Analytics Vidhya has been a tremendous journey for us. Today, when we look back at the journey we have covered so far – it makes us feel proud. It gives us a sense of accomplishment – that we have added value to our readers. It gives us a sense of fulfillment – that we, along with our audience go to bed after doing our bit of learning.
We get a kick out of what we are doing – and we love it. We loved it, when we decided to roll-out the Apprentice programme in a matter of few days. We loved it, whenever we designed a way to help people build their analytics career – be it analytics trainings, jobs, interviews or just an article about learning analytics.
During this journey, we have added a lot of articles on a lot of topics. While the tags and categories have helped to provide some structure to this madness – it is becoming difficult for new people to discover the best of our articles easily. Hence, we decided to create this page. This page will serve as an index to some of our best articles on the site. This is by no means an exhaustive list.
We will continue to refresh this page regularly as we write more. If there are topics and articles – you would want us to write more on – feel free to mention it in comments below.
Analytics Career related articles:
These articles contain advice around how to start your career in Business Analytics and once started, what are the best ways to stay updated on Analytics to be on top of your game.
For people starting analytics career:
- How to start a career in Business Analytics?
- Should I become a data Scientist?
- How to become a data Scientist?
- Planning a late career shift to Analytics / Big data?
- Common myths about a career in Business Analytics – Busted
- The lack of anlaytics work experience and how to overcome it?
For people already in Analytics Industry:
- Must read books:
- Training recommendations, PyCon videos
- How to train your mind for analytical thinking?
- How to become an Analytics Rockstar?
- Interview with Top Kaggler and Data Scientist
- Interview with Srikanth Velamakanni, CEO – Fractal Analytics – Part I, Part II, Part III
- Five habits of highly successful analysts
- Taking a new job in analytics – ask these 5 questions first
- 8 rules for new age analytics learning
Analytics Interview Preparation articles:
- How to identify a good (and a bad) Business Analyst?
- Definitive Guide to analytics interviews
- How freshers can ace interviews for Business Analytics roles?
- How to crack a Guess estimate?
- Interview case studies
- Commonly asked interview Puzzles I and Puzzles II
- Common technical Questions in Interview (SAS I, SAS II, R)
Analytics Frameworks:
These articles includes tips and several best practices to improve your analytical thinking
- The art of structured thinking and analyzing
- How to improve your structured thinking?
- Importance of segmentation and how to create one?
- Business Case studies (part I, part II, part III)
- How to apply web analytics for e-commerce websites?
- How do banks identify the next best product need of its customer?
- Limitation of Pre vs. post analysis and importance of testing?
- Questions to ask while designing A / B tests?
- How to create financial models flawlessly?
- Four rules to create insightful and actionable reports
- How anaytics helps Organizations become more customer centric?
- Segmentation of customers for effective implementation of analytical projects
Business Analytics tools:
These articles contain tips and tricks on various tools used in Business Analytics
SAS:
- Joining / merging in SAS
- Productivity enhancing tips for Enterprise Guide
- All you want to know about SAS Macros (Introduction, conditional statements, functions)
- SAS Analytics U Review
R:
- How would an analyst use Facebook?
- Who is the world cheering for – FIFA world cup? (mining Twitter)
- How to build a word cloud using R?
- Simple framework to build survival analysis model in R
- How to extract information from Unstructured text
Python:
- Baby steps in Python
- Mining YouTube
Business Intelligence tools and data visualization:
These articles contain tips and tricks to gain proficiency in various Business Intelligence tools
Qlikview:
- Creating a simple and effective Sales dashboard (with Qlikview) – Part I and Part II
- Set analysis – simplified!
- AGGR() functions
- Creating Geo-location charts in Qlikview
- Customized reporting in Qlikview
- How to create waterfall chart in Qlikview?
- Review: Qlik Sense desktop
Data Visualization:
- Upcoming trends in data visualization
- How to create compelling analytical stories using Infographics?
Others:
Predictive Modeling and clustering
These articles cover various algorithms and techniques used in predictive modeling and clustering
- Basics of Predictive Modeling
- Regression related:
- Introduction to Random Forests – simplified
- Comparing CART to Random Forests
- Market Basket analysis
- Markov chains – simplified
- Introduction to Artificial Neural Network – simplified
- Introduction to k-nearest neighbours
- Support Vector Machines – simplified
- Survival Analysis simplified
- Getting your clustering Right
- Building models on seasonal data
Big Data:
- What is Big data and how is big data architecture different?
- Loss of privacy or boon by Big Data?
- What is Hadoop? – simplified
- What is MapReduce? – simplified
Others:
That looks like a lot of work – and it truly has been. We will continue to put more and more informaiton on the subject out there and make sure it is of top notch quality. Here are 2 things, we would want you to do to get your brain cells working:
- Now that you have seen one way to organise this information about various articles on Analytics Vidhya – can you think of some more ways to represent this information? For example, one interesting view can be to change the size / color of fonts of titles mentioned in this list based on number of vies or user engagement and see what it throws up. What other views can you think of?
- If there are other topics on which you would want us to write on or include in this list, please add them in comments below and we will action on them.
