Recap August 2024
Here’s what you may have missed last month
Greetings, curious reader,
You are reading the special monthly issue of Data Gibberish (this time, a bit later than usual). These monthly recaps allow you to catch up on what you missed last month. Enjoy your reading!
Data Engineering Career Boost: Become Your Team's T-Shaped MVP
Are you struggling to keep up with data engineering's rapid changes? Becoming a T-shaped data engineer could be your solution. This approach combines deep expertise in one area with broad knowledge across various domains.
Why does it matter? It can revolutionise your career and make you invaluable to your team. How do you achieve it?
Start by assessing your skills, creating a learning plan, and implementing new knowledge.
What's the impact? You'll become the go-to person for complex problems.
Crush Scope Creep: Data Engineer's Blueprint for Bulletproof Data Product Plans
Ever struggled with project chaos? A scoping doc could be your lifesaver. It's not just paperwork. It's your project's roadmap.
Why bother? It aligns expectations, prevents scope creep, and boosts success rates.
How do you create one? Start with the problem statement, define objectives, and outline deliverables. Don't forget to set boundaries and identify risks.
What's the payoff? More transparent communication, smoother execution, and happier stakeholders.
Data Team Building 101: Hire This Profile First To Set Yourself For Success
Launching your data team? Your first hire should be an analyst.
Why? They bridge the gap between data and business decisions. Analysts can translate raw data into actionable insights. They understand business needs and can communicate effectively with stakeholders.
How does this benefit you? You'll get immediate value from your data with simple infrastructure. Analysts can identify quick wins and guide future data strategy.
Unlocking dbt: Everything Data and Analytics Engineers Need to Know
Curious about dbt's role in data engineering? It's reshaping the field. dbt bridges the gap between data engineers and analysts.
How? It empowers analysts to handle data transformations independently.
What's the impact? Data engineers can focus on more complex tasks.
Is it a threat to data engineering jobs? Not really. It's an opportunity for evolution. You'll need to adapt your skills.
What's next? Learn SQL, version control, and data modelling. Embrace collaboration with analysts.
Until next time,
Yordan
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