Choosing data tools for small and midsize enterprises, adjusting data lakes to increase processing speed, and finding the right data to achieve success.
- By Quint Turner
- November 10, 2016
How election predictions and polls failed, avoid common mistakes in securing network endpoints, and understand the future of big data and emerging technologies.
- By Quint Turner
- November 9, 2016
The RDBMS challenges of the 1980s are being replayed in the world of big data.
- By Luke Liang
- November 7, 2016
What does it take to be a data engineer? A background in software engineering doesn't hurt. Although the number of data engineers doubled from 2013 to 2015, that growth rate far outstripped that of data scientists.
- By Steve Swoyer
- November 4, 2016
How to find value in data that hasn’t been used, what each type of analytics is good for, and making predictions about the future of big data and advanced analytics.
- By Quint Turner
- November 3, 2016
See an updated consolidation of election polling predictions, plus learn how selling data can be a huge opportunity if approached correctly, how to improve the quality of data visualizations, and understand the basic history and current potential of BI.
- By Quint Turner
- November 2, 2016
These articles explain Vs for managing big data, why AI projects are thriving in the cloud, and the environmental pros and cons of cloud computing.
- By Quint Turner
- October 28, 2016
Today’s articles explain the ethical capture and use of geospatial data, what factors are improving predictive analytics, and how to solve common big data challenges.
- By Quint Turner
- October 27, 2016