Data Science
While the field of data science is not tied directly to Big Data, advances in one tends to produce advances in the other. Big Data increases our ability to harvest and process data, while data science allows us to dig into it for insights.

Data-driven Marketing Insights at your Fingertips
Does a swipe mean more than click? Does a hover indicate indecision and a firm push mean certainty? As touchscreens begin to dominate internet interaction, can we learn more from a human gesture than we did from the click of a mouse? And if we can, what are the benefits?

Securing Competitive Advantage with Machine Learning
Business dynamics are evolving with every passing second. There is no doubt that the competition in today’s business world is much more intense than it was a decade ago. Companies are fighting to hold on to any advantages. Digitalization and the introduction of machine learning into day-to-day business processes have

Four Strategic Differentiators of an Enterprise Knowledge Graph
With its unlimited size, an Enterprise Knowledge Graph contains all of an organization’s data — structured, unstructured, internal or external — presented as trillions of interlinked facts made available in any combination, on-demand to approved users. The Enterprise Knowledge Graph enables organizations to take advantage of in-memory computing at cloud-scale

When Data Science Alone Won’t Cut it
I recently read an article (paywall) in the WSJ about Paul Allen’s Vulcan initiative to curb illegal fishing. It’s insightful and sheds light on Big Data techniques to address societal problems. After thinking on the story, it struck me that it could be used as a pedagogical tool to synthesize data science

AI – The Present in the Making
For many people, the concept of Artificial Intelligence (AI) is a thing of the future. It is the technology that is yet to be introduced. But Professor Jon Oberlander disagrees. He was quick to point out that AI is not in the future, it is now in the making. He began by mentioning Alexa,

Why large financial institutions struggle to adopt technology and data science
Data innovation and technology are a much discussed but rarely successfully implemented in large financial services firms. Despite $480 Billion spent globally in 2016 on financial services IT, the pace of financial innovation from incumbents lags behind FinTech which received a comparatively puny $17 Billion in investment in 2016. What

Graph Visualization with a Time Machine
Franz Inc., an early innovator in Artificial Intelligence (AI) and leading supplier of Semantic Graph Database technology for Knowledge Graphs, recently announced Gruff v7.0, the industry’s leading Graph Visualization software for exploring and discovering connections within data. Gruff provides novice users and graph experts the ability to visually build queries and explore

Why Businesses Should Embrace Machine Learning
In 2016, Google’s net worth was reported to be $336 billion, and this is largely due to the advanced learning algorithms the company employs. Google was the first company to realize the importance of incorporating machine learning in business processes. And the technology powerhouse doesn’t stop at any given point; it keeps

Performing Nonlinear Least Square and Nonlinear Regressions in R
Linear regression is a basic tool. It works on the assumption that there exists a linear relationship between the dependent and independent variable, also known as the explanatory variables and output. However, not all problems have such a linear relationship. In fact, many of the problems we see today are

Big Data is changing the future of NBA scouting
Big data and sports analytics are changing the ways many things in sports have traditionally been done. They are allowing for new processes that have the potential to alter the way that organizations conduct their scouting. This is because data science and sports analytics are opening up new data points