Best of Upside’s Data Digest
Articles discuss applying predictive analytics to cybersecurity, solving three important data analysis problems, getting value from the Internet of Things, and comparing cloud BI and the traditional data warehouse.
- By Quint Turner
- August 12, 2016
Using Predictive Analytics in Cybersecurity
(Source: TechCrunch)
Given enough data and the right algorithms, predictive analytics can change the way enterprises approach many problems. This article explains how advances in predictive analytics and machine learning can help predict and detect cybersecurity attacks.
Solutions to Three Data Analysis Problems
(Source: O'Reilly)
In this article, a data scientist shares techniques to address three frequent data analysis challenges: overfitting, hyperparameter tuning, and model interpretability.
Getting Value from IoT
(Source: Forbes)
How can you turn the connectivity of the Internet of Things into business value? Analytics, data management, and staying focused on goals, according to this article.
Security Must Protect the Unknown
(Source: Dark Reading)
Making assumptions about the safety of data or encryption can lead to security breaches. According to this article, seeking information about what you don't know -- what data and processes are invisible, what avenues of access aren't being monitored -- allows you to develop effective, proactive security.
Cloud BI Versus the Data Warehouse
(Source: Information Management)
This article explains how using self-service cloud BI may eliminate some of the inflexibility and inertia of the traditional data warehouse.
About the Author
Quint Turner is an editorial intern at TDWI and an undergraduate English student at Skidmore College. Follow his blog at pungry.com.