Massachusett Open Cloud highlights rising demand for big data services

Enterprises and governments are increasingly drawn to open cloud storage systems as they seek to streamline costs and facilitate better interoperability between IT components. The Massachusetts government recently teamed up with Boston-area research universities to create an open cloud solution, and its move underscores broad organizational interest in deriving more value from big data, often through combinations of open source software and industry-standard hardware.

Massachusetts develops open cloud based on OpenStack
The Bay State's project is called the Massachusetts Open Cloud and it complements the similar Big Data Initiative, which governor Deval Patrick launched May 2012. According to GCN, Massachusetts forewent proprietary solutions in favor of open source infrastructure because it wanted to create a marketplace in which software and services could be exchanged and resold by many different vendors.

MOC is hosted at the Massachusetts Green High Performance Computing Center, with additional funding from businesses such as Cisco and research universities such as Harvard and MIT. MOC's contributors are currently working on infrastructure based on OpenStack and Red Hat technologies, as they aim to provide accessible features such as IaaS, big data analytics and on-demand virtualized resources.

Interested organizations, especially ones that are smaller and trying to get their cloud operations off the ground, may be able to save time and money on application development by using MOC. The cloud hardware at MOC may also be a useful platform for startups seeking to make services available to a wider audience.

MOC development demonstrates growing interest in big data projects
Massachusetts' projects come at an opportune time, when interest in big data is ramping up among enterprises. IDG recently published the results of its 2014 Enterprise Big Data research, finding that analytics projects continue to be top priorities for many companies. Interest was most pronounced among organizations with more than 1000 employees, but even 40 percent of small and midsize businesses were keen on big data adoption.

Across the board, data volumes are rising for enterprises, putting pressure on them to implement scalable cloud storage solutions. Total data managed per organization may increase more than 75 percent over the next 12 to 18 months, rising to 280TB as workers utilize more documents and email and IT sets up additional databases to keep up with demand.

Half of IDG's respondents were working on big data projects, with 12 percent having already deployed one. The top reasons for pursuing these initiatives included refining and speeding up decision-making processes, coming up with new products and revenue streams and acquiring additional customers.

"The potential benefits from analyzing data are limitless and three quarters of organizations predict that big data will be in mainstream use within the next three years," stated IDG Enterprise CEO Matthew Yorke. "It is not surprising that 70 percent of enterprise organizations are investing in big data, compared to 56 percent of SMB organizations. Some of the biggest winners in this, within enterprise organizations, will be marketers who partner with IT to better understand their customer data, activities and drivers."

Still, there are challenges that could set back some big data projects. Enterprises are mindful of security requirements, as well as budgetary constraints that could limit procurement of new hardware and software.

To overcome these obstacles, enterprises are doing things such as encrypting data and controlling access to critical IT assets. On top of that, more than 60 percent of respondents stated that they stored some data on-premises rather than in the public cloud. While scalable infrastructure is the key to supporting big data, not all of it will come from public cloud vendors, and the private cloud will remain a core part of enterprise architectures.

2014-01-10T14:55:35+00:00

About the Author: