Data Digest: Data Whisperers, Big Data Missteps, Data Quality versus Quantity
Today learn what a data “whisperer” is, the top 4 mistakes managers make in data projects, and how to balance quantity and quality in your data collection.
- By Quint Turner
- July 22, 2016
The data scientist may be 2016's hottest job, but 2017's might be the data whisperer. This article explains this new position, which is mostly concerned with translating data analysis through business and human context.
Read more at Datanami
Many enterprises have amassed large amounts of data, but this article claims that actionable insight is often missed because of managers' misunderstandings. The article reviews four common mistakes and how to avoid them.
Read more at Harvard Business Review
When measuring the success of some projects, a large volume of data (such as the number of website views) is generally good. However, not all data gets better when it gets larger. This article discusses why successful big data projects consider the balance between data quality and data quantity.
Read more at Business 2 Community
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.