While there are benefits to centralizing data and deploying applications nearby, there are also some notable drawbacks. Companies can find themselves uncomfortably dependent on a specific architecture or industry vendor. Variables like outages, price changes, and contractual or geopolitical issues can extend beyond the company’s risk tolerance. Once your dataset and applications reach a certain size, it’s a challenge to migrate away from that configuration.

The effects of data gravity might also complicate data backups.  Full backups and large restores can take days if everything is being pulled across a network. Backup operators should test their backup and restore processes regularly to ensure their recovery objectives can be met. These tests should also expose bottlenecks, bandwidth issues, compliance gaps, broken dependencies, or restores that appear successful but are ultimately unusable. You may also find that you are overprotecting your low-value data or not protecting your critical data well enough.

Managing data gravity comes down to a small set of intentional acts and processes:

• Know where your data gravity exists
• Design your architecture to work with it rather than against it
• Use governance, lifecycle, and placement controls to manage costs and risk

By deliberately centralizing data only where it creates real value, companies can mitigate the negative impacts while still getting the performance and insight they need. When it’s understood and properly managed, data gravity can be used as a strategic advantage.