Delving into the World of Data: Exploration Guide — Tip #5
Welcome aboard to the data world ⚓️
Ever felt like you’re Christopher Columbus embarking on a voyage to the unknown 🌎, being swamped by a sea of new terms, concepts, and ever-evolving technologies? This is the guide for you. In my previous article, #4 Get Started From dbt — 30 Tips to be Data Practitioners, I took you through my journey of stepping into the data world using dbt, and I know firsthand how mind-boggling it can be.
Here, I’d like to give you a compass 🧭 to navigate this ocean of the data world. We’ll explore three pivotal perspectives — the data stack, guidance for those beginning their journey, and the various roles in this the data world.
Discover the Data Stack Universe
You might recall from #3 Finding Your Data Fit — 30 Tips to be Data Practitioners that I started my exploration with the data stack. Your selection of the data stack that fits you is crucial, akin to choosing the right gear for an adventure.
Luckily, resources like https://www.moderndatastack.xyz/ have categorized various data stacks for your convenience. While the tools within each stack are numerous, the categories are manageable. E.g. 11+ tools for one category “Reverse ETL Tools.”
Data stack could also mean the data product, e.g. The hiring manager would declare the data stack to appeal or filter the candidates.
Think of data stack hunting as a quest, a tad like collecting Pokémon. There is always something new to discover.
🤜 Tip
Let your problems lead you. Identify your problem, and you’ll likely find an existing tool designed to solve it. For example, if you’re looking to automate emails after segmenting your users by data, “Reverse ETL” could be your hero. You may not know it by name initially, but a little research or chat with fellow data practitioners will soon get you there.
Seek the Guidance of the Data Gurus
If problem-solving feels a bit sporadic and you crave a systematic approach, I’ve got some top-shelf resources for you:
- The Analytics Engineering Guide by dbt is a treasure trove of insights from seasoned professionals.
- The Analytics Setup Guidebook by Holistics offers a solid framework to set up modern analytics.
- DataCamp’s Understanding Data Engineering and Understanding Data Science courses are excellent courses for starters.
These resources are just the tip of the iceberg. The world wide web is a library brimming with knowledge.
Evolving Data Roles
When I first dived into data, I learned about data engineers — the superheroes who set up dbt, BigQuery, and take care of data extraction and loading. But I knew their skills were beyond my reach. Then I heard about data scientists — a popular term, but not quite what I was doing.
Thankfully, dbt introduced a new role “analytics engineer” in 2022, which seemed to fit me like a glove.
Analytics engineers provide clean data sets to end users, modeling data in a way that empowers end users to answer their own questions.
Soon, another role “Data Analyst” popped up on my radar.
My suggestion? Dive into the roles and responsibilities (R&R) of each role. Job descriptions give you insights, but remember, titles should not confine your potential. Explore what you can do, and perhaps even invent your own title in a small or culture-fit company! The fun 😙 lies in the exploration!
What’s Next!
These three perspectives should serve as your compass as you navigate the vast ocean of the data world. Keep in mind that being a data practitioner is not just about the skills or roles you adopt. It’s also about the journey you undertake, the problems you solve, and the impact you create. So, take the leap and continue your voyage ⛵️ into the data world!
🤩 I’m happy to hear how you handle product development process? what tool do you use? Feel free to reach out to me on LinkedIn Karen Hsieh or Twitter @ijac_wei.
🙋🙋♀️ Welcome to Ask Me Anything.
