We are growing data at exponential rates. This amount only increases when you use or rely on AI tools, which are very fast and very efficient at generating and extracting information. With all that data, however, comes cost.
On average, around 49% of your business cloud storage billing costs goes to data and usage fees, while the rest goes to the actual capacity. Worse, around 62% of polled businesses state they exceeded their budget spending in 2024. In comparison, that number was only 53% in 2023.
Data is getting bigger, and the costs to manage it are going to increase, even with AI.
The good news is that cleaning up your data footprint can bring many benefits:
- Reduced overhead
- Improved security
- More efficient (and reliable) tool integration
How do you get started with reducing your data and improving your data management? There are several solutions. Here are the top options in 2025:
Centralizing Your Data
Centralizing data is an effective way to bring all data sources into a single data warehouse. With all the information in a single repository, you’ll be able to more efficiently clear out duplicates, stack files so historical data is located in reach of current reports, and so on. A centralized system that’s fully marked up with metadata is also how you can more efficiently use automation, ML, and other AI tools, since you’ve done the bulk of the hard work already. You can use solutions like integration platform as a service (iPaaS) to ingest data from multiple sources into one data warehouse, for example.
Centralizing data, however, is just the start. You also need to sort it, classify it, and mark it up.
Data Security Posture Management
That’s where data security posture management comes into play. Now, DSPM systems can link between multiple systems at once and don’t need a centralized repository, but the rest of your systems might. The good news is that DSPM can work just as well with one data repository as opposed to multiple cloud and on-premises accounts.
What DSPM does is it works to find all your data (including shadow data) and sorts it by classification. This does several things:
- Helps you understand which files contain sensitive data and which don’t.
- Allows you to easily see access limits, so you can improve your access strategy and prevent unauthorized use of your data.
- Identifies data duplicates so you can streamline your datasets.
- Keeps your business compliant with policies like GDPR by identifying the types of data you need to purge.
Every one of these outcomes helps you save on your overhead.
Purge Your Data
Not all data is important or needed. If you used to offer a service that you no longer offer, for example, it’s best to archive those files and potentially store them offline. This keeps them on hand if you need them, but keeps them off your “in use” data repositories.
There is also redundant, obsolete, and trivial (ROT) data. What this means to you will depend on your goals, needs, and business type. Duplicate files are an easy example. Others include expired server session cookies or out-of-date documents. Think ROT data is minimal? Think again. A Veritas Global Databerg Report found that 85% of stored data is either dark or ROT data.
Using a centralized repository and DSPM can help you find, identify, and purge these files and free up your cloud storage space (and reduce costs).
