There is growing demand of data scientists in every organization. For growth of any business enterprise there is need to evaluate data in order to streamline the strategi...
In a prior post I outlined some thoughts on the outlook for the data analytics sector and referenced a database I prepared of analytics companies. At the time the list ...
Originally posted on Analytic Bridge By Dan Kellett, Director of Data Science, Capital One UK Disclaimer: This is my attempt to explain some of the ‘Big Data’ co...
originally posted by the author on Linkedin : Link It is very tempting for data science practitioners to opt for the best known algorithms for a given problem.However...
Summary: Continuing from out last article, we searched the web to find all of the most common myths and misconceptions about Big Data. There were a lot more than we t...
One of most excruciating pain points during Data Exploration and Preparation stage of an Analytics project are missing values. How do you deal with missing values –...
Summary: It’s become almost part of our culture to believe that more data, particularly Big Data quantities of data will result in better models and therefore better ...
For almost as long as we have been writing, we’ve been putting meaning into maps, charts, and graphs. Some 1,300 years ago, Chinese astronomers recorded the position of...
The Riemann Hypothesis is arguably the most important unsolved problem in mathematics. It falls into an area called Analytic Number Theory which is essentially number the...
Summary: There is a common misconception that data is the enemy of intuition. It’s true that sometimes our clients are misled by their preconceived notions. But all...