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Data processing and delivery is witnessing a sea change with the ’shift-left‘ approach, where problem resolution and similar activities are carried out as close as possible to the end beneficiary (the enterprise business teams). Further, data management continues to reel under the avalanche of perpetually growing data. Data management software makers continue to upgrade and reimagine the software features to address these challenges. During the planning of upgrades, software dimensions such as self-service, scalability, technology-support, and so on, invariably draw attention and stories related to them enjoy priority in the product backlog. Undeniably, these primary dimensions are critical to the overall success and are the differentiation factors of the software.
However, a deeper analysis reveals that the primary dimensions are not the sole factors that determine the success of the software. Several ‘supporting’ features play a silent yet significant role in elevating the utility levels of the software. These features may not appear as important to a software architect, as those like scalability or support for technology-heterogeneity. Nonetheless, when implemented, they have a significant bearing on the software’s value and the effectiveness of its primary features. The key supporting features include:
Looking Beyond the Obvious
While the primary dimensions of data management software clearly need continuous improvement, we must not lose sight of the other ancillary features that have a major impact on the success of the software. These features play a significant role in enhancing the usability of the software. While the must-have features for data management are prioritized for immediate market demands, it is important to consider the key supporting features that can lend a competitive edge to the software. While many claims offer the high-end primary features, software that offer pragmatic, user-centric ones can often prove to be the game changers.
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