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Our top 10 Data Science articles in 2014

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2014 has been a year of growth for us. We now get 10x traffic compared to what we used to get 12 months back. It gives us immense satisfaction to be able to create something which is helping more and more people every day. We only hope that we could get some more time to create more content for our audience!

Not only we wrote more articles and better articles in 2014, we also started a jobs listing and a trainings listing page

2014

While we are on the brink of entering into 2015, I thought it might be a good time to recap some of the best articles we have written in 2014. Please note that these are articles which were written and read the most in 2014. The analyst in me can not help from pointing out that the articles early in the year have some advantage. But as I said, the later articles were written when we had far higher reach!

So, here are the articles, which were written and read the most in 2014. In order to make the article more interesting, I have included some behind the scene stories along with the articles:

  1. SAS vs. R vs. Python – which tool should I learn?

    This was clearly the best article we wrote this year. It not only helps people compare and decide which is the right tool to learn, but is also one of the fairest comparison of these tools till date. This article has a few stories associated with it. First of all, I was not sure whether to include Python in this article. I knew that usage of Python is increasing, but I was not sure whether it is mainstream enough! When I look back, including Python in the mix was probably one of the better decisions I made in the year. The article got a lot of appreciation for it’s non-biased view towards all these tools and it continues to be a traffic puller for us. Here is another interesting fact about the article – I added the scores on various attributes at the end as I was not satisfied with the previous version of the article.

  2. Tips to crack a Guess estimate (Analytics case study):

    A must read article, if you are appearing for interviews for the position of Business Analyst. As the name suggests, the article gives you a nice framework and a lot of tips to excel in analytics case studies during interviews. When Tavish first discussed this idea of writing an article on this topic, I wasn’t sure it would come out so nicely! The only reason I agreed to go ahead because Tavish felt very passionately about the topic and said that he can write an awesome article on the topic. Another bet which paid off!

  3. Set Analysis in QlikView:

    Set analysis is one of the most complex, useful and dreaded topic in QlikView. All said, they are also the life line of any good business dashboard. I had some acquaintance with set analysis before I read this article, but this article explains such a complex topic in very simple way using a lot of examples.

  4. How to use AGGR() function in QlikView?

    An awesome article to read, if you have used QlikView for some time. AGGR() functions along with set analysis is what differentiates a pro from a novice! This article continues from the awesome article on set analysis.  are the life line of any good business dashboard. I myself was not comfortable using AGGR() functions in QlikView, till I read this article from Sunil. He has played on his strength here – how to take a complex topic and simplify it to explain it to any lay man!

  5. Must have books for data scientists (or aspiring ones):

    This article is on one of my favorite subject – books. We have a popular article on books from 2013. This was the one for 2014. Each of these books is a treasure of knowledge and are becoming immensely helpful to people learning R or Python by themselves. If you have still not read some of the books mentioned here, check out if you can get some discounts during the holiday season.

  6. Planning a late career shift to analytics / Big Data? Better be prepared:

    One of the most useful article, if you are making a lateral shift to analytics. The article contains a lot of useful advice on what to expect during the transition and how to go about making this career transition.

  7. Performing exploratory data analysis in Pandas (baby steps in Python): 

    I started the baby steps series when my daughter took her first steps. This is one of the best tutorials on use of python (pandas) for performing data analysis. This solves one of the most common problems on Kaggle, but still manages to teach the subject to a new Python convert!

  8. Data Science projects to learn data science:

    This article came straight from the heart! This is how I feel each one of us should go about learning data science. Whether you are new to the field or have spent years in the domain, you might still find an interesting project here. The article provides a good mix of problems across several categories, which are not only fun, but will leave you wanting more of them.

  9. Should I / How do I become a data scientist?:

    Our take on one of the most commonly asked question by wannabe data scientists across the globe. The first article provides our self developed framework to help you decide whether you fit the role of a data scientist. The second article starts exactly where one article ends, how to become a data scientist once you are clear that you should become one.

  10. Definitive guide to prepare for an analytics interview:

    Another article with tons of information – the only resource you need to crack an analytics interview. Do read it, if you are planning career switches in 2015!

These were some of the most popular articles we have written this year. They were instrumental in helping us grow tremendously and continue to bring us traffic. These are just the tip of the iceberg. There are many more articles which would provide you with wealth of information.

Gearing up for 2015:

Hope you found this recap useful. If you want us to write more on specific topics, do let us know through comments below. We will make sure your wish is granted in 2015! Looking forward to hear more from you.

Happy New Year 2015

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3 Comments

  • Ena says:

    Hello Kunal
    I have MBA (Marketing) degree. Now i am working as a desktop support anlayst for a company in canada. How can i choose my career? HOw can i use my Business degree with my IT knowdledge? Should i go for MS SQL or System admin or Network admin or business analyst?
    I seen you provide some good advise in website
    Please help me with your ideas. I am kind of frustrated for my career.

    thanks

  • Sandeep says:

    Hi Kunal,
    I have an experience as SAP BO BI platform administratio. Pursuing BABI at Great lakes.
    I have been offered a job of BI analyst recently at startup. Would an experience as BI analyst be right move
    To further aspirantion as analytics consultant ?

    Regards
    Sandeep

  • Riya says:

    All are great blogs! Thanks for sharing! Data Science is the competitive advantage of the future for organizations interested in turning their data into a product through analytics. Industries from health, to national security, to finance, to energy can be improved by creating better data analytics through Data Science. The winners and the losers in the emerging data economy are going to be determined by their Data Science teams.
    Booz Allen Hamilton created The Field Guide to Data Science to help organizations of all types and missions understand how to make use of data as a resource. The text spells out what Data Science is and why it matters to organizations as well as how to create Data Science teams. Along the way, our team of experts provides field-tested approaches, personal tips and tricks, and real-life case studies. Senior leaders will walk away with a deeper understanding of the concepts at the heart of Data Science. Practitioners will add to their toolboxes.

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