Data Digest: Shadow Data, Data Hoarding, and Different Types of Data Scientists
In today’s articles, read about the dangers of ungoverned access to “shadow data,” the costs of hoarding every bit of data, and tactics for hiring the type of data scientist that matches your needs.
- By Quint Turner
- June 22, 2016
Shadow IT is a well-known problem in the enterprise, but the new threat on the block is dubbed "shadow data" -- any data uploaded, stored, or shared in the cloud without adequate access control. This article outlines some advice for finding shadow data and keeping it secure.
Read more at Computer Weekly
Thanks to extremely inexpensive storage, many enterprises are now hoarding huge amounts of data "just in case." According to this article, data hoarding wastes money and time. To fix the problem, enterprises need better employee education about realistic data value.
Read more at Datanami
Many enterprises are hiring data scientists only to be let down if the employee is not a good fit. This article describes two broad categories of data scientists and recommends concentrating your hiring search in whichever one best fits your business needs.
Read more at Kdnuggets
Quint Turner is an editorial intern at TDWI and an undergraduate English student at Skidmore College. Follow his blog at pungry.com.