Best of Upside’s Data Digest
Articles discuss what a data scientist actually does, how data storytelling is more than just visualizations, effective big data alternatives to Hadoop, and adding machine learning to big data.
- By Quint Turner
- October 7, 2016
What a Data Scientist Actually Does
(Source: Forbes)
This article provides a first-person perspective on the core tasks of a real data scientist.
Data Storytelling is Much More than Visualizations
(Source: Datamation)
The key to crafting a strong data narrative lies not in the visuals but in understanding the story. This article is a guide on how to improve the story part of data storytelling.
Effective Big Data Alternatives to Hadoop
(Source: Forbes)
Hadoop and big data have seemed synonymous, but this article claims NoSQL databases may be more effective and less expensive for some big data use cases.
Questioning the Need for a Full-Time Data Scientist
(Source: Business 2 Community)
Hiring a specialized data scientist should not be done blindly. This article asks the important question of whether your enterprise truly needs a full-time data scientist.
Best Practices for Going Digital
(Source: Information Age)
This article offers general guidance on modernizing enterprise systems and considering cloud migration.
Add Machine Learning to Big Data for Best Results
(Source: Information Management)
This article claims that traditional analytics may be too slow to work with big data. It explains how to get started with machine learning to boost your analytics strategy.
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.