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4 questions to ask before starting a big data initiative

Reda Chouffani | Aug. 22, 2012
Big data holds much promise for organizations seeking ways to improve business processes.

A combination of grants and executive initiatives, including a recent directive from President Barack Obama, aim to support big data within the federal government. The primary goal is to improve the accessibility of government services and information to the American people, in part by making possible data access using mobile devices. Federal CIO Steven VanRoekel will oversee the White House Roadmap for a Digital Government, which plans to provide free data access to the public and private sector-which would help many organizations advance their big data initiatives.

Of course, many industries in addition to those listed here can take advantage of big data to help drive change and improvement.

Can You Easily Measure ROI on Big Data Initiatives?

While some vendors may claim immediate ROI on big data, you will need to identify the different aspects of the data they have access to and what value it will provide to your organization.

In most ROI scenarios, you must tie a cost-benefit analysis to the proposed project. In the case of a big data initiative, there are typically several non-measureable aspects. Since you're looking at large volumes of data with the intent to discover insights into potential changes to business processes, it's hard to predict the value of what can be discovered.

That said, there are a couple rules of thumb to keep in mind.

The cost of a big data initiative is unlikely to increase as data volume increases, since big data technologies tend to be highly scalable. In addition, although data comes in different formats (structures, semi-structured and unstructured) at ever-increasing growth rates, the implementation and maintenance of platforms that support Hadoop can help make it much more cost effective than traditional database management systems. That's because newer solutions can run on commodity hardware running open-source software.

As with any new trend, hype surrounds big data. In the past, many organizations used large data warehouses for data analysis and evidence-based decision making. As we know it today, big data brings into the mix additional information, such as social media behavior, which was previously unavailable to users of a siloed warehouse-and now that data can be stored and managed in the cloud for a fraction of what it once cost. To make the most of that data, it's critical to find out what big data means to your organization and what you want your next (or first) big data initiative to accomplish.

 

 

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