Big Data. Big Decisions
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Big Data Squeezes Legacy IT Spending: IDC



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Most companies can make high-level, strategic decisions using analyses that approximate the answers they need, according to Vesset's analysis. The next step up in sophistication requires better data and processes, streamlined to make analysis timely and actionable, that allow companies to improve their troubleshooting, operational efficiency, and performance in near-real time, rather than on a monthly or quarterly basis.

The most sophisticated level of analytical capability is the potential to make day-to-day tactical decisions based on data rather than instinct, according to the report.

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That level of analytical ability, however, is comparatively rare because it requires high levels of automation in the gathering and dissemination of data, identification of patterns, real-time performance monitoring, and extra touches that make abstruse analytics accessible to non-technical business users.

Creating those abilities in companies that don't have them takes more than just the addition of sophisticated data-handling software such as Hadoop or other open source big data analytics.

Making even the basics of big data work is easier with help from other hot-trending technologies--cloud networks that provide capacity on demand and data from mobile devices or social networks that offer a look at the real-world use of a company's products or services, data that may be difficult to get using traditional methods, Woo said.

It is the combination of these major technologies that makes them the pillars of the next generation of computing, according to Woo and Vesset.

Demand for combinations of these technologies will also drive development of other technologies--ultra high-capacity storage media; high-speed, high-volume messaging; and even higher-capacity broadband networks to connect big data, big clouds, and distributed applications, for example, according to IDC's March report from Woo and Vessett.

Because each of those technologies also depends on a reliable, high-speed, secure infrastructure, the four pillars of the new world of IT will not only drive development of consumer technology. They will drive reinforcement, acceleration, and refinement of corporate IT infrastructures as well, the two wrote.

The future of IT, in other words, relies as much on updating the technology of yesterday as on inventing something new. Not coincidentally, it is the difficulty in taking advantage of any of the them that will drive most companies to develop the skills and infrastructure they need to make all work together and quantify the benefit of having done so, according to experts in predicting the progress of analytics as well as technology.

Many enterprises are building data warehouses to centralize the ever-increasing information flowing through their organizations into useful repositories. This makes good business sense, but it opens up a slew of concerns from a security standpoint. IT professionals can apply many of the same security best practices used with databases, but there are new lessons to be learned, as well. Download our Securing The Data Warehouse report. (Free registration required.)

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By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



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