by Reda Chouffani

5 Reasons to Move to Big Data (and 1 Reason Why It Won’t Be Easy)

May 21, 20136 mins
AnalyticsBig DataData Management

Companies of all sizes are beginning to reap the benefits of data analytics technology. If you're not up to speed yet, here are five ways that big data can benefit your business--and one precaution that may well thwart your big data plans.

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.

Commentary: Data Analytics Will Fail If Executives Ignore the Numbers

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.

How-to: 5 Tips to Find and Hire Data Scientists

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.

Analysis: 4 Barriers Stand Between You and Big Data Insight

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.

4. Your Company Can Find New Business Opportunities

As big data analytics tools continue to mature, more users are realizing the competitive advantage to being a data-driven enterprise. The 2012 presidential election demonstrated this. Campaign managers in both the Democratic and Republican parties saw a critical need for information on voters and their specific interests; taking this info and addressing an issue through a customized email or flyer meant the potential to gain or sway a vote.

Analysis: 2012 Presidential Election a Victory for Quants

Information regarding our preferences, likes and dislikes is critical to more than just political candidates. Social media sites have identified opportunities to generate revenue from the data they collect by selling ads based on an individual user’s interests. This lets companies target specific sets of individuals that fit an ideal client or prospect profile.

Finally, big data use cases in about in retail, where the focus is on gaining insights by studying consumer behavior in online stores or physical shopping centers.

5. Your Data Analysis Methods, Capabilities Will Evolve

Data is no longer simply numbers in a database. Text, audio and video files can also provide valuable insight; the right tools can even recognize specific patterns based on predefined criteria. Much of this happens using natural language processing tools, which can prove vital to text mining, sentiment analysis, clinical language and name entity recognition efforts.

One example that highlights the use of audio analysis and big data comes from MatterSight. This call center tool can match incoming caller to the appropriate customer agent by using predictive behavioral routing and other analytics technology. MatterSight performs audio analysis to identify and score the calls based on specific criteria and then match customers with the best department to ensure the best experience. These advanced capabilities highlight some of the advancements we continue to see in unstructured data analysis and Big Data capabilities.

The Big Data Challenge: You’ll Need New People

In addition to buying the right software, recruiting the right talent ranks among the most important investments an organization can make in its big data initiative. Having the right people in place will ensure that the right questions are asked—and that the right insights are extracted from the data that’s available. Keep in mind that data scientists, as many refer to those working with big data, are in short supply and are being quickly snapped up by top firms.

Every CIO wants to keep his finger on the pulse of innovations that can transform his company, enhance existing business models and identify potential revenue sources. Enabling this business transformation means adopting the right tools, hiring the right people and—most of all—convincing executive leadership to embrace new models for using existing and brand-new data.

A successful big data initiative, then, can require a significant cultural transformation that’s driven by the IT department. Highlight these five advantages of pursuing a big data initiative, though, and your executives are more likely to give you the resources, and the talent, you need to rise to the challenge.

Reda Chouffani is a vice president at Biz Technology Solutions, which helps medium and large companies in the Southeastern United States deploy BI and EHR software as well as IT infrastructure.

Follow everything from on Twitter @CIOonline, Facebook, Google + and LinkedIn.