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August 16, 2012


5 Big Data Trends in the Enterprise

By Chris Gonsalves

Enterprises are inexorably drawn to storage and backup, two technologies that work in tandem to guarantee all of a business’s mission-critical, archived and unstructured data is properly saved and standing at-the-ready when needed. The obvious benefits of business continuity and disaster recovery notwithstanding, the main drawback to these systems is that the data contained within them lies largely fallow and unproductive.

The traditional IT complaint: Storage data costs organizations money instead of making it.

Big Data significantly changes the equation. All of the buzz and hype around Big Data has led some to complain the space is really just a repackaging of data mining and business intelligence. While there may be some truth to that, the really big idea behind Big Data is that it finally finds productive, profitable uses for all of that previously unproductive storage and backup data.

Big Data’s goal is simple: examine and analyze the reams of data sitting in warm and cold storage to discover trends, opportunities and paths to more sales. Big Data lets business managers better understand their operating environment and make smarter, more accurate business decisions.

That’s making Big Data big business. Deloitte predicts enterprise software sales this year will reach $270 billion, with approximately one-quarter of those investments going to Big Data, enterprise resource management and business intelligence. That means businesses of all sizes will be getting on board with the technology. Vendors such as IBM are pushing business analytics and Big Data into all areas of the market with appliances and applications that make easy work of processing data and churning out actionable intelligence.

The Big Data wave has the potential of eclipsing other white-hot tech trends like cloud computing in sheer scope and impact. Here are five Big Data trends that will drive technology in the enterprise over the next decade:

1. Data consolidation and reorganization pave the way.

Before numbers can be crunched and data can be analyzed, the organization must have the right data and know where it lives. Unfortunately, much enterprise storage data looks like the piles of newspapers and empty boxes on an episode of “Hoarding: Buried Alive.” The path to Big Data starts with corporate IT identifying where the data is, eliminating redundancy, optimizing file systems and ensuring analysis applications know where to find information. If there is no data, there is no analysis.

2. Hardware must be up to the task.

Though it seems counter-intuitive, Big Data will require significant capital investments in equipment to get the business intelligence ball rolling. Analyzing large volumes of unstructured data is a matter of pure processing power, storage capacity and I/O speeds. CIOs will first need to justify high-performance appliances or clustered servers that can handle the Big Data load. Even when Big Data is delivered as a cloud service, it requires a fair bit of new gear for running analytical workloads.

3. Storage and business intelligence are merging.

Today, storage and backup are all about capacity and management efficiency; Big Data is focused on processing power and analytical capabilities. Expect those two to merge storage and backup vendors and cloud file-sharing services, crafting strategies for collaborating with or providing Big Data products and services. This will dramatically change the composition and nature of storage offerings and the vendors who provide them.

4. Security demands multiply with Big Data growth.

To really leverage Big Data in this world of clouds and distributed enterprises, organizations will need to open data stores to a growing number of employees, contractors, applications and hosted resources. With so many hands – and automated processes – touching critical information, security risks and vulnerabilities are bound to skyrocket. Demand for Big Data-related access control, authentication, data encryption, intrusion prevention, auditing and regulatory compliance is already mushrooming. Big Data will continue to evolve into a change agent for security technologies as we know them.

5. Opting for business management ‘-as-a-service.’

Big Data is about more than measurements; it’s about completing predictive analytics for better business performance. The ability of many enterprises to perform such activities in-house is often limited. For now, many are hiring analysts and quantitative specialists to fill the skills gap. However, many CIOs may ultimately opt for outsourcing both Big Data technology and the associated analytics to reap the business benefits while keeping their IT staffs focused on their core.

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