Hyperscale Data Analytics is the Future but Brings Concerns

By Greg Tavarez, TMCnet Editor  |  August 16, 2022

Data is growing at an extraordinary rate, and organizations are having to manage the shift from big-data volumes toward ingesting, storing and analyzing hyperscale data sets that include trillions of records.

IDC (News - Alert) Global DataSphere research documented that in 64.2 zettabytes of data was created or replicated in 2020, and more than 180 zettabytes — that’s 180 billion terabytes — will be created in 2025.

Ocient released a report, “Beyond Big Data: The Rise of Hyperscale,” and revealed the goal of understanding the top opportunities, challenges and concerns associated with the rise of hyperscale data analytics.

An Ocient  report notes that 97% of IT professionals expect their data to grow fast in the next one to five years, and 98% agree that it's important to increase the amount of data analyzed by their organizations in the next one to three years.

Previously, companies found ways to keep their legacy systems alive. But as the amount of data increases, the ability of legacy systems to scale and flex sufficiently is threatened. More than half of businesses are actively looking to switch data warehouse providers.

  • 40% say the technology is legacy and are looking to modernize.
  • 42% say the system(s) isn’t/aren’t comprehensive enough to meet their needs.
  • 36% say they are not flexible enough.

With legacy systems becoming outdated, decision makers are thinking about what comes next. Speed, agility and integration are top of mind, but replacing legacy systems can be an overwhelming proposition. IT leaders say that, in addition to speed and performance upgrades, having a flexible and agile system and improving data access and integration across the enterprise are key.

Of course, with each change comes challenges and concerns. The top challenges organizations face when it comes to switching from their legacy systems include:

  • Hiring enough experienced and specialized talent to achieve data strategy needs (65%).
  • Maintaining security and compliance as data volume and needs grow (63%).
  • Scaling data management and analysis in a cost-effective manner (49%).
  • Streamlining the number of systems and ecosystems under management (48%).

Decision makers are preparing for their organizations to collect a large amount of data. They are looking for ways to upgrade and modernize their legacy systems and skill up their teams to reduce complexity and cost. Without those assets, there’s little hope they can effectively manage and benefit from the massive amounts of data they continue to amass.




Edited by Erik Linask