CIOs believe that expecting conventional data constructs and storage to provide the scale, portability, and speed needed by cloud-native applications, will lead to disappointment
Enterprise leaders acknowledge that while data is the crown jewel among business assets, it is hard to monetize, manage, and secure in spite of receiving focus from both vendors and customers.
When analyzing historical data on how the attempts have been made to harvest insights from the data, the underpinnings have remained common. Developments and innovation related to data services and cloud storage can boost the business value as Machine Learning, and Artificial Learning gains mainstream adoption across the world.
The shift from humans to machines
In the initial days, the main aim of data management and business intelligence software was to provide understandable human insights. Context was given second preference compared to precision. Timeliness was secondary to completeness.
In the current scenario of digital world fueled by ML and AI, algorithms consumer data and convert them to actions. The focal point is that only a fraction of such actions are meant to be followed by humans. Data comes in and out at will, in different formats, and at high speeds. CIOs doubt if a human-intensive data mindset can stay focused and relevant in the machine fueled world.
Data and applications are two faces of a coin
IT leaders point out that application development has drastically changed in the current millennium. The agile processes have enabled developers to iterate often, fail fast, and deliver in regular increments. Tools powered by DevOps has reduced development workflows and boosted software quality.
Data scientists and AI/ML engineers agree that the application’s initial development has become easier; however, management of varied and large storage of data used by applications has become difficult. Specifically, data preparation and acquisition have become a bigger challenge for enterprises.
The sudden increase of hybrid cloud and containers has heightened the frustration levels of data stakeholders. They are already struggling to strike a balance between making data more securely accessible and helping in higher innovation for developers. CIOs agree that a feasible and iron-clad solution is yet to be realized for the issue.
They continue to push for treating data and application modernization as the two faces of the same challenge rather than pushing data modernization to the back burner.
Implementing cloud-native data services for cloud-native workloads
CIOs believe that organizations often fail to leverage their investment in the cloud-native development methods and tech as old storage stacks and data prove to be a hurdle. Conventional data and storage constructs are incapable of meeting the requirements of cloud-native applications.
On a positive note, hybrid cloud infra, for instance, can use more innovative methods to unlock data that can then be more resilient, actionable, and accessible to applications in the open hybrid cloud.
CIOs believe that cloud-native data services are capable of creating an open hybrid cloud application environment, with easy use services for intelligent storing, responding, storing, learning, and moving of enterprise data.
Redefining scale and agility
CIOs say that as the IT industry shifts towards infrastructure as a code model, business leaders require larger scale, consistency, and agility from IT architecture. Conventional storage vendors are required to reinvent and restructure themselves or risk elimination.
IT and business leaders may be more empowered when they are able to meet hurdles via the lens of data in action, data at rest, and data in motion. These are the real reflection of modern data pipelines in the era of hybrid cloud, containers, and real-time development workflows.