> ## Documentation Index
> Fetch the complete documentation index at: https://data.wiki/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction

> Welcome to a pragmatic first open workshop to learn data analytics

## Introduction

This workshop has its objective to inspire people with the latest open and modern data analytics technologies and how to design the right architectures.

More specifically, a distinction is made between two typical scenarios:

* **Batch data processing** - Analyzing historical data in batches
* **Real-time data streaming** - Processing data as it arrives in real-time

## Workshop Objectives

### High-Level Goals

1. **Master Modern Data Stack Components**: Learn to work with DuckDB, ClickHouse, Kafka, and Metabase
2. **Understand Data Architecture Patterns**: Explore both batch and real-time processing paradigms
3. **Build End-to-End Analytics Solutions**: From data ingestion to visualization
4. **Practice Real-World Scenarios**: Work with actual restaurant and coffee shop data from Prishtina

### Learning Outcomes

By the end of this workshop, you will be able to:

* Set up and configure modern data analytics tools
* Process batch data using DuckDB and PostgreSQL
* Implement real-time streaming with ClickHouse and Kafka
* Create data lakehouses for scalable analytics
* Build interactive dashboards with Metabase
* Apply geospatial analytics to location-based data
* Design data architectures for different use cases

## Workshop Structure

### Task 1: Batch Analytics with DuckDB

* **Focus**: Historical data processing and analysis
* **Technologies**: DuckDB, PostgreSQL, R2 Object Storage
* **Data**: Namecheap premium domain names, restaurants and coffee shops and historical revenue data

### Task 2: Real-Time Analytics with ClickHouse

* **Focus**: Real-time streaming and live analytics
* **Technologies**: ClickHouse, Kafka, Metabase
* **Data**: Streaming real-time transaction from restaurants and coffee shops

## Prerequisites

* Basic understanding of SQL
* Familiarity with command line tools
* Knowledge of CSV, JSON, and tabular database formats
* Understanding of basic data concepts

## Data Overview

### Namecheap Premium Domain Names

* **Format**: CSV
* **Content**: Premium domain names
* **Data Fields**: domain, price, extensions\_taken
* **Source**: Namecheap marketplace

### Prishtina Places Dataset

* **Format**: JSON
* **Content**: Restaurants and coffee shops
* **Data Fields**: name, location, rating, reviews, coordinates
* **Source**: Scraped using SerpAPI from Google Places

### Historical Transaction Data

* **Format**: PostgreSQL database
* **Content**: Synthetic transaction data for each establishment
* **Time Range**: Historical synthetic data from 2025 for trend analysis

### Real-time Transaction Data

* **Format**: Kafka
* **Content**: Real-time transaction data from restaurants and coffee shops
* **Time Range**: Real-time syntheticdata for immediate analyses and decision making

## Getting Started

1. **Open the Workshop**: Click the "Open in GitHub Codespaces" button above
2. **Follow Tasks Sequentially**: Complete Tasks (e.g. 1.1) before moving to the next task (e.g. 1.2)
3. **Use Hints**: Each task includes helpful hints and answers in accordion sections
4. **Experiment**: Don't be afraid to try different approaches

## Next Steps

Ready to begin? Let's start with Task 1 to learn about ad-hoc and batch analytics with DuckDB.