Automatically identify potential story leads. Lets you create autonomous bots which poll data sources and run predefined data analysis. Results are then compared to the last time the bot ran – and any additions or deletions trigger an email alert.
Create simple static charts quickly – a tool for the non-technical. Can be easily customised to your organisation's house style using a simple stylesheet.
Enrich your data by doing batch lookups against various online services. For example, quickly convert a list of company names into a list of directors of those companies.
Finds matches in two spreadsheets, optionally using various fuzzy-matching algorithms. Used by organisations including the Guardian, the Times, and news agency Irin who used it to identify a company the United Nations had a contract with who was also on its own sanctions list.
Like our reality, our data is often messy. Finding meaningful connections between such datasets often means using fuzzy matching algorithms. This was a high-level look at some of the most commonly used algorithms, their pros and cons, and how they are used in practice. Slides here.
Want to take your first steps with code but not sure how to begin? Or want to learn how code is being used in the newsroom and if it can help you and your team? This weekend workshop is an introductory primer to learning to code, showing recent story examples, explaining the fundamental concepts in programming, and demystifying the jargon. Book here.
Graph database Neo4j has been used as part of an increasing number of investigative stories including the Panama Papers. This two-hour session was a hands-on introduction to the tool, examples of how it has been used, and a demonstration showing how to build a database of political donations matched with corporate data, revealing the networks involved.