Today there is widespread awareness in corporate boardrooms globally about the significant new value being created from the adoption of cloud computing, containers, big data and AI, and other components of modern technology stack. Yet to actually realize all of the potential, existing technology platforms must be transitioned out, which can cause short-term disruption and pain. CTOs and CIOs need to be supported as they embrace new tools that are emerging at a rapid fire pace and as they learn to recruit the talent necessary to implement and leverage these tools.
Today, companies like Salesforce enable non-technology corporations to assemble their own tech stacks in a modern enterprise cloud model. Literally dominating the San Francisco skyline with its new headquarters Tower, Salesforce has become a leading enterprise cloud platform, expanding beyond CRM to serve as a developer platform for customers who want to unleash their own proprietary data by developing new applications. One critical unlock for the growing Salesforce enterprise customer base is recruitment of new skills, including cloud SW managers.
And it is all happening fast. By way of example, in a couple of years Docker has become the predominant open source container software to enable widespread deployment of software packages across different platforms. IT departments leveraging containerized software expanded from 22% in 2016 to over 80% in 2018 (Pitchbook Survey.) And $3.1B venture was invested in 2018 alone into this new category of Cloudtech (Pitchbook). Meanwhile, open source software is becoming widespread across even traditional industries, with 69% of enterprise executives viewing it as very or extremely important to their company’s strategic goals (Redhat’s 2019 State of the Enterprise Open Source Report). Cloudfare’s strong debut on the public markets just this month stands in visible contrast to some less exciting IPOs from non-tech infrastructure companies in 2019, notably in the marketplace category.
In line with the size of venture investments into the tech stack category, we are seeing more high potential start-ups developing IT automation services. For example, Cloud First Core Venture Group portfolio company Ascend.io uses ML and AI to automate the data pipeline process, enabling data scientists to focus on data models and not data pipes. When it comes to Machine Learning and AI potential in traditional industry categories, it is clear that there is still too much time being spent by data scientists on data engineering.
To what extent do corporations in traditional industries need to evolve into actual technology companies themselves? What are the opportunities to embrace data and cloud computing as core to their business strategies?
We would love to hear how your enterprise company is embracing the new tech stack and fast modernizing, or where you are getting stuck.Read on Nikkei Site