# Introduction

Welcome to the introduction to data session run by Claire Back and Dave Rowe.

## Timetable

| Time  | Description                          |
| ----- | ------------------------------------ |
| 10:05 | Introduction                         |
| 10:10 | Group exercise: jargon busting       |
| 10:25 | Group exercise feedback              |
| 10:35 | Teaching: data and automation        |
| 10:40 | Human data intro                     |
| 10:45 | Human data part A                    |
| 10:50 | Human data part B                    |
| 11:05 | Working with data exercises and demo |
| 11:15 | Finish and answers                   |

## Introduction

This session introduces working with data. At the conclusion of the lesson you will:

* understand terms, phrases, and concepts in data analysis;
* identify and use best practice in data structures.

## Why Data?

We make decisions every day. Sometimes these are very small ones that don't require much consideration, or that come naturally through professional experience. But making the right decisions is key to our roles and the people we are trying to help. There are many aspects to decision-making that we always try to take into account. What's the ethical thing to do? Is it legal? Is it possible? Can we afford it? Is it supported by data?

Think of some example library-based decisions:

* amount spent on different types of stock;
* fines for overdue items;
* hire charges;
* staff levels in a library at different times;
* van routes and frequencies to move items between branches;
* stock to have in different libraries;
* opening hours;

How often are these fully informed by analysis of data and evidence?

Data is essential to decision-making, but even when data is available to us, we don't necessarily have the skills to interpret it, or manipulate it in the way we need to. But you don't need to be a data scientist to gain confidence in using data. This session aims to discuss data tasks we all deal with, and gain practice in some data manipulation techniques.

## Source Material

See [introduction to data](https://data-lessons.github.io/library-data-intro/01-introduction/) at the Library Carpentry materials site.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://librarydata.gitbook.io/voyage/introduction.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.