Today more than even, every business is focusing on collecting the data and applying analytics to be competitive.Big DataAnalytics has passed the hype stage and has becom...
Today more than even, every business is focusing on collecting the data and applying analytics to be competitive. Big Data Analytics has passed the hype stage and has bec...
Outdated, inaccurate, or duplicated data won’t drive optimal data driven solutions. When data is inaccurate, leads are harder to track and nurture, and insights may ...
Data Denialism A common scenario that data analysts in general encounter is what I like to describe as “data denialism”. Often, and especially while consultin...
I describe here an interesting and intuitive clustering algorithm (that can be used for data reduction as well) offering several advantages, over traditional classifiers:...
Data is important. It is not a secret for anybody. We can even paraphrase famous saying mentioning that “who owns the data, owns the world”. And if you are a business...
Data Science and DevOps Convergence The primary mission of DevOps is to help the teams to resolve various Tech Ops infrastructure, tools and pipeline issues. At the other...
Leveraging the use of big data, as an insight-generating engine, has driven the demand for data scientists at enterprise-level, across all industry verticals. Whether it ...
A long, long time ago (maybe 10 years) the data analytics industry was fairly easy to define and track. Back in that pre-historic era SAS was considered the gold standard...