With outdated systems, companies risk reaching the limits of their data analysis capabilities, and they have a much harder time responding to dynamic market conditions,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:
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.
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.
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.
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:
The importance of futureproofing your data ecosystem
Key opportunities to build reliability and versatility into your data management strategy
Data management and data messaging structure options that accommodate new tools and technologies