Yesterday marked my first day in the Data Engineer Nanodegree course offered by Udacity. After thinking a lot on how to best equip myself and enrich my knowledge in the world of Big Data and taking the steps towards it, this course came along talking about THE essential things that I wanted to learn – Cloud data warehouses, Spark and Data Lakes.

What further sealed the deal was I am working on a project where we are using Spark and Data Lake as well. However, it is being handled by a separate team. My involvement so far has been to the extent of writing Impala queries, creating data structure, testing the sqoop queries and occasionally query tuning by looking at the logs to understand which partitioning is better. I reasoned that doing this course will give me a better ammo to pitch myself to get into the Data Lake team. Time will tell (fingers crossed)

I have been longing for an opportunity to pivot my career from the traditional BI to Data Engineering on Big Data Platforms. Here is a course that not only promises to teach the nitty gritties of being a Data Engineer with a proper structured methodical teaching but also help with shaping up my career via services like resume editing and LinkedIn page setup. Long way to go for that.

So here is what my Day 1 (yesterday) felt like so far- Absolutely wonderful!
In the first few videos I have really gotten to know what Data Engineer really means and what other titles actually mean and how they stack up.

What resonated me a lot was this article that was one of the materials to read up. It spoke volumes to me as this was exactly the path I had been following all through my career. I started off writing ETL packages via SSIS on traditional OLTP – OLAP databases, designing cubes off of it, designing and developing reports based on it.

All these have stopped about 3 years ago and it was only a year ago, I am completely off it. I am now working on data sources which are disparate in nature or are built on the Data Lake. This is a brand new world for me and am loving every part of it. The challenges are different, more exciting and there is SO much more to be done.

Looking at the evolution of how data has proliferated and how the traditional RDBMS technologies are not sufficient to cater the growing needs of business, I am happy to see the organic growth in me. Of course, to be where I am today, the forces that have shaped me are largely due to the work done in BI but stepping into new future I need more ammo.

Coming back to the course, I started off with Data Modelling basics and some intro into PostgreSQL.

Next post would be more structured. The purpose of this post with # tag is to motivate myself to read every day and share my thoughts on my learning.