5 reasons to move to Big Data (and 1 reason why it won’t be easy)

IT executives continually evaluate the technology trends that will impact their business in 2013 and beyond. Some simply deploy technology to advance the goals spelled out in business plans. Others take on the role of chief innovation officer and introduce different models of using existing data to generate new revenue and gain insight into who clients are and what they want.

Buzz has certainly surrounded big data for some time, but many IT executives still and wonder how they can begin to leverage the three “V’s” of big data-volume, variety and velocity, or the frequency at which data is generated and captured-and augment the value of data for their organization. Any IT organization considering a big data initiative should consider these five major selling points, which will bring clarity as well as revenue to a company.

1. You’ll Manage Data Better

Many of today’s data processing platforms let data scientists analyze, collect and sift through various types of data. While it does take some technical know-how to define how the data is collected and stored, many of today’s big data and business intelligence tools let users sit in the driver’s seat and work with data without going through too many complicated technical steps. (See big data advantage No. 3 below.)

This added layer of abstraction has enabled numerous use cases where data in a wide variety of formats has been successfully mined for specific purposes. One example is real-time video processing. The 2012 Summer Olympic Games in London made heavy use of closed-circuit video, with 1,800 cameras monitoring Olympic Park and the athletes’ village. Teams of analysts used applications to process data pertaining to those who were filmed and flag any individuals behaving suspiciously.

Another example is medical transcription. As electronic health record (EHR) use grows, healthcare organizations are increasingly using natural language processing systems to transcribe, extract and process data within a clinical context.

2. You’ll Benefit From Speed, Capacity and Scalability of Cloud Storage

Organizations that want to utilize substantially large data sets should consider third-party cloud service providers, which can provide both the storage and the computing power necessary crunch data for a specific period.

Cloud storage presents two clear advantages. One, it lets companies analyze massive data sets without making a significant capital investment in hardware to host the data internally. Two, as internal IT departments recognize that big data hosting platforms require new skills and training, they find that a hosted model tends to abstract that complexity, enabling more immediate deployment of big data technology. This also lets developers build a sandbox environment that’s preconfigured and ready to go without having to set up the necessary configurations from scratch.

3. Your End Users Can Visualize Data

While the business intelligence software market is relatively mature, a big data initiative is going to require next-level data visualization tools, which present BI data in easy-to-read charts, graphs and slideshows. Due to the vast quantities of data being examined, these applications must be able to offer processing engines that let end users query and manipulate information quickly-even in real time in some cases. Applications will also need adaptors that can connect to external sources for additional data sets.

Usability is another consideration. CFOs, CMOs and other non-IT executives are looking to leverage data, so they need access to charts, infographics and dashboards. Fortunately, leading BI vendors are shifting from an IT-driven to self-service analytics model that puts business users in the driver’s seat. This accelerates adoption as well as return on investment and expands analytics’ reach beyond report writers and more technical end users.