Fuzzy matching – context and testing

This is the third article in a short series on fuzzy matching:  Introduction  Example algorithms  Testing and context  In this article I will consider the difference between context-dependent and context-independent fuzziness, and think about how fuzzy matching systems can be tested.  Context-dependent and context-independent fuzziness  If you are trying to do fuzzy matching of strings, … Continue reading Fuzzy matching – context and testing

Fuzzy matching – example algorithms

This is the second article in a short series on fuzzy matching:  Introduction  Example algorithms  Testing and context  In this article I will go into three algorithms that are examples of fuzzy matching – Levenshtein distance, Dynamic Time Warping (DTW) and Hidden Markov Models (HMMs).  Levenshtein distance  The Levenshtein distance is a way to do … Continue reading Fuzzy matching – example algorithms

Connecting Azure Data Factory code to an external database table

In this article I will talk about how to connect Azure Data Factory (ADF) to a database table. This can be surprisingly complex, so I will start with the simplest version and work towards more complex versions. I won't go into connecting ADF to other types of data store such as APIs, blob storage etc, … Continue reading Connecting Azure Data Factory code to an external database table

An introduction to parameterised types

This article is about parameterised types, which are also known as generics or parametric polymorphism.  I first came across them in the functional programming language ML, but they have spread beyond the functional programming world, to languages like Java, C#, and TypeScript. Parameterised types let you define a family of similar but different types What … Continue reading An introduction to parameterised types