Flask on AWS Serverless: A learning journey - Part 2
About 3 years ago I learnt some basic Python, which I've used almost exclusively to
I never really understood the Big Data hype. Its data, but lots of it, so you need special ways to deal with it. Big deal!
But this article about how twitter processes large amounts of data really got me excited. This post too explains all the moving parts in big data, which I had no idea about before this (I heard about Hadoop once or twice)
What made it more relevant for me was this article about how big data and this fancy-named software is actually used. This is the best part:
The data science team embeds itself with the product team and they work together to either prove out product managers’ hunches or build products around data scientists’ findings. In 2013, Garten said, developers should expect infrastructure that lets them prototype applications and test ideas in near real time. And even business managers need to see analytics as close to real time as possible so they can monitor how new applications are performing.
Now for the last few weeks I have been prattling along about relevance: may be even re-inventing yourself and learning new skills. So perhaps Big Data is a good thing to learn and get into. And its not only just whitepapers and vapourware - the industry has a real need for these skills. The question is how long will a person with typical current skills, SQL in this case, be relevant in tech industry if these new Big Data systems are becoming more prevalent. Will a typical RDBMS and SQL become the next COBOL very soon?
There is real world training as well from Udacity(Cloudera), Coursera and EDX to help a person build these skills while still in his old job.