Cloud Convergence – Biased Simplicity?
I recently came across a paper published in Nature that posited that most observed scientific phenomenon, from biochemistry to quantum mechanics, seem to gravitate to the most simplistic output, regardless of the complexity of input. In short, nature prefers simple. While seemingly unrelated and undeniably esoteric, at its heart lies a pattern that may actually explain the emerging trend by large organizations toward reducing data landscape sprawl and complexity.
Unless you’ve been hiding under a rock for the past decade or so, you’re acutely aware that a mass migration to the cloud is well underway. In fact, of the 200 CXO’s surveyed in 2019 by the Everest Group in companies with $1B USD of revenue or more, 90% of them indicated they’ve already adopted some form of cloud computing. What was also clear from the same survey is that nearly half of respondents expected to employ a multi-cloud architecture. Not surprising then that these two observations, added to the inexorable, exponential increase in data being produced—forecasted by IDC to exceed an almost inconceivable 175 Zettabytes by 2025—combine to create a chaotic, complicated data ecosystem for even the least data-dependent enterprises. In an equal and opposite reaction to the forces described above, enterprises are desperately seeking to converge toward a simpler architecture, preferentially pursuing platforms that can handle multiple workloads and remain hyperscaler agnostic, while providing the value, flexibility, and scale of a cloud-native platform.
Punctuating this observation, a 2020 IDC survey found that over 75% of the organizations surveyed stated they were looking to consolidate their data “on as few cloud databases as possible.” Clearly the last decade has been marked by a massive migration to the cloud which appears to now be giving way to a convergence in the cloud.
While there is much to gain from this consolidation, I’ll briefly emphasize three primary benefits here:
- Reduce Data Transfer – Moving data between purpose-built databases not only increases processing and storage costs, makes data integration more complex and costly, but most importantly, slows down time to insights.
- Improve Security – Harmonizing governance and security across a disparate and diverse data landscape, accessed by an ever-growing number of personas, is a nearly impossible task for even the most sophisticated organizations. Leveraging a unified cloud data platform makes this standardization not only possible, but can have the additional benefit of achieving the elusive “single source of truth” for a diverse set of stakeholders.
- Automation – So much of what consumes many organization’s DBAs time are simply commoditized, mundane tasks that are far better suited to being left to a single intelligent platform, as a managed cloud service. This frees up important data professionals to focus on high-value activities, delivering far more ROI to their respective stakeholders and organization. IDC found that “half the surveyed DBAs were responsible for administering at least six production databases, with the largest amount of their time spent on investigating problems in the data likely caused by application or user error.”
Whether by coincidence or some inexplicable parallel to what scientists observe in the natural world, global organizations are showing clear signs of paring down their ever-more complex data ecosystems to far more simplistic, unified data platforms.
If you’d like to hear more on this subject from two preeminent experts, I encourage you to tune in to a webinar on the emerging trend toward adopting a unified cloud data platform on September 29th, hosted by Dan Vesset, Group VP of IDC’s Analytics and Information Management, and Brian Raver, VP, SAP HANA & Database Solution Management. Brian will also share details of how SAP HANA Cloud and the SAP Business Technology Platform support these trends.
For related content on SAP HANA Cloud please see below: