News Stay informed about the latest enterprise technology news and product updates.

Predictions for the future of big data architecture

Big data means big hopes. In this #CIOChat recap, read about big data architecture's prospective evolution and how CIOs can leverage service providers.

Big data is among the most-buzzed-about terms in technology of late, and with more chatter comes more questions: What should CIOs consider when making big data investments? How does the cloud factor into big data analytics? In CIOs' continuing quest to make the most of big data, what business intelligence (BI) architecture is most appropriate?

As the big data discussion gains momentum, it becomes clear that the future of big data architecture has yet to be determined. But that hasn't stopped prognosticators from trying to predict the innovations to come. In this recap of SearchCIO's recent #CIOChat on big data architecture, the site's editors, writers and Twitter followers offered their thoughts on how big data will evolve -- and how CIOs can keep up.

What does the big data architecture of the future look like? What stays? What goes?

In addition to discussing the build vs. buy dilemma and the particulars of what today's enterprises should seek in making the most of a big data architecture, #CIOChat participants weighed in with a wave of predictions about what that architecture might resemble and include. Their guesses ranged from expanded databases to repositories for new sources of data to the inevitable role of machines in the numbers-crunching process:

While some participants said that relational databases aren't going anywhere any time soon, others pointed to a more flexible construction and underlined expectations of new standards for managing big data -- including efforts to tone down the complexity of big data architecture and ensure that any long-term lock-ins ultimately benefit business needs:

Making big data more accessible and user-friendly

One CIO participant voiced a fervent hope for more powerful analytics delivered precisely how and when decision makers need them, and predicted that increased attention to user experience (UX) will ultimately lead to more varied and powerful uses of big data:

SearchCIO Executive Editor Linda Tucci inquired which well-known companies might preside over the "big data castle," touching off a dialogue on what it takes for service providers to stand out, as well as where the value of big data will lie:

How should CIOs leverage service providers for big data storage, collection and analysis?

#CIOChat-ters weren't afraid to delve into specifics around their hopes for leveraging service providers to improve the future of big data architecture. The discussion shifted toward such metrics as the total cost of ownership (TCO) as well as their willingness to assume risk:

What does the future of big data architecture look like from your side of the data center? Let us know in the comments section below.

Next Steps

See our first recap from this chat and our second tweet rundown for more on the complex topics of big data architecture and investment. Check out our CIO Essential Guide to learn all there is to know about the evolution of big data analytics. Then, head over to SearchBusinessAnalytics to get some expert tips on how to prep your big data architecture for better analytics.

Dig Deeper on Enterprise business intelligence software and big data

Join the conversation


Send me notifications when other members comment.

Please create a username to comment.

How do you think big data architecture should evolve? How is leveraging service providers vital to that evolution?
Once, adding computing infrastructure involved ordering, installing and configuring physical hardware and software - a process that often lasted 6-8 weeks. If you were lucky. Cloud computing has revolutionized the old paradigm, dramatically reducing implementation time frames and speed to market. And now, cloud computing seems poised to do the same thing for big data, and big data may ultimately be the 'killer app' for cloud computing. Certainly, AWS and other providers are banking on this. But given the costs involved, and the level of customization required to meet different requirements, can big data be supported in a public IAAS model?