Cloud has topped the “one to watch” technology lists of every pundit, analyst and business leader for the last two decades. Touted as the solution to immortality, health, wealth, happiness and space travel, cloud is a mission-critical system with remarkably high potential for access, accessibility and efficiency.
Unfortunately, cloud is also a remarkably underutilized technology — one defined by a high focus on data storage but a lower consideration for insight generation. The first generation of cloud centered around storage, apps and the emergence of software as a service. The second iteration saw IT teams modernize work practices and deliver greater capability. The next generation of cloud computing will be defined by accessibility.
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Despite unprecedented change over the last few years — with businesses held back by historic organizational moves, skills shortages and shifting competitive landscapes — the need for insights to compete and thrive is higher than ever. The ability to generate those insights, however, is dictated by two factors: Firstly, the amount of data to be analyzed; secondly, the bottleneck of data scientists in-role to analyze it.
While there is a huge and often overarching focus on cutting-edge capabilities, with more data available than ever before and an increasing shortage of data scientists to manage it, 2023 is the year when accessible cloud computing will hit its stride. This technology can go much further when insight generation is put in the hands of those with the most to gain.
Cloud computing: Putting the right technology in the right hands
Ultimately, any technology is only as effective or impactful as the person using it. This also rings true for cloud computing. Over the next decade, the most valuable cloud computing advances will be those that magnify and amplify human potential on a wider scale — provided organizations can merge access and accessibility requirements and bring their human experts to the forefront.
Effective use of any technology is always dependent on the human factor. In many cases, that can be a net benefit, allowing human ingenuity to rise to the forefront of decision making. In other cases, as we see with data science teams today, the human factor can also act as a bottleneck to business value. As the amount of data created on a daily basis continues to grow exponentially, and without the ability to scale these teams effectively, data science teams across the world now find themselves overwhelmed and burned out due to their excessive workloads.
Businesses are rapidly reassessing the resources at their disposal, turning their focus to areas where they can deliver the greatest value in the most reasonable timeframe.
It is clear that the move to cloud — at least in part — was driven by pragmatism in the face of this exponential data growth and the need for fast insights. In 2023 and beyond, that same pragmatism will be a key driver behind greater adoption of democratized in-cloud analytics, solving the challenge posed by increasingly burned out and overworked data science teams now unable to keep pace with the scale of data growth.
In delivering the ultimate promise behind cloud computing, Gartner figures show that global public cloud spend is set to reach $600 billion in 2023. A continuation of IDC research, completed by Statista, showcased a huge increase in the volume of data created by 2025, growing to 180 zettabytes each year. For context, to store just one zettabyte of data would require 41.5 million of the world’s largest commercially available hard drives (24TB).
Businesses now not only have a strong motivation to deliver timely insights from their data, but also a foundational drive to remain competitive in a hugely disrupted competitive landscape. 2023 is the year when cloud computing finally meets its true potential — combining both usability and widespread accessibility. In practice, this not only includes data scientists facilitating cutting-edge cloud technology integrations, but also upskilling in-department knowledge experts and data workers to solve their own problems with in-cloud data.
2023 and beyond: Redefining our relationship with cloud
The first bridge businesses need to cross to unlock this potential for 2023 and beyond is breaking free of the legacy understanding of how cloud computing should work. Gartner research estimates that we exceeded one billion knowledge workers globally in 2019. These workers are defined as those who need to think creatively and deliver conclusions for strategic impact. These are the very people that cloud technology was designed to facilitate.
Cloud integrations in many cases can be hugely advanced and mature from an operational standpoint. Businesses have integrated multi-cloud solutions, containerization and continuously learning AI/ML algorithms to deliver truly cutting-edge results, but those results are often not delivered at the scale or speed necessary to make split-second decisions needed to thrive in today’s operating environment.
For cloud democratization to be successful, companies need to upskill their knowledge workers and upskill them with the right tools needed to deliver value from cloud analytics. Low-code and no-code tools reduce the experiential hurdle needed to deliver value from in-cloud data, whilst simultaneously delivering on the original vision of cloud technology — giving people the power they need to have their voices heard.
Suresh Vittal is the chief product officer at Alteryx.
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