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Data

A collection of 14 posts

Topological Data Analysis for CAN Decoding

Topological Data Analysis for CAN Decoding

In this blog post, we have tried to explore topological data analysis in the automobile domain. Our analysis was to decode the CAN ID from the data byte on a CAN bus. Multiple methodology was explored and ultimately, a Kepler mapper an exploratory data analysis tool from TDA helped us

Becoming Data Driven: Lesson learned (Part 2)

Becoming Data Driven: Lesson learned (Part 2)

This article follows another post "How to become a Data Driven Company in 10 simple steps" which relate the steps we took in initiating our data driven initiative. When reflecting on our journey there are some take away, things we could have done differently and areas we are

How to become a Data Driven Company in 10 simple steps

How to become a Data Driven Company in 10 simple steps

When your core business is selling tyre 1. Build A Data Custodian Network and a Data Catalogue 🕸️ The first step in becoming Data Driven is to identify the experts in the data within your company. Those would generally be people within your IT organisation that have a good understanding of

AI for Engineering

AI for Engineering

AI for Engineering, an active topic for Michelin. Looking back at 2022, we have been communicating on it on different channels, but not on that tech blog. Let’s do it now before it gets outdated! In the data transformation at Michelin, we love meshes [see data mesh], and Artificial

An introduction to Datalog

An introduction to Datalog

A rule-based data query language that thinks differently

Open Sourcing Qlik Enterprise Manager Ansible Module

Open Sourcing Qlik Enterprise Manager Ansible Module

Michelin Engineering team is pleased to announce Qlik Enterprise Manager Ansible Module in open source. Discover how our teams use this Ansible Module permits improve the speed and quality of Qlik resources deployment.

“The metamorphose” of our Information System by Implementing a distributed event streaming platform

“The metamorphose” of our Information System by Implementing a distributed event streaming platform

In this article, I want to share Michelin's experience on its first implementations of Kafka and distributed architectures, which is part of the early stages of implementing our EDA architectures. Our firsts experiences we had on a distributed platform.

Open Sourcing Kafka Connect transforms for Qlik Replicate

Open Sourcing Kafka Connect transforms for Qlik Replicate

We're very pleased to announce Kafka Connect transforms for Qlik Replicate in open source. This Single Message Transformation library aims to ease a Change Data Capture event integration into the Kafka ecosystem.

Learn EDA & Streaming from practice

You hear more and more IT colleagues talk about event-driven architecture and stream programming, you understand this is the new paradigm shift of IT system design in company, but you might wonder how to grasp the key concepts quickly and most important how to apply them in your own products,

Ordering guarantee when using Qlik Replicate and Apache Kafka

Ordering guarantee when using Qlik Replicate and Apache Kafka

Streaming a database looks simple with Change Data Capture and Kafka. This post will explain the pitfalls and solutions when dealing with events ordering.

Measuring Kafka uptime

Measuring Kafka uptime

Discover how Michelin teams measure Kafka uptime.

Legacy integration, a story of modernisation

Legacy integration, a story of modernisation

Discover the challenges faced by Michelin teams to transform a 15 years old legacy system into domain-oriented streaming data source.

Exponential Information Systems for a Data-Driven World

Exponential Information Systems for a Data-Driven World

We live in times of accelerating changes fueled with “exponential technologies”. “Exponential Information Systems” is all about constant adaptation for the information system. This article details it and show how it can contribute to a data-driven backbone towards a data driven company.