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

# Task 1 Intro

> Ad-hoc and batch analytics with DuckDB

![DuckDB Logo](https://duckdb.org/images/sharingduckdb.jpg)

## Task 1 Overview: Ad-hoc and Batch Analytics with DuckDB

In this task, you'll learn how to process and analyze historical data using DuckDB, a modern analytical database designed for OLAP workloads. You'll work with a mix of real and synthetic data.

### Learning Objectives

* Install and configure DuckDB for batch processing
* Query and explore CSV data files
* Query and explore JSON data files
* Perform geospatial analytics
* Create a data lakehouse with DuckLake, a new open standard built on object storage and PostgreSQL

## DuckDB Installation and Setup

### Install DuckDB

First, we need to install DuckDB to our Codespaces. DuckDB runs almost anywhere and it's very easy to install.

<Accordion title="Installation Hint">
  Visit the [DuckDB installation page](https://duckdb.org/docs/installation/?version=stable\&environment=cli\&platform=linux\&download_method=direct) for Linux installation instructions.

  For Codespaces, you can typically install it using:

  ```bash theme={null}
  curl https://install.duckdb.org | sh    
  ```
</Accordion>

### Verify Installation

Test that DuckDB is working correctly:

```bash theme={null}
duckdb --version
```

You should see the DuckDB version information.

### Adjust max columns

DuckDB has a default limit of 1000 columns. Let's increase it to 10000.

```bash theme={null}
.maxcolumns 10000
```