The key skills to understand, manage and work with data.
Data FundamentalsThe Data Fundamental modules provide a solid overview over the workflow with data guiding you from what data is, to how to make your data tell a story. The courses listed below should be seen as a whole, a quick overview of the elements involved in working with data.
What is Data?This course gives a short introduction in the world of data. If you are starting your journey into this wonderful land, this course is for you. The course covers basic concepts, different types of data and gives an introduction to machine readable data.
Finding DataDon't know where to start looking for data? This section gives an introduction to data portals and different data sources. Finally we will walk you through how to use one sample data portal.
Sort and Filter: The basics of spreadsheetsSo you found and downloaded your dataset? What now? Sort and Filter introduces a powerful tool to manage data: Spreadsheets. Based on Google Spreadsheets, this Course introduces the basic functions as well how to sort and filter data to find what you might be interested in….
Taming the Fierce Beast – The Math you need to startWorried about all those numbers? This module will help you to refresh the basic math (don't be afraid it's mainly counting and adding).
'But what does it mean?': Analyzing data (spreadsheets continued)Wonder how to make sense of the data? Basic Analysis will help you to understand what your data might mean. It also introduces spreadsheet formulas and helps you calculate more values out of what you already have.
From Data to Diagrams: An introduction to plots and chartsA picture says more than a thousand words – yeah but how do we turn a thousand words into a picture? This section will help you to understand basic data visualization and create them using Google spreadsheets. Visualizing data will help you to better understand the data you are handling.
Look Out!: Common Misconceptions and how to avoid them.Not everything is easily understood in dataland. In this course we give a short overview over common pitfalls when talking about data and how to avoid them. It can help you avoid the mistakes made as well as read other peoples claims more carefully. If you want to learn what to watch out for: join in!
Tell me a story: Working out what’s interesting in your dataData alone is meaningless and often boring. To understand it better you will need context. In this section we will talk about how to publish the data we worked on throughout the basic track. We will talk about how to identify key points of your data to help you use data to make your voice heard.
Data provenanceTo make a credible and sustainable data project, you need to document your steps right from the beginning. This course contains tips and tricks and tools for doing so.
Basic GraphsVisualising your data is not just about communicating your findings. It's also a very powerful way to gain insights into your data. This module introduce you to the basics of making graphs in a spreadsheet.
A Gentle Introduction to Data CleaningThis School of Data course is a gentle introduction to reducing errors by cleaning data. It was created by the Tactical Technology Collective and gives you a clear overview what can go wrong in spreadsheets and how to fix it (if it does). Take this course if you want to learn why it is important to clean data and how to do it.
Course outline: a gentle introduction to cleaning dataIn this section, learn about the “horror stories” of where data errors in spreadsheets have led to real consequences and how you can avoid them yourself.
Section 1: Nuts and chewing gumIn this section, you’ll gain practical knowledge of common formatting and layout features of spreadsheets and some ideas about how to present your raw data to others so they will love you!
Section 2: the Invisible Man is in your spreadsheet, messing with your dataIn this section, you’ll learn how even characters which you cannot see can cause havoc in data analysis. The section will teach you to ghostbust white space and other non-printable characters such as carriage returns, spaces and tabs. Once you have removed them, you can get on with your analysis in peace.
Section 3: your data is a witch’s brewThree is not a number. Nor is a million. At least not when they are typed in as text in a cell in a spreadsheet. Your spreadsheet is pedantic and needs everything to be precise and consistent. Read on to learn more.
Section 4: Did you bring the wrong suitcase (again)?All our spreadsheet wants from us is each cell of data to be organised and neatly packed. In this section, you will analyse data to highlight problems in the way it has been structured so as to avoid them in your own work with data.
Introduction into Exploring DataThis set of modules will give you essential tools to explore and analyse data to find insights. Made by Tactical Technology Collective, School of Data and friends.
A gentle introduction to exploring and understanding your dataWhat if we told you, there is a quick way, your computer can help you to summarize and understand data? Wouldn’t this be great? Check this course to learn how to use pivot tables to do this!
Advanced Spreadsheet FormulasIt's time to go beyond the basics and learn advanced formula tricks. This module will introduce you, among other things, to Vlookup: one of the most powerful spreadsheet formula.
An introduction to SQL Databases for analysing data - Part 1Spreadsheets are really useful, but sometimes they're too limited for what you want to do. Like analysing a very big dataset quickly or gaining complex insights on your data. Here comes the SQL query.
An introduction to SQL Databases for analysing data - Part 2Now that we know the basics of SQL language, we can explore how to use them to analyse a real dataset.
A gentle Introduction into Extracting DataYou know the data you need is somewhere out there on the Web - but how do you get it on your computer? This course will lead you there.
Extracting Data from PDFsFar too much data is trapped in PDFs. In order to be able to work with, analyse and visualise data, we need it in machine-readable formats. It's often not easy to the data out again, but sometimes possible - find out how here.
Making data on the web useful: scrapingLearn how to scrape without code in 5 minutes and when you might need to invest time in more sophisticated techniques.
A Gentle Introduction to MappingSo you want to make maps? Maps are easy to read, but not that easy to make. Read on to discover the tools and techniques that will allow you to make maps for offline and online uses.
Online geocodingNeed to put your data on a map but it doesn't contain Latitude and Longitude values? Read on!
Introduction to GIS: QGISThere are many ways to visualise data on a map. But the free and open source tool QGIS (or Quantum Geographical Information System) will give you a lot more power and flexibility than most tools.
Collecting data using smartphonesIf you ever had to collect data on the field for research or humanitarian purpose, you know how complicated that process can be. But with the right tools and a good process, mobile data collection can be made a lot more easy and efficient.
Course outline: introduction to mobile data collection and ODKAn introduction to the challenges of mobile data collection and the tool that will be featured for this course: Open Data Kit
Creating your ODK Data Collection FormThis module will introduce you to the initial setup of your spreadsheet for use with Open Data Kit
Uploading and Testing your forms using Kobo ToolboxThis module will help you navigate the interface of Kobo Toolbox, a variation of Open Data Kit, to prepare forms before starting your survey.
Setting up your Kobo Toolbox form on your Android deviceKobo Toolbox provides a good platform to collect data using two devices: your laptop and your mobile devices e.g. smartphones and tablets. On this module, we will talk about how to use your Kobo Collect forms on your devices.
Managing your Kobo Toolbox databaseWith this last module about Kobo Toolbox and mobile data collection, we will talk about how to manage your Kobo Toolbox database using the online platform.
Presenting DataData presentation can mean Data visualisation, but not only. There are a million ways (and tools) to present data, and the best way is the one that works for your audience. This course will introduce you to some interesting tools and methods, allowing you to tackle data presentation in various ways.
Storytelling with data: TimemapperJsAre you working on complex stories involving different kind of data (geographic, time)? Get to know the datastorytelling tools that help you make the most of your story.
Know your data to make the best out of it.
An Introduction to Aid DataThis course was produced in 2014 as part of the Open Development Toolkit, a project led by Zara Rahman and jointly funded by School of Data and Development Initiatives. It provides an introduction to the world of data available on the topic of international aid, from finding it, cleaning it, visualising it and using it in the media.
Course outline: Introduction to aid dataWelcome to the world of aid data! In this first module, we’ll be starting from first principles: what do we actually mean when we say ‘aid’, and why is looking at aid data important?
A guide to IATI dataOne major source of aid data is made available through the International Aid Transparency Initiative (IATI). There are a few different ways that you can access raw IATI data, so here’s a quick run through of what you can get, and where it is, including IATI data itself as well as data about IATI data (metadata).
Cleaning IATI data with OpenRefineSo once you've got the raw IATI data, what next? Often it might need 'cleaning' - here, we'll use a sample IATI dataset to learn how to use a powerful cleaning tool, OpenRefine.
An introduction to OECD-DAC dataAnother major source of data available about international development data, is the OECD. Here, we run through a few ways that they make this data available, and where to find what you're looking for.
Inspiration module: how is aid data used in the media?We've seen a few ways of where to find aid data, how to clean it and use it - but how is this applied in the real world? Here are a couple of examples of 'reverse engineering' aid data that we might come across in the media - maybe it will give you some ideas!
An introduction to data visualisationThis module is structured a little differently to the others, in that this is a slideshow running through different ways that aid data can be visualised. Included are instructions on how to customise the slideshow for your own purposes, and tips on presenting it to other people.
Jargon busting the world of aidThis module is intended as a reference point while you're going through the other modules. In each case, the relevance of the term to working specifically with data is highlighted to try and make it clear what you should be looking out for when you come across the term in your work.
Working with Budgets and Spending Data.In this course, we will take you through the steps involved working with budget and spending data. In the process, you’ll learn how to wrangle and clean up some of the most common errors which we see in spending and budget data, as well as doing some dataset gymnastics, such as transposition and cleanup before creating a simple visualisation at the end. If you don’t have your data yet, or don’t have it in machine-readable format – take a look at the two courses above on extracting data, we start from cleaning up and formatting your data.
Categorization and reference dataNeed to put your data on a map but it doesn't contain Latitude and Longitude values? Read on!
Choosing an audience and classifying your dataSometimes you will need to classify your financial data, for example, to reflect services that people care about or to conform to internationally recognised standards.
What is the difference between budgets and spending?Before we begin working with the data, let's take a closer look at the difference between budgets and spending data - what questions is it possible to answer with this data?
Cleaning spending dataA quick introduction to why spending data often needs cleaning, following into a recipe for cleaning spending data with Open Refine.
Learn about the relevant skills and tools to solve common problems (coming soon).