The Why What and How of Data Science

WHY Inferential Statistics and Hypothesis testing?? In today’s world, with the abundance in data, every organization wishes to optimize on their products by making it more customer centric. To do that, they need to develop an understanding of the population. In order to understand the population, companies need to categorize customers based on certain parameters like age, education, location, life style, income and so on. But in most cases, it is extremely difficult to collect data for the entire population. That is where the concept of samples and sampling comes into the picture. Sampling is the process of selecting a subset from a population that would be representative of the population. The idea is to perform the analysis on a sample and make inferences about the population. Let us look at a simple example to understand this concept. Consider a case where we want to find the average height of men and women in the city of Cincinnati and compare it to a value that is cl...

Deep Learning!! I have always wondered about the concept of perception i.e. how does our brain understand the objects we see? How does it know the difference between a cat and a dog? How are we able to differentiate people from each other? The most amazing thing is how does the brain identify the same person over the years even when they age? I haven't got answers to most of these questions, but what if I say there are technologies out there today that can do this same task as a human being in terms of perceiving objects? Yes, it has become a reality!! Take for example the iPhone X's face recognition based locking system. Isn't is amazing? There are many more applications of the same technology. When we dig a bit deep into what is the most commonly used technique in these applications, we find that the answer is neural networks. To be more specific, people have started using a neural network based technique called Deep Learning extensively for this purpose. No...

Analytics!! There has been a lot of talk about data and analytics in the past decade. But what exactly is data analytics? Why has it become a buzz word in recent times? If data can help companies make decisions, how can organizations take this approach? Why was this domain not prominent earlier? Being a data science enthusiast and practitioner myself, I wanted to try answering these questions which I have been frequently hearing from people around me. This post is a compilation of my understanding of what is analytics along with my take on the questions in a brief and simple context. WHY Data Analytics?? In the past 10 to 20 years, we have witnessed a tremendous growth in Digitization. Everything around us has been digitized in some form or the other. All these digital transformations have led to a humongous digital imprint in the world which can be used to harness a lot of insights for businesses ranging from retail, banking, manufacturing, healthcare and so on. ...

Hello All - When I look around, I am fascinated by the way the world has transformed over the past decade with the digital revolution and data democratization. Gadgets have become ubiquitous and business decisions are driven by the data obtained from numerous data points available across platforms, impacting a plethora of fields like education, healthcare, retail, banking, sports and so on. Data Science and analytics being the core of this transformation, I am one among those who are fascinated about the field and aspiring to be at the forefront of this revolution. I am an engineer at heart which makes me the guy with a WHY wherever I go. Over the years I have also realized that learning and sharing knowledge is really important in a technical field like data science. I strongly believe that knowledge sharing is one of the most important asset for any individual and in that regard, this series of blog posts are a set of insights that I have gained with respect to Data Science...