Tasks Overview

🗓️ 4-Day Data Analyst Onboarding Overview

Welcome to your 4-day onboarding sprint! This program is designed to introduce you to our real-world data stack and workflows. Each day you’ll tackle a focused, hands-on challenge that simulates core parts of our pipeline—from raw data ingestion to analysis and integration.

In every daily_tasks/day_X/ folder, you’ll find:

🔗 A link to the task’s GitHub Issue (in the README or markdown files)
📂 All necessary datasets, database connection details, and starter materials

🧑‍🏫 You’ll get guided explanations and walkthroughs by a team lead during the morning masterclass.

📍 What to Expect Each Day

📊 Day 1 – Data Exploration & Submission

Start with a small dataset. Explore it using Google Sheets.
You’ll answer simple analytical questions and share your work.

🧰 Skills: Data loading, quick exploration, Google Sheets, basic markdown submission

🧹 Day 2 – Data Cleaning & Preparation with Python

Work with messy data. You’ll clean, transform, and prepare a dataset for analysis.
Handle duplicates, missing values, naming conventions, and outliers.

🧰 Skills: pandas, data types, cleaning strategies, CSV export

🗃️ Day 3 – SQL + Python Exploration

Connect to the PostgreSQL training DB and explore it with SQL inside Python notebooks.
Answer analytical questions using real queries and joins.

🧰 Skills: psycopg2 / sqlalchemy, pandas.read_sql, JOINs, filtering, logic in SQL

🧮 Day 4 – Data Integration & Schema Design

Integrate a new dataset into the existing PostgreSQL schema.
Identify keys, clean/prep with Python, and write a script to append it to the database.

🧰 Skills: Data modeling, ETL scripting, foreign key relationships, INSERTs via Python

We’re here to help — ask questions during the daily masterclass or on Discord!

Let’s build something great. 💪