darren whittingham - Fotolia
How are big data and cloud related? Do big data projects require cloud?
Businesses today can collect, store and access an astonishing array of data. That data could come from tracking a visitor's Web browsing habits to watching in-store shopping traffic -- and everything in between. And this data collection comes from more than just register receipts or software logs. Businesses can collect data from cameras, microphones, RFID readers, wireless sensors and more.
These vast and diverse data stores pose a computing dilemma. Their complexity makes it impossible to use traditional data processing applications, such as databases, to yield meaningful business intelligence. Processing big data demands more than a single desktop or server; it requires thousands of servers running massively parallel processing software. In other words, big data requires big computing infrastructures.
Meanwhile, businesses are trying to reduce their IT footprints and investments. It's hard to justify storing terabytes or petabytes of data and operating additional servers to analyze that data. Instead, businesses offload the necessary storage and computing resources for big data -- which is where cloud comes in.
Cloud isn't the only option for big data storage and analysis, but it's definitely a good one. To help organizations collect -- and ultimately make sense of -- massive amounts of data, cloud provides scalability and flexibility.
Big data analytics, however, doesn't require cloud computing; it's an outsourced computing model that facilitates it. Instead of investing in new hardware, organizations can store and process those big data sets in the cloud. To tackle big data analysis, cloud offers enormous flexibility, and can scale and combine with distributed processing software. And when processing is complete, it can also be scaled back or turned off. Businesses only pay for the computing they use, which transforms capital costs into operational expenses -- a core benefit of public cloud computing.
Public cloud, private cloud and hybrid cloud models can all be used for big data initiatives. However, public cloud -- largely due to its pay-per-usage model -- has emerged as a popular option.
Stephen J. Bigelow is the senior technology editor of the Data Center and Virtualization Media Group. He can be reached at email@example.com.
Google cloud expands its big data ecosystem
Big data among top technology trends of 2015
VMware boosts vCloud Air with database management
Dig Deeper on Big data, machine learning and AI
Related Q&A from Stephen J. Bigelow
Just because software passes functional tests doesn't mean it works. Dig into stress, load, endurance and other performance tests, and their ... Continue Reading
Don't neglect form factor as part of your data center server selection. Instead, figure out what type of environment you need and learn which server ... Continue Reading
Learn how load balancing in the cloud differs from a traditional network traffic distribution, and explore the different services available from AWS,... Continue Reading