WaKED-CO (Watch of Knowledge on Emergent Diseases COVID-19) is an initiative launched in record time — deployed just a month after developing a prototype — under the leadership of the health service within the Ministry of Armed Forces in France. The project had one core mission: to make it easier to research the literature around the COVID-19 crisis.
In this blog I’m exploring the issues that will guide senior leaders in Government this year as they continue their transformative journey towards digitalisation, remote work, cloud migration and a data-driven approach to public services.
I have seen many junior data scientists and machine learning engineers start a new job or a consulting engagement for a telecom company coming from different industries and thinking that it’s yet another project like many others. What they usually don’t know is that “It’s a trap!”. I spent several years forging telecom data into valuable insights, and looking back, there are a couple of things I would have loved to know at the beginning of my journey.
Enhancing the customer experience and boosting revenue with the power of analytics are key concepts for telecom operators in today’s ultra-competitive business environment. Many telecoms are going through transformation of their system architectures and stacks to change how they operate and manage their day to day operations as well as their strategies and planning for what comes next.
What does Netflix, eBay and Walmart have in common? They all use Elasticsearch. Elasticsearch is a real-time open-source distributed search and analytics engine built on top of Apache Lucene™, a fulltext search-engine library and developed in Java. Elasticsearch started as a scalable version of the Lucene open-source search framework that uses a structure based on documents instead of tables and schemas and comes with extensive REST APIs for storing and searching the data.
During an InfluxData internal hackathon, I was looking to work on a project that would help me strengthen my Telegraf and Flux skills. I also wanted to use InfluxData’s Giraffe to visualize my project in a React application. After reading Sean Brickley’s blog post on tracking the International Space Station with InfluxDB, I was inspired to build on this idea.
Despite a halt in travel in 2020, InfluxData made incredible progress reaching users around the world through the new InfluxData Authorized Channel Partner program. The program features a robust ecosystem of distributor and reseller partners that help to support InfluxDB users around the world. In 2020, we welcomed 23 channel partners, including three regional distributors and 20 resellers in the Asia Pacific, EMEA and North American regions.
When we announced our license change for Elasticsearch and Kibana, moving the Apache 2.0-licensed source code to be dual licensed under both the Elastic License and SSPL, we also mentioned we would work closely with the community on a simplified and more permissive version of the Elastic License. I am happy to share the results with you. The Elastic License is already widely used.
Elasticsearch 7.10 made configuring the lifecycle of your data less complicated. In this blog post I’ll walk through some of the changes, how to use them, and some best practices along the way. Data lifecycle can encompass a lot of stages, so we’ll touch on.
