Now Learning Predictive Data Modelling

I recently got a consulting project that will require predictive modelling. I spent this week trying to get a feel of what the client requires from me; I spent 4 days (closing at 8pm) at the company just to get a good grip of the work scope. And now I have a big enough motivation to learn predictive modelling.

Yesterday, I bought the following books:

1. Predictive Analytics: Microsoft Excel by Conrad Carlberg
2. Applied Predictive Modeling by Max Kuhn, Kjell Johnson
3. Data Science for Business: What you need to know about data mining and data-analytic thinking by Foster Provost, Tom Fawcett
4. Data Smart: Using Data Science to Transform Information into Insight by John W. Foreman
5. Predictive Analytics For Dummies (For Dummies (Business & Personal Finance)) by Anasse Bari, Mohamed Chaouchi, Tommy Jung
6. Decision Analytics: Microsoft Excel by Conrad Carlberg
7. Statistical Analysis: Microsoft Excel 2010 by Conrad Carlberg
8. R for Everyone: Advanced Analytics and Graphics (Addison-Wesley Data & Analytics Series) by Jared P. Lander
9. Learn R in a Day by Steve Murray

image: datasciencecentral.com

You might be amazed by the number of books and ask if I will be able to read them all. The truth is I'm not bothered about reading them all immediately; the trouble is that when I want to learn a thing I don't buy just one book. Even when I do google search, I open up to 10 different results before I begin reading one. It's really funny, especially when I'm searching for the meaning of a word. I would open results from thefreedictionary.com, vocabulary.com, dictionary.reference.com, merriam-webster.com, en.wikipedia.org and urbandictionary.com. And investopedia.com sometimes. Just to learn the meaning of a word. Even a word I could have correctly guessed its meaning. And I use the same approach in learning from books; I buy many books.

So I've now officially joined the Big Data train. I will be learning to make predictive models and do all those cool stuff that has made Big Data the new hype. And I will not be working on dead sample data. I will be working on live data that will drive business decisions and deliver value for everyone involved. 

I have tried learning R language and statistical analysis a few times before but I never had a commercial reason to give it my usual obsessive focus. The training I signed up for were all taught by college professors and I saw little commercial drive to learn it like I did Excel. But now I'm into it. I will be reading my eye balls out and putting to practice all I read as I have a soft deadline to meet. I have been told to help make the most out of the data bank, so I will be needing to think as creatively and analytically as possible. Both during the day and at night I will be thinking big data. Even in my dreams, like I used to dream of Excel in 2012, I will be dreaming of predictive analysis. I will be turning down some training offers to make out more time for this. Training has never been a big piece of my original business plan; consulting and building creative data analysis solutions were my original focus. But training is easier to sell and with my level of expertise, I come at a huge bargain. Even while I used to do this part-time, I did mostly Excel macro jobs and special Excel based jobs. I never tried to make money from training, the few people I trained, I trained for free (except 1).

Soon you will begin to see occasional posts on big data and my journey into that exciting world.