Editor’s note: This article is based on content initially published in the SHARE President's Corner blog.
Big data was a big focus at the recent SHARE
conference in Anaheim, Calif. Event organizers devoted two days of conference content to a Big Data Spotlight with a concentration of sessions designed to address the “most pressing big data questions and concerns” of its community.
Like big data itself, the SHARE spotlight could be measured across four dimensions:
– More than 20 sessions included strategies and tactics for managing Big Data
– 60-minute sessions moved fast, providing a persistent, consistent blend of insight and information
– Session topics varied in scale, focus and format, from spacious ballrooms to intimate salons, from debates of policy and governance to technical intricacies, from rousing panel discussions to “how-to” handbook-style lectures.
– Speakers came from real-world technology users, the deep ranks of IBM’s subject-matter experts, the leadership of IBM’s Strategic Partners, and dozens of vendors offering complementary mainframe computing technologies. But regardless of the speaker’s origin, each presentation was infused with real-world big data application stories, and each session included dialog with the real-world practitioners in the audience.
(The original “3Vs” of big data—volume, velocity and variety—were originally coined by Gartner Research Vice President Doug Laney in a 2001 article as outlined in this blog post.)
Why the Big Emphasis on Big Data?
Keynote speaker Brian Gallagher, president of EMC’s Enterprise Storage Division, called today’s technology landscape the “most exciting” period in his 30-year career and named big data as one of the top-three megatrends that’s “changing IT forever” and resides “top of mind for CIOs.”
In a separate session, Mark Simmonds
, senior product marketing manager, IBM System z Software, and a contributor to IBM’s Smarter Computing Blog
, echoed these sentiments when he confessed to being “obsessed with big data.” Simmonds said his preoccupation comes not from fear of the rapidly rising tide of data in the digital universe but from a fascination with the possibilities presented by the “ability to process, integrate and understand data from anywhere.”
Speakers in multiple sessions shared Simmonds sentiment, a theme running through the conference that could be dubbed: Big Opportunity in Big Data for the Mainframe. And the storyline from session to session followed three arcs:
Gallagher told SHARE participants they are a natural choice for leading IT through the process of transforming big data challenges into opportunities. In an era of disruptive technologies, he said, “the mainframe is a constant.” In an interview after his keynote address, Gallagher gave mainframers a three-step guide to successful change leadership:
1. Make clear your intent to your team.
2. Engage as many people in the enterprise as possible.
3. And build your organization, skillset and technology toolkit around your intent.
Simmonds assured participants in his session that the mainframe is a natural choice as a trusted technology for managing big data for greater opportunity. Gesturing to the audience, he said, “I’m sure some of you have managed your systems for more than 10 years without an outage.” He cited four reasons System z is ideal for big data processing:
1. History of handling mixed workloads
2. Capacity for real-world scalability
3. Capable of end-to-end security
4. Compatibility as a consolidation platform
For the SHARE participants in his session, Mike Biere, marketing manager, Business Analytics and DW, IBM Silicon Valley Lab, named five business opportunities for big analytics from big data:
1. Act on deeper customer insights
2. Create innovative new products
3. Optimize operational processes
4. Proactively maintain business assets
5. Prevent fraud and reduce risk
As a practical means of seizing initiative for leadership, trust and insight, Biere recommended mainframers establish a big data team, project office or competency center. He urged his audience to take these opportunities seriously.
“Big data is often called ‘mission critical’ to the enterprise,” Biere said. “What is ‘mission critical?’ That should mean, ‘If it goes down, we’re toast.’” He then asked the crowd how many big analytics plans they had seen that truly were “mission critical.”
“If you use the term ‘mission critical,’ be sure you mean it,” he said as he cautioned SHARE participants that competitors in the marketplace are acting with true mission-critical urgency when pursuing the big opportunities in big data for the mainframe.
“Those who hesitate can be outperformed two to three times by competitors,” he warned.
Communications strategist Bob Dirkes attended SHARE in Anaheim on special assignment. Follow him on Twitter @RCDirkes. Follow SHARE on Twitter @SHAREhq.