Now Working On A Big Data Science Project

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This month is turning out a very good and busy one for me. I am fully engaged on lots of projects, many are training and a couple are data science projects.

There is one in particular that is going to be the biggest data analysis project I have ever taken up. It will involve daily warehousing of data across Twitter and Google. I would have to probably buy the unlimited Twitter data search access (called firehose). Already contacted the section of twitter in charge of that, Gnip.


Unfortunately, I can't share the details of the project due to its commercial nature. But I should be learning a lot new things that I can safely share with you all.

I am also getting better at using R and Python for very complex analyses. I managed to fix one big issue I have been facing for over six weeks now with my R script scheduling. Turned out that it was relative file path issue that was messing everything up. And I was already thinking it had something to do with R since I had done similar scheduled scripts with Python without any problem. It was a very small problem that has cost me a lot of lost value (days the script didn't work as intended).

These are the types of issues you'll never find in books or from tutorial videos. And it is the main thing I keep telling people wanting to learn data analysis. The only genuine way to learn it is by doing. 


1 comment:

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