Accelerated cloud data migration fuels modern BI adoption
Data is moving to the cloud faster than ever, driving organizations to rethink their data strategy.
Modernizing your data strategy often means rethinking where your data is stored. More companies are seeing the benefits of moving their data to the cloud, including added flexibility and scalability at a lower total cost of ownership. In fact, Gartner research indicates that the "public cloud services market is projected to grow 21.4% in 2018 to total $186.4 billion." The cloud makes it easier for companies to capture and integrate different types of data. This means moving away from an environment where all data resides in a highly-structured, on-premises warehouse and into a more scalable, flexible infrastructure—either a full-cloud or hybrid solution.
This brings us to data gravity, a concept suggesting services and applications are pulled in the direction of where the data resides. As more organizations move workloads to the cloud at an accelerated rate, this data gravity is pulling analytics processes to the cloud as well.
The driving factors behind this gravitational shift are latency—the amount of time required to perform an action—and throughput—the number of times an action can be performed or result achieved per given unit of time. When data, applications, and services are closely aligned, there is a decrease in latency and throughput, resulting in increased efficiency. Naturally, when data resides in the cloud, these applications and services will start to follow.
As organizations asses their broader data strategy, they are also rethinking their analytics model, moving from traditional to modern BI. McKinsey notes that the value of the cloud comes when companies approach cloud infrastructure and systems "not as one-off tactical decisions but as part of a holistic strategy to pursue digital transformation."
Traditional business intelligence relies on IT departments to provide answers to questions, creating bottlenecks and keeping analytics separate from the business context. In the same way, traditional BI deployments are often built on a rigid on-premises model meant to support this mode of enterprise reporting.
In contrast, cloud analytics offers a variety of benefits, including the opportunity to think about new deployment models—and leaders are eager to leverage these opportunities. This includes pushing out mobile dashboards to employees in the field so they can access data without first having to clear a firewall. The cloud also enables secure dashboard sharing with partners or customers, creating one source of truth that goes beyond internal processes.
Although not all companies are prepared to move all of their data to the cloud, many are experimenting with hybrid solutions to take advantage of diverse data sources. As a result, companies are assessing modern BI platforms on the premise of whether or not they can support a future transition to full-cloud analytics.