Unlocking Cost Efficiency In Data Management

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Unlocking Cost Efficiency In Data Management
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Yuri Gubin is the Chief Innovation Officer at DataArt. Read Yuri Gubin's full executive profile here.

As businesses struggle with escalating costs and technological advancements, the imperative to streamline operations and reduce expenses has become paramount. Amid the ongoing focus on cost savings within technology sectors, a significant oversight often occurs when managing data initiatives.

Over the past decade, data management technologies have evolved rapidly. Still, this evolution has led to what can be termed"modern legacy" systems—up-to-date technically yet operationally cumbersome and costly structures, much like legacies from two decades ago. These systems, initially designed to be cutting-edge, have become inefficient and slow over time, not fully aligning with the current needs and inadvertently leading to escalated costs.

The accumulation of such data is driven by a fear of losing potentially valuable insights, a phenomenon known as"sunk cost anxiety." Yet, to transition toward more cost-effective practices, businesses must critically assess their actual usage and utility, challenging long-standing assumptions and making tough decisions to discard or redesign underutilized or outdated data storage practices. This encourages them to think critically and challenge the status quo.

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