Category: Data
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Humour me – DRY vs WRY
Don’t Repeat Yourself (DRY) is a tenet of software engineering, but – humour me – let’s consider some reasons Why to Repeat Yourself (WRY). LEGO reuse lessons In 2021, I wrote a series of posts analysing LEGO® data about parts appearing in sets to understand what it might tell us about reuse of software components…
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I did it my way – hand-rolled navigation with open spatial data
Sure commercial maps app directions are great, but have you ever found the customisation options limited? What if you want to use bike paths and back streets when cycling, or avoid winding roads that might make backseat passengers car-sick on a road trip? The paved route OpenStreetMap and OpenRouteService do provide this type of functionality,…
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22 rules of generative AI
Thinking about adopting, incorporating or building generative AI products? Here are some things to think about, depending on your role or roles. I assume you’re bringing your own product idea(s) based on an understanding of an opportunity or problems for customers. These rules therefore focus on the solution space. Solutions with generative AI typically involve…
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Synthesising Semantle Solvers
Picking up threads from previous posts on solving Semantle word puzzles with machine learning, we’re ready to explore how different solvers might play along with people while playing the game online. Maybe you’d like to play speed Semantle against an artificially intelligent opponent, maybe you’d like a left-of-field hint on a tricky puzzle, or maybe…
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Second Semantle Solver
In the post Sketching Semantle Solvers, I introduced two methods for solving Semantle word puzzles, but I only wrote up one. The second solver here is based the idea that the target word should appear in the intersection between the cohorts of possible targets generated by each guess. To recap, the first post: introduced the…
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Data Mesh Radio
I joined Scott Hirleman for an episode (#95) of the Data Mesh Radio podcast. Scott does great work connecting and educating the data mesh community, and we had fun talking about: Fitness functions to define “what good looks like” for data mesh and guide the evolution of analytic data architecture and operating model Team topologies…
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Data mesh: a lean perspective
Data mesh can be understood as a response to lean wastes identified in data organisations. I paired with Ned Letcher to present this perspective at the LAST Conference 2021, which was much delayed due to COVID restrictions. Lean wastes including overproduction, inventory, etc, may be concealed and made more difficult to address by centralised data…
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The Business Case for Data Mesh
I collaborated with with some colleagues to share our experiences with data mesh and how to frame the benefits for an executive audience, written up in an article titled The Business Case for Data Mesh.
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Data mesh at Data Engineering Melbourne Meetup
Here’s the recording of my presentation on data mesh at the Data Engineering Melbourne Meetup, on 26 August 2021. We covered architecture, building blocks and more. Lots of great questions and discussion. Thanks as always to organisers Harmeet Sokhi, Timothy Findlay, and Andrew Jones!
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Slackometer Hello World
Project Slackpose gives me one more excuse for hyperlocal exercise and number crunching in lockdown. Last time, I briefly touched on balance analysis. This time, I look at tracking slackline distance walked with my newly minted slackometer. Inferring 3D Position I’m working only with 2D pose data (a set of pixel locations for body joints)…