With outdated systems, companies risk reaching the limits of their data analysis capabilities, and they have a much harder time responding to dynamic market conditions, delivering innovative products and services, and maintaining customer satisfaction. In data management, futureproofing means establishing a system with agile architecture and loosely coupled software components. In short, futureproofing means anticipating change.
Here are a few key opportunities to help you anticipate change through reliability and versatility:
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Avoid Vendor Lock-In
Vendor lock-in is a product of inaction. It happens when an enterprise sticks with a product or service designed by one vendor, regardless of quality, because it’s difficult or not financially viable to change partners. By minimizing competition, vendors can increase costs and de-prioritize innovation.
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Embrace Open-Standards Technology
Open standards are additive by design. For example, Hadoop and MongoDB are displacing proprietary storage systems from IBM, Microsoft, and Oracle. Similarly, delta lakes are a product of earlier innovations in file systems. Open standards encourage innovation and promote longevity by accommodating vendor agnostic approaches.
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Seek Vendor-Supported Compatibility
A collaborative data replication partner accommodates the evolution of data management strategy with flexible options for connecting open-standard and proprietary technologies.
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Consider Elastic Storage Repositories Like Delta Lakes
For greater efficiency, enterprises are moving away from databases and adopting data repositories that are inherently self-defining.
For additional detail on each of these strategies, read our white paper "How to Futureproof Data Management Strategy to Prioritize Change Data".
In this white paper, we’ll cover:
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The importance of futureproofing your data ecosystem
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Key opportunities to build reliability and versatility into your data management strategy
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Data management and data messaging structure options that accommodate new tools and technologies