Data-Driven Digital Transformation Means Cloud Data and Analytics
Last year, Gartner declared that on-premises databases are now legacy technology. Are we ready to say the same for analytics and BI?
Organizations have recognized the cloud opportunity for years now. Most, however, lacked a cohesive strategy to get there. There was little urgency to make this shift. Organizations could get by using their traditional on-premises infrastructure to meet their data and manage their business.
In the last few years, everything has changed. Extreme economic conditions and the pace of change have forced organizations to adopt a “cloud now” strategy for data and analytics.
Looking to capitalize on new opportunities in a digital world, organizations were well on their way to data-driven digital transformation. With more data now originating in the cloud, many enterprises were implementing their data modernization plans before the pandemic hit. The pandemic, however, has further accelerated these plans. A Gartner survey of boards of directors shows 69% of organizations have accelerated their digital business plans.
The global pandemic has pummeled certain industries, but the ones that had already begun their digital transformation and cloud journeys have proven to be more resilient. Instead of focusing on upgrading and maintaining on-premises applications and infrastructure, these organizations have moved more quickly, and they’ve been able to nimbly focus on rapidly changing processes. Organizations with more resilient infrastructures and better data (internal and external) have pivoted faster and will continue to benefit from the first-mover advantage.
Cloud computing enables new forms of analytics with greater amounts of data than on-premises deployments provide. On-premises analytics can prohibit experimentation because the data infrastructure has to be designed for peak demand—even for a one-time analysis. During a debate about the trade-offs of cloud, the CDO of a large financial services firm shared that the analytics his company is performing today was simply not possible before. They simply didn’t have the budget or “people power” to scale the on-premises data center. Cloud enables an organization to add compute power, experiment, analyze, and then remove what is no longer needed or return to steady-state demand. This can be done in hours and days as opposed to potentially months and years for on-premises deployments.
First-generation on-premises data warehouses focused largely on internal, transactional data. With the rise of the Internet of Things (IoT), data is being generated from a range of devices including cars, household appliances, cell phones, medical devices, smart meters, and more. Global telecommunication companies are in the process of rolling out 5G, which will generate even more data, faster, touching every sector from healthcare to entertainment to manufacturing and smart cities. According to research from Seagate and IDC, the volume of enterprise data will grow 42% annually from 2020 to 2022. The ability to store and analyze this data will be a critical competitive differentiator for rolling out new use cases, improving customer experience, and driving revenue. In this way, cloud, IoT, and 5G are the perfect storm for analytics. The leaders are aggressively moving to the cloud ahead of these trends, while laggards, who remain largely with on-premises deployments, will face a sharp demise.
The cloud data and analytics market has matured, now rivaling and surpassing the levels of security, administration, and control once found only in mature on-premises deployments.
