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Best of Upside's Data Digest

Articles look at data science don'ts, big data vs. smart data, hooking an audience with data storytelling, and open source's role in IoT development.

• By Quint Turner
• April 27, 2016

Developing Skills for More Efficient Data Science
(Source: Dataversity.net)

Becoming a data scientist requires a large array of skills, but determining which skills are the most important may depend on who you ask. This article summarizes multiple sources to attempt to determine the primary skills needed in the data science field.

The Difference Between Big Data and Smart Data
(Source: Techrepublic)

Although big data receives a lot of attention right now, you can classify data in more ways than simply big versus small. The author of this article makes a different divide: big data and smart data. He explains how they are different and how to stay focused on overall data strategy.

How to Hook an Audience with Data Storytelling
(Source: Business 2 Community)

Visualizations are only one part of data storytelling. Once you understand the storytelling potential in your data, you will see many opportunities for content creation. This article gives you five ways your enterprise might turn your data into stories that your audience will love.

Data Scientist Don'ts
(Source: Kdnuggets)

The popularity of data science has prompted lots of people to get jobs as data scientists. Because the role is often poorly defined, prospective employers of data scientists may run into trouble. This article explains 10 traits a good data scientist should never have.

Open Source Key to IoT Development
(Source: Designworldonline)

The Internet of Things is growing every day, but the speed of development is held back by siloed solutions and compatibility issues. This article recommends a combination of ecosystem standards and open source platforms and frameworks to help all IoT development advance.