monitoring at least once a week in my calendar. Sometimes this slot is split across several days a week, especially at the end of work days when I have less energy for anything else. This is when I would read some of the newsletters I received. As for podcasts, I like to listen to them when I am travelling by train or when I go running.
With all that content read and listened to, how do you keep in mind the essential elements? Even with the best ability to memorize it can be hard to remember all the good stuff you went through.
Right after you consumed data science-related content, doing a quick recap of it orally can help “fix” your ideas. You can either talk to a friend about the article you just read or tell yourself the main takeaways from the article. This is how I make sure that I retain something concrete from an article. Otherwise it is easy to read and almost instantly forget what you just read.
A complementary approach is to write these down. I personally keep a Google Document file where I store all the most relevant links, recaps and ideas for the future. As categories of topics appear, I group my notes into common themes like “Data Architecture”, “Useful tools”, etc. In a dedicated folder I would have this file and some downloaded content (e-books, graphs…).