Data Digest: Data Science without Data Scientists, Object Store, Data Center Sites, and Limiting Shadow IT
Self-service data science can be achieved without a data scientist, plus pros and cons of object storage in the cloud versus in-house, locating your data center to survive data onslaughts, and limiting shadow IT.
You Don’t Need a Data Scientist for Effective Data Science
(Source: Datanami)
The new hype involving data is behind the mystical data scientist. Every enterprise has to have one, right? Wrong. This article proves that self-service data science is achievable and gives basic tips on effective big data usage without a data scientist.
Pros and Cons of Object Storage on the Cloud vs. In-House
(Source: Computer Weekly)
Object storage is a useful system that is widely misunderstood in the modern enterprise. This article gives a rundown on what the term actually entails before launching into an in-depth discussion about the pros and cons of building your own object storage system versus hiring a cloud provider to make one for you.
Data Center Location Crucial to Surviving Data Onslaught
(Source: Data Center Knowledge)
A majority of data has been created in the past few years. Even more data will be created as the IoT is implemented. For enterprises, this increase in data is a huge boon, but only if they have the storage space to use it. This article looks forward to the upcoming data boom and hints at what might help enterprises get accustomed to it.
Limiting Shadow IT in the Enterprise
(Source: Network Computing)
Shadow IT is a major worry for CIOs, and with good reason, but it is not impossible to control. This article provides background on the history of shadow IT and shows how to control these projects quickly and efficiently.
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Quint Turner is an editorial intern at TDWI and an undergraduate English student at Skidmore College. Follow his blog at pungry.com.