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The ability of legacy data warehousing platforms and business intelligence (BI) tools to glean insights from big data is decreasing exponentially as more sources of data are poured into them, according to an Actian and Skyhigh Networks survey of more than 250 senior executives.
The survey found analytic workloads are failing in traditional technology environments that are pervasive across enterprise networks.
Half of the IT leaders surveyed indicated they are not very confident in their existing data infrastructures, while 56 percent said legacy systems are feeling the strain of these new workloads today. Another 42 percent said their data warehousing platform is breaking under the pressure.
In addition, just under half (47 percent) of respondents said the cost to maintain traditional systems continues to rise and an additional 46 percent acknowledged that these traditional technologies were not architected to handle—and lack the flexibility required for—modern workloads.
“The dichotomy is between senior leadership and IT admins on where things are broken,” Ashish Gupta, chief marketing officer and senior vice president of business development and big data expert at Actian, told eWEEK. “Interestingly, the IT admins correctly believe that modern BI and analytics workloads are broken because the problem is with the underlying traditional architecture that these applications run on. The senior management, not having the details believes that the issue is with the BI application.”
Gupta noted that regardless of this gap, it is clear that companies are unable to deploy modern analytic workloads and they are clearly unsure about the steps forward.
The survey also indicated confidence is low when it comes to scalability, but the gap between C-level executives—27 percent of whom were “completely confident” in their existing data infrastructure’s ability to scale—and IT staff (just 13 percent) was notable.
Forty one percent of respondents said the explosion of new types and sources of data are overwhelming systems and slowing performance.
When asked how they plan to address issues with their organization’s traditional data platform, 32 percent indicated that they intend to rip and replace with a modern solution.
However, a greater number are looking to augment it with tools that can maximize their investment (62 percent), and many plan to keep moving excess data into storage and deal with it later (45 percent). Nearly half said they currently look to SQL analytics to help them make sense of their big data.
“We see an ever increasing amount of data being analyzed by business to inform their business processes,” Gupta explained. “In fact, we [expect] not only the size of the data but also the types of data being analyzed to balloon and consequently, the traditional architectures will just not be able to deliver the analytic insights in a timely, commercially viable or technically feasible manner.”