I’ve taken up learning to sew with a machine just for fun and to break up the home office vibe these days and yes, home office because of COVID-19.
As it turns out, I had quite a collection of fabrics and pre-loved batik serviettes and such which I have started re purposing into pot holders and cushion covers. I’m not quite at the haute couture stage of my creations…
What’s nice is that each item is mostly pre-loved and has a story of when and where the fabrics, ribbons and so forth were either bought or were a gift.
So… or sew… it’s like going down memory lane while the machine is chugging along. The machine is a Husqvarna 5710 – pre loved as well – so my environmental footprint is quite small.
Anyhoo. I plan to keep track of the items and how they were made in my hobby tool de jour, Elasticsearch.
Here is the placeholder “Sew Good” page that will have more info.
Looking forward to playing around with how to visualise it all!
I have a strong interest in big data, analytics and dashboarding.
Therefore I started digging into how data gets into Kibana, as previously this had been done for me, and I was simply searching, analysing and visualising the data.
The more I dug, the more I realised I did not know.
Writing as I go
As per my previous blog post, I started writing a book along my journey. This helped me to help me learn and understand my weak areas.
The book is now called:
FANTASTIC ELASTIC
Level: Beginner
An interactive reading experience for data fans!
My Journey to Visualise Eurovision winners using Kibana dashboards
Follow along to go from no data… to wow, Kibana!
FANTASTIC ELASTIC
Level: Beginner
An interactive reading experience for data fans!
My Journey to Visualise Eurovision winners using Kibana dashboards
Follow along to go from no data… to wow, Kibana!
My book about Kibana is now 80% complete. Which in the software world, means good enough and ready for release into the world, right?
The early versions of this book were over complicated and inaccurate, so I removed both confusing and incorrect information. If you downloaded an earlier version, please delete it and grab a new copy.
I completely updated the book to take a beginner from no data to wow, Kibana!
The title now shows Level: Beginner, and the book is much easier to read and follow along. That is the hope at least!
All feedback welcome.
An Elastic Certified Engineer
Since starting the book, I attended the Elasticsearch Engineer I and II classes, which I highly recommend. I am also now a very proud Elastic Certified Engineer.
Elastic Certified Engineer
I studied a lot to become #ElasticCertified. I also was highly motivated to step into the world of big data and analytics, and I figured picking one tool, Elasticsearch, and focusing on it, would be the fastest and easiest way forward. It was not easy though, just easier than not following their curriculum and documentation, in my opinion.
Writing the book really helped me towards my goal of learning about big data, analytics and dashboarding. It highlighted the many gaps in my understanding, and pushed me to learn and improve.
Thank you
Thank you to the good people of elastic.co, and the many encouraging friends and even total strangers along the way!
The purpose of this article is to layout a fun idea I have, which I hope will help me with my eventual goal of becoming an Elastic Certified Engineer.
What’s in it for you, dear reader?
If you would like to follow along how to make fun and informative visualisations of data, even if you have never heard of Kibana before, and even if you have no data, then this is for you.
🙂
What is Kibana, anyway?
Kibana is a window into the Elastic Stack. It enables visual exploration and real-time analysis of your data in Elasticsearch… [enabling] data exploration, visualization, and dashboarding.
Just in case we don’t share the same hobbies, the Eurovision Song Contest is an annual international song competition, primarily for European countries. It is colourful, kitch, and classy all wrapped in one giant live TV spectacle, and past winners include ABBA (1974) and Celine Dion (1988), with the favourite being awarded the now famous douze points (twelve points) from enough other countries to make them the winner.
Eurovision has been broadcasting since 1956, making it one of the world’s longest-running television programmes, with audience figures of between 100 million and 600 million internationally.
How on earth will I do this?
Things might change as I go, though for now I have outlined the following phases of the project. I have tried to make each phase as realistic as possible, for someone who has never done this before.
Phase 1
Create a raw data file
…perhaps in a google drive spreadsheet that can be exported as a .csv file, for the past 10 years of Eurovision winners. Do some copy/paste manually from sites such as Wikipedia, if I am not able to find some database with this already. Don’t try to make a data scraper or automate this, at this stage
store this in source control, eg github
Install elastic locally on my computer
…at home, and on my laptop, depending on where I am working from. Do not try to create a docker image or store this in source control at this point
Phase 2
Import this data file to Kibana
Create some visualisations
I will probably want to do some data enhancements at this point, such as adding more data, or converting the .csv to SQL or a more viable database solution
… in order to have a package that can be stored in the cloud, and thus used and run by anyone.
🙂
Blog, book, and do. Repeat.
I hope to blog, write and actually do this project at the same time, updating and revising the steps as I go. I hope anyone with an interest in this will be able to follow the steps.
I will write this up in detail on leanpub as I go:
FANTASTIC ELASTIC: My Journey to Visualise Eurovision winners using Kibana dashboards
One more thing…
It would be amazing to get feedback along the way, so that I can make the steps as clear and as helpful as possible, for all dear readers. So please reach out and send any feedback or questions you might have.
After all, Elastic IS fantastic, just like the Eurovision song contest, and I think you will have fun with me on this journey!
ROOT CAUSE: you control your sneaker lacing with an app… the Android version of the app refuses to pair with the left shoe… because the necessary firmware update … [experienced] connectivity problems
ROOT CAUSE: The issue isn’t… with the race strategy software… we found a bug in [an offline] [tool… used to create delta lap times] that meant that it gave us the wrong number… Had Hamilton known, he could have gone faster after his earlier stop to give himself a greater margin.
PREVENTATIVE MEASURES: an extensive analysis had been carried out and processes put in place “to make sure that we don’t have a repeat”
