1. Market Research

Market Challenges for Big Data Solutions Providers

  • January 2014
  • 9 pages
  • Frost & Sullivan
Report ID: 2005754

Summary

Table of Contents

On the brink of any new high tech era, the temptation is strong for solution providers to hype the benefits and minimize the disruption that such major shifts can produce. In these early days, one of the most important missing pieces in the Big Data puzzle has to do with accurately articulating both the potential payoffs and the attendant challenges. In this paper, Frost & Sullivan ventures some observations about these communication challenges. To illustrate these observations, we take a look at how Oracle is approaching the Big Data market, how Netflix defected from Oracle to Amazon Web Services (AWS), and how Salesforce.com opted to combine Oracle solutions with those of newer solution providers.

Introduction

Once upon a time, databases were static information repositories, housed on expensive mainframe computers, updated in planned and consistent cycles, and accessible only to those who could mount the drives, punch the cards and paper tapes, and decipher the cryptic output. Fast forward fifty years, and Excel lets everyone enter and retrieve whatever data they can gather, while organizations seem to have as many databases as they have departments, projects and accounting auditors.

Data storage options also have evolved, from basement vaults and offsite bunkers full of tapes and disc arrays, to data warehouses, mirrored systems, storage area networks, and instances in service provider network clouds.

Advances in computing power and network capacity have greatly expanded our ability to collect, store, analyze and transport the data needed to support our traditional social and economic activities; while at the same time they are stimulating the generation of vast new data stores. We generate this new data every time we use our smart phones and tablets to “go online” and check the weather, update our calendars, order a pizza, or download a podcast.
Companies like Amazon and Google pioneered the concept of Big Data—basically by using commodity servers, copious bandwidth and open sourced software platforms as substitutes for what was then the gold standard for data management: complex, special-purpose hardware and software running over carefully engineered networks. These early adopters discovered that their new environments were not only more cost-effective but also more scalable than traditional data processing, networking and storage solutions. While Big Data applications used by these online pioneers and by the scientific community (Big Science) have been well underway for a decade or more, successful implementations in more mainstream market segments are just beginning to accumulate.

There is a simple reason why so many different types of vendors have a stake in the multi-billion dollar market for Big Data solutions. It’s the same reason why so many different types of organizations are trying to figure out how they might put Big Data to work in their own environments and on their own applications. Everyone senses that Big Data could be the next crucial and pervasive information technology, as transformative and necessary as its computing and networking antecedents have proven to be over the past fifty years.

On the brink of any new high tech era, the temptation is strong for solution providers to hype the benefits and minimize the disruption that such major shifts can produce. In these early days, one of the most important missing pieces in the Big Data puzzle has to do with accurately articulating both the potential payoffs and the attendant challenges. In this paper, Frost & Sullivan ventures some observations about these communication challenges. To illustrate these observations, we take a look at how Oracle is approaching the Big Data market, how Netflix defected from Oracle to Amazon Web Services (AWS), and how Salesforce.com opted to combine Oracle solutions with those of newer solution providers.

Oracle: How One Big Vendor Does Big Data

In a recent LinkedIn article posted by Mark Hurd, late of HP and now leading Oracle, Hurd mischaracterizes Big Data as one of several “modern business challenges,” including mobile, social, real-time visibility and decision-making, and deeper and longer-lasting customer engagements and experiences. Although Big Data initiatives have already begun to address all the other items on Hurd’s list, his solution is what he calls “truly modern IT systems,” and he broadly dismisses legacy systems as “stuff in the basement that creates little or no value.”

Perhaps it’s a bit unfair to fault Hurd for using the kind of marketing message so common in the high-tech industry, which is often broadly criticized for over-simplification and an exaggerated sense of urgency. And it isn’t a surprise that Hurd is again dissing legacy IT installations; after all, he made part of his reputation at HP by inverting the IT truism that legacy systems eat up % of most IT budgets, leaving only % for innovation and growth initiatives. However, when he claims that, by spending less than that % on these “truly modern IT systems,” organizations could “liberate precious IT dollars from low-value or no-value infrastructure and integration” and “not only help drive customer-focused innovation, but also help to cut overall IT spending at the same time”—well, here we have a great example of the need to better articulate Big Data’s promises and challenges.

Big traditional IT solution providers, like Oracle, who are pitching Big Data also may want to soft-pedal the urgency aspect for a while. That’s because the “stuff in the basement that creates little or no value” is still a primary revenue generator for these vendors, who collect stiff fees for ongoing licensing and support. It’s also the functional IT backbone of the installed base of customers who pay those fees. Neither these vendors nor their customers are really in a position to simply yank these systems out and start over with a clean sheet of paper.

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