Data Digest: Data Science Pitfalls, IoT Concerns, Convergence of Open Source and Commercial Software
Today’s articles explore major reasons why data science projects fail, 7 concerns with the spread of IoT, and why open source and commercial software options are very similar today.
- By Quint Turner
- June 27, 2016
Effective data science requires more work than gathering data and throwing algorithms at it. This article explains three common problems many enterprises run into with data science projects.
Read more at Dataconomy
This article covers seven major concerns those developing for or using the Internet of Things will face as it gets more popular.
Read more at Datamation
When it comes to enterprise solutions, most people perceive a split between commercial and open source software. This article argues that such a divide is false, and all software has become more open. The only thing that matters now is what software works best for your enterprise.
Read more at TechCrunch
Quint Turner is an editorial intern at TDWI and an undergraduate English student at Skidmore College. Follow his blog at pungry.com.