Top Tweets for #100DaysOfDataEngineering
Day 1 of 30 – #DataEngineeringJourney
🔹SQL: Solved 1 coding problem to sharpen query logic
🔹Spark: Covered basics — architecture, transformations, actions, DAG, lazy evaluation Building the foundation strong. #SQL #ApacheSpark #100DaysOfDataEngineering
Kicking off my 30-Day #DataEngineering Challenge!
For the next 30 days, I’m:
🔹 Solving 1 SQL problem every day
🔹 Learning + implementing 1 Apache Spark concept
If you’re also leveling up in #SQL or #Spark — let’s grow together.
#DataEngineeringJourney #100DaysOfDataEngineering
Day 49-56 #100daysofdataengineering
I’ve been working on a project a lot of brands need… A system to catch viral posts before they blow up.
Here’s how it’s going😊
I’m building a cheap and efficient pipeline to:
- Extract hourly data from Reddit’s API
🧵 [1/2]
detect trending posts early, before they spiral. Let’s see where it goes.
Day 41-48 #100daysofdataengineering
Day 40 #100DaysOfDataEngineering
Over the next few days, I’ll be working on my first end-to-end DE project.
This will help me breathe life into the abstract knowledge I’ve gathered so far. I'll collect data, model it, transform and load into BigQuery, then visualize in Tableau.
Day 38-39 #100daysofdataengineering
What if you could measure how much Trump's tariffs shook the stock market?
We know everyone was bleeding money, lol, but did you know that Spotify stocks managed to rise by +40% since Trump won the elections???
My latest project using [1/2]
![Jhoie__'s tweet photo. Day 38-39 #100daysofdataengineering
What if you could measure how much Trump's tariffs shook the stock market?
We know everyone was bleeding money, lol, but did you know that Spotify stocks managed to rise by +40% since Trump won the elections???
My latest project using [1/2] https://t.co/n8G8nyiBAS](https://pbs.twimg.com/media/GqSjdhxXMAANuGv.jpg)
Day 36-37 #100daysofdataengineering
I had to make a tough call this week.
I was ready to share my project on Trump's impact on the stock market…
But right before posting, I spotted a data discrepancy. Not my fault, but still my responsibility.
I could either hit [1/2]
![Jhoie__'s tweet photo. Day 36-37 #100daysofdataengineering
I had to make a tough call this week.
I was ready to share my project on Trump's impact on the stock market…
But right before posting, I spotted a data discrepancy. Not my fault, but still my responsibility.
I could either hit [1/2] https://t.co/Nbkv9u1wpr](https://pbs.twimg.com/media/GqHkEewWQAAuETk.jpg)
Day 22-35 #100daysofdataengineering
While the stock market has been experiencing a bloodbath, some stocks have been thriving quite nicely. In my recent project, I analyzed the market's reaction and recovery in response to Trump's tariffs.
Using SQL and multiple data [1/2]
![Jhoie__'s tweet photo. Day 22-35 #100daysofdataengineering
While the stock market has been experiencing a bloodbath, some stocks have been thriving quite nicely. In my recent project, I analyzed the market's reaction and recovery in response to Trump's tariffs.
Using SQL and multiple data [1/2] https://t.co/ZJ5Dw7StLo](https://pbs.twimg.com/media/Gp9Nax7XQAAZTcQ.jpg)
Day 21 #100daysofdataengineering
I’m taking out time to document my SQL and Python projects. I want to be more intentional about getting my work outside the four corners of my computer.
Day 20 #100daysofdataengineering
I spent a significant amount of time learning about data structures and their importance in data engineering.
I realized their importance and the tradeoffs they bring in terms of speed, cost, reliance and maintenance.
Day 19 #100daysofdataengineering
So I’m faced with an ethical dilemma and I need to hear diverse opinions.
So I created an AI summarizer for my personal tasks. Now, I’m thinking about using it to summarize Trump’s 116 Executive Orders.
I need to stay on top of global [1/2]
Day 18 #100daysofdataengineering
I created a document summarizer using Langchain and Python. The goal was to flex my Python skills and build a tool to aid my day-to-day activities.
Day 15-17 #100daysofdataengineering
I worked on an SQL project to analyze the impact of Trump’s tariffs on the global stock market.
I used datasets from the Global Stock Market and BBC reports, connected them, and wrote complex queries to uncover meaningful insights.
It [1/2]
Day 14 #100daysofdataengineering
For the next few days, I’ll be working on an SQL project. I’ll be back on Sunday with updates. 😊✌🏽
Day 13 #100daysofdataengineering
I begin my daily study not knowing what I'm doing half the time, but I always end with so much clarity. I owe everything to technical content creators. 😆♥️
That being said, today I learned about ETL, data pipelines and their use cases.
Day 12 #100daysofdataengineering
I was conflicted on if I should continue learning about Kimball's Data Warehouse approach. However, I got to learn that it serves as a good foundation in understanding data architectures.
Data keeps evolving and so will tools!
Day 11 #100daysofdataengineering
Today, I practiced Linux commands to get more comfortable at using the terminal.
Day 10 #100daysofdataengineering
Today I read Chapter 1 of The Data Warehouse Toolkit by Ralph Kimball.
However, I noticed there is some debate on the relevance of the Kimball Data Warehouse approach. I'd really like to know what experts in the field have to say about this.
Day 9 #100daysofdataengineering
Today, I learned about data models - the skeletal structure of what's happening in a business. I got to know how data models affect storage, speed, and business costs.
Other concepts I learned include: Conceptual Model, Logical Model, [1/2]
Day 8 #100daysofdataengineering
One thing I've prioritized on this journey is building a solid foundation. I spend a good amount of time learning the basics
While learning about Linux today, I went down memory lane to study its history, why operating systems work the way [1/2]
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