Workshop: Introduction to Databases

UC Davis DataLab
Spring 2024
Instructor: Elise Hellwig <echellwig@ucdavis.edu>
Maintainer: Elise Hellwig <echellwig@ucdavis.edu>

• Reader
• Event Page
• Google Drive

Description

This workshop provides a broad overview of the various technologies for storing and organizing different collections of data. We will discuss how data structure and data types impact your storage options, when you should use a database, and which platforms you might consider for your research. This workshop is a general lecture with case studies and Q&A (no laptops necessary). This workshop is a prerequisite for DataLab's "Getting started with SQL for querying databases" workshop and part of the Research Computing micro-credential.

Learning Goals

By the end of this workshop, learners should be able to:

• Describe different data set structures

• Compare and contrast different data storage platforms

• Explain the differences between SQL and noSQL databases

• Explain the components of an Entity Relationship Diagram (ERD)

• Define relational keys

• Identify appropriate data storage solutions based on the structure of a research data set

Contributing

The course reader is a live webpage, hosted through GitHub, where you can enter curriculum content and post it to a public-facing site for learners.

To make alterations to the reader:

1. Check in with the reader's current maintainer and notify them about your intended changes. Maintainers might ask you to open an issue, use pull requests, tag your commits with versions, etc.

2. Run git pull, or if it's your first time contributing, see Setup.

3. Edit an existing chapter file or create a new one. Chapter files are R Markdown files (.Rmd) at the top level of the repo. Enter your text, code, and other information directly into the file. Make sure your file:

   • Follows the naming scheme ##_topic-of-chapter.Rmd (the only exception is index.Rmd, which contains the reader's front page).
   • Begins with a first-level header (like # This). This will be the title of your chapter. Subsequent section headers should be second-level headers (like ## This) or below.
   • Uses caching for resource-intensive code (see Caching).

   Put any supporting resources in data/ or img/. For large files, see Large Files. You do not need to add resources generated by your R code (such as plots). The knit step saves these in docs/ automatically.

4. Run knit.R to regenerate the HTML files in the docs/. You can do this in the shell with ./knit.R or in R with source("knit.R").

5. When you're finished, git add:

   • Any files you added or edited directly, including in data/ and img/
   • docs/ (all of it)
   • _bookdown_files/ (contains the knitr cache)

Then `git commit` and `git push`. The live web page will update
automatically after 1-10 minutes.

Github Actions

GitHub Actions can be set up to automatically render your reader when you push new content to a repo. If you would like to use this function, download the materials in datalab-dev/utilities/render_bookdown_site and follow the instructions there.

Setup

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