Today’s economy, led by advances in changing economic cycles and communication, relies more on data science. Big data techniques, a significant component of data science and business intelligence, are utilized to harness vast amounts of data quickly for analysis. Increasingly, the volume and availability of granular data, coupled with highly specific and powerful analytical tools such as R and SAS drive organizations toward making more accurate predictions with the prospect of increasing sales and generating organizational efficiencies. These predictions help enable efficient supply chains, driving down costs for producers and leading to more expedient delivery of products and services for consumers.
“Tea is an act complete in its simplicity.
When I drink tea, there is only me and the tea.
The rest of the world dissolves” – Thich Nhat Hanh
A picture is worth a thousand words, and numbers have the capacity to summarize a picture with just a few statistics, especially in today’s data driven world. The right perspective is necessary for the right kind of analysis. It is not just employing the right technique , but rather, it’s implementation determines the efficacy of the analysis and the relevance of the insight. Continue reading There’s No Free Lunch, Stupid
R is a versatile and powerful programming language that enables the user to perform various types of statistical and data analyses. Like with any other tool, R’s potential largely lies in the user’s knowledge of the extent of its capability. Having used R extensively over a period of time, we have some useful tips we think will benefit the beginner and the seasoned R user alike. Because R is open source, its adaptation has increased exponentially. Several users without any programming or computer science background have been able to benefit from it. Being a newcomer to programming and scripting languages myself, I have fallen prey to several programming and scripting fallacies. Over the course of time, thanks to a multitude of help from experienced colleagues, and to the sea of information readily available on the internet, I have been able to learn several programming etiquettes which I wish I knew sooner. Continue reading Decluttering R
Visualizations are a great data exploration technique. Our human minds are better able to understand and retain visuals than scripts or text. Visualizations, apart from giving us a good general overview of the data, entail us with an intuitive understanding of the distribution of the dataset and its trends.
Continue reading Dispelling illusions using Visualizations
The aim of this paper is to study the search behavior of users, based on their Google search query terms, and to find similarities between search behaviors of a pool of users. We want to identify the types of searches that are central to other searches. These searches would ideally lead to searches of other kinds, and it would be conducive to invest in Google ads for searches of this type. Continue reading Tracing Search Behavior using Social Network Analysis