The Fundamentals 📚

The Fundamentals 📚

In this section, we break down the foundational knowledge essential for data professionals, providing a solid framework for mastering the core principles of modern data ecosystems. Whether you’re a data architect, engineer, or AI practitioner, understanding the principles behind data and AI technologies is crucial for building scalable, efficient, and future-proof solutions. This section offers key concepts to help you navigate the evolving data landscape with confidence and expertise.

What You’ll Find Here

📊 Data Analytics: Discover how to transform raw data into actionable insights with the right tools, methodologies, and visualizations.
🏛️ Data Architecture: Learn about designing scalable, secure, and efficient data systems that support business needs.
🔧 Data Engineering: Master the ETL/ELT processes, data pipelines, and modern data stack technologies powering AI and analytics.
🤖 Data Science & AI: Understand machine learning, deep learning, and AI models that drive automation and intelligent decision-making.
📂 Data Governance: Explore best practices for data management, metadata, quality, and compliance to ensure trustworthy data.
📦 Product Management: Learn how data products are designed, built, and managed to align with business objectives.
📋 Project Management: Discover how to lead and execute data initiatives with agile methodologies and strategic planning.

Understanding the Data Lifecycle

This diagram illustrates a modern data platform, covering the entire lifecycle of data—from ingestion to serving layer 🚀.
Each step ensures data quality, governance, and accessibility, allowing organizations to turn raw data into strategic value.

Data Engineering

15/03/2025

7 Min Read

Difficulty

★ ★ ★

Data Modeling: Storing historical data

Every day, your data lake ingests 20 million client records. If you store all these records, you will accumulate around 7.3 billion records per year (and Jeff Bezos will definitely love charging you for that 🤑!).

Data Analytics

09/03/2025

8 Min Read

Difficulty

★ ★ ★

Data Modeling: Star, Snowflake, Galaxy, Data Vault, Wide-Table

Cause you’re a sky, full of stars, I’m gonna give my heart.” 🎶 Today we’ll be exploring the galaxies and the stars of data modeling.

Data Architecture

08/03/2025

12 Min Read

Difficulty

★ ★ ★

Data Modeling: Dive into data normalization levels

At its core, normalization follows the principle of Don’t Repeat Yourself (DRY). This ensures that each piece of data is stored only once, reducing redundancy and improving data integrity.

Data Architecture

01/03/2025

6 Min Read

Difficulty

★ ★ ★

The Foundation of a Scalable Data Architecture : Data Modeling 101

Data modeling consists of three key layers, each playing a unique role in the lifecycle of data architecture.

Data Architecture

22/02/2025

7 Min Read

The Foundation of a Scalable Data Architecture : Data Storage

Hello, all data lovers! Today, I want to talk about a subject that is absolutely crucial for every organization. We…

Data Architecture

15/02/2025

9 Min Read

Difficulty

★ ★ ★

From Data Models to Database Technologies: Choosing the Right Tool for the Job

You’re designing the next big e-commerce platform, and everything looks great—until your database starts slowing down 🐌.

The Fundamentals

14/02/2025

5 Min Read

Difficulty

★ ★ ★

Analytical vs Transactional : Why You Can’t Mix Oil and Water

Data is everywhere. Data powers customer management in databases, speeds up websites through caching, and fuels decision-making in executive dashboards.

The Fundamentals

08/02/2025

5 Min Read

Difficulty

★ ★ ★

Data 101 : A beginner guide to Data & AI

The massive amount of data a company generates daily. Every time you buy something online, swipe your credit card, or even just browse a website, you’re generating data.

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What You’ll Find Here

Understanding the Data Lifecycle

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