Scott Murray, a designer and educator, writes D3.js tutorials and an SVG primer, and is the author of a book on data visualization for the web.
HN commenters recommend his D3 tutorials as clear and intuitive, one preferring them to another tutorial, and point to his O'Reilly book.
There's a lot of stuff under the "Big Data" umbrella: I focused on Hadoop below because that's my focus right now. I'm sure I'm missing some roles here, but the specialities I can think of are:
- getting data out of production systems and transforming it (infrastructure or ETL)
- analytical querying and reporting
- system administration
- machine learning
There's also the wide world of NoSQL data stores, which people lump in with big data, but which require vastly different skills.
The Hadoop VM I linked to above is good for working through exercises for all of the above.
As a starting point, this book[1] walks through the motivation behind Hadoop, and then gets a little into internals and use cases. It's out of date, but you can work through it and get into the right frame of mind, understand HDFS, etc. It's a good starting point.
AMP Camp (that I linked to above) is an introduction to Spark for people with a little Hadoop experience. Spark is getting a lot of attention, you could run into it in a number of roles.
If you're going to be planning the whole pipeline, or doing any sort of infrastructure role, I recommend Hadoop Application Architecture[2] for more modern tools and design patterns. This blog post[3] is a pretty good overview of distributed logs, which are essential for horizontal scale. Understanding Kafka and ZooKeeper is really useful for infrastructure roles, maybe less so for admins.
If you're planning to be in the reporting layer, having a deep…
Nice timing. I just found this website the other day and love it. I've just recently been getting into data visualization and have fallen in love with d3.js. Another good resources is http://alignedleft.com/work/d3-book/. Maybe a bit introductory for some of the smartypants on HN but I've been away from front end dev for a while and so find blasting through the chapters pretty helpful. Hilarious tone, also. Combined with d3indepth.com's examples and the API docs I've been able to get a good grasp of d3.js.
It's an API for building custom charts. It's a huge step up from having to fully 'roll your own'. If you have to do any kind of vis that isn't available in the various off the shelf libraries, you can put it together with D3 easier than you could if you fully DIY a solution. It's well thought out but you have to use it for that to be more obvious. This book (by the D3 author) got me started, it's worth the hassle of learning [0].
[0] http://alignedleft.com/work/d3-book
You might have already come across these, but I figured posting them here might help nonetheless.
Start here - http://bost.ocks.org/mike/join/ This gives you the neccessary understanding of how D3 works (from mbostock himself).
I found this tutorial to be pretty good -
http://alignedleft.com/tutorials/d3/
He also has a book out there with O'Reilly.
Here's another good one
http://2011.12devsofxmas.co.uk/2012/01/data-visualisation/
Hope that helps!
This was my first attempt at Data-visualisation using d3. I've done a few things with GoogleVis and R, the one is awesome for the web the other is awesome for its flexibility, D3 is awesome for both. I was also pretty much a novice to JS and CSS, I highly recommend AlignedLeft's tutorials http://alignedleft.com/ if like me you start from scratch with this.
Back in the day I learned d3 by reading a tutorial by Scott Murray [1]. It was perfect for me as it also covered the basics of javascript itself, which I hadn't used prior. It's written for v3 of d3.js, so a bit out of date now, I still wanted to give it a shout out - thanks Scott!
[1] https://alignedleft.com/tutorials/d3