Thursday, July 9, 2020
Gregory Piatetsky and Shashank Lyer have begun to answer one of the most asked question facing data science practitioners: Which tools work with which other tools? If I had a dollar for every time this question was asked of...
This is the first in a series of screencasts designed to demonstrate practical aspects of data science. In this episode, I will show you how to integrate R, that awesome awe inspiring statistical processing environment, with Hadoop, the master...
Companies continue to struggle with how to implement an organic and systematic approach to data science. As part of an ongoing trend to generate new revenues through enterprise data monetization, products and services owners have turned to internal business...
Data science is much more than just a singular computational process. Today, it’s a noun that collectively encompasses the ability to derive actionable insights from disparate data through mathematical and statistical processes, scientifically orchestrated by data scientists and functional...
At the request of a friend, I recently reviewed the article "Your Math Is All Wrong: Flipping The 80/20 Rule For Analytics” by John Thuma. It is a good article, but incomplete and bit misguided. Thuma argues that we...
The current working definitions of Data Analytics and Data Science are inadequate for most organizations. But in order to think about improving their characterizations, we need to understand what they hope to accomplish. Data analytics seeks to provide operational...
Data science is changing the way we look at business, innovation and intuition. It challenges our subconscious decisions, helps us find patterns and empowers us to ask better questions. Hear from thought leaders at the forefront including Growth Science,...
There is a lot of discussion around how data sciences and data analytics differ, from the tools that are used to the methodologies that are employed. Two useful perspectives are to look at the differences (what separates them) and...
A common data exploration came up while talking with a British colleague in the advertising industry on Friday, how many independent subject areas should be investigated (1, 10, 100, …, N) in order to have a statistically significant chance of making a...
In the article "46 Critical Capabilities of a Data Science Driven Intelligence Platform” an original set of critical enterprise capabilities was identified. In enterprise architecture language, capabilities are "the ability to perform or achieve certain actions or outcomes through a set...