DSC Webinar Series: Columnar Databases: Best Choice for Real-Time Analytics
Business today often calls for analyzing millions or even billions of rows of data on demand and in real time. And although relational databases are unmatched for transac...
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DSC Webinar Series: How the Role of Data Prep & ETL is Evolving
As businesses have modernized data processes to prioritize self-service and agility, the need for more “analysis ready” data, faster, has led to the advent of modern ...
7 Steps to Build a Data-Driven Culture in your Organization
A data-driven culture does not happen overnight. Very deliberate & tangible steps need to be taken to foster a data-oriented culture in the following order: 1) A sing...
5 Principles for Big Data Ethics
Greek Philosophers Busts, College of Arts & Sciences, Miami University Big data analytics raises a number of ethical issues, especially as companies begin monetizing ...
How to pay your data scientists to increase retention
Scene from the TV series Pablo Escobar Promising data-minded individuals are easy to spot from the distance: curious detailed-oriented thinkers, energized by uncertainty,...
Can Artificial Intelligence replace Data Scientists?
Steve Urkel and Urkelbot, whose intelligence doubled every 2 minutes. Image Credit: ABC’s Family Matters Steve Urkel from the world-famous ABC’s sitcom Family Matters...
Why Data Governance should be on the CEO’s Plate
Traffic policewoman in Pyongyang World-famous Pyongyang policewomen, who are reportedly picked by North Korea’s Supreme Leader himself, have garnered a cult followin...
New Book : Big Data in Engineering Applications
BOOK : Big Data in Engineering Applications, SPRINGER. Editors: Roy, S.S., Samui, P., Deo, R., Ntalampiras, S. (Eds.). Dear All, The most anticipated book titled “B...
Big Data and Machine Learning (Google case)
The database is like a library building … every book (information) that enters must be properly placed (processed systematically), when a number of books come then ...
Reading List for Data Scientists
Here are some recommended books for data science practitioners, covering machine learning, deep learning, business intelligence, forecasting, text analytics and much more...