Companies across most industries have begun using big data for mission-critical processes and workflows. Most cultivate these cutting-edge operations by way of digital transformation programs, which researchers for the International Data Corporation say will account for $1.25 trillion in global enterprise spend in 2019 and eventually consume almost $2 trillion by 2022. Through these initiatives, businesses of all sizes are rolling out data-driven, paradigm-shifting technologies that facilitate never-before-seen operational efficiency and scalability.
Artificial intelligence software is among the many emerging innovations that underlie big data infrastructure. Once futuristic fantasy, the technology has advanced to the point of deployment. Today, vehicle manufacturers use AI to create self-driving systems, while life sciences firms produce medical devices that monitor and respond to patients’ internal chemistries in real time, according to Deloitte. The same sort of AI innovation is even unfolding in the professional services sector, where insurance firms are using these tools to track claim patterns and automate payments and rejections. These companies, along with adopters in other sectors, are expected to spend more than $32 billion on AI technology in 2019, according to IDC.
The no-operations IT approach, called NoOps, is another big data-based advance influencing modern business. Technical specialists have traditionally devoted considerable time to coding new applications, implementing network patches and performing maintenance, all to develop backend systems that keep front-of-house functions online and working as intended. The NoOps methodology ends this manual work, allowing IT teams to harness newer technologies and techniques, such as cloud computing, containerization and serverless computing, to automate all technical operations and focus on achieving new levels of efficiency and scale. While in its early stages, NoOps possesses immense potential and is driving companies everywhere to look into its technological building blocks, including serverless infrastructure, which 22 percent of businesses have already adopted, per research from the Cloud Foundry.
Big data has also led to the development of hybrid work environments where humans, hardware and software collaborate to achieve optimal production results. Industry innovators such as Amazon created the blueprint for this approach, and now enterprises in numerous niches are adopting and perfecting it, harnessing AI’s power, augmented and virtual reality, cloud computing and robotics to cultivate future workflows. Approximately 51 percent of organizations are working to facilitate human-technology symbiosis and lay the groundwork for the hybrid future, analysts for Deloitte found.
These and other enterprise IT innovations linked to big data have stoked excitement among consumers and industry insiders. However, few organizations have the internal technical talent they need to pursue rapid adoption. For instance, there are fewer than 25,000 certifiable AI experts globally, The New York Times reported. With countless companies moving forward with AI implementation, there is just not enough talent to go around. This offers significant potential for emerging specialists looking for new information technology careers.
