The size of your organization doesn’t matter when it comes to data fragmentation. The issue can happen anytime data is being stored and used across multiple applications, systems, and storage devices. If you have data on a physical server and also in the cloud, chances are it’s fragmented.
While data fragmentation doesn’t usually make the information inaccessible, it can drag down efficiency. However, detecting data fragmentation in databases is relatively easy, and resolving the issue usually isn’t too complicated.
How to Detect Data Fragmentation
There are plenty of technical tools that can help detect data fragmentation. You can take advantage of tools that monitor performance, track data lineage, and analyze storage locations. The tools can identify inconsistencies and duplicate data. The tools can also look at response times. If these analytics are off, the tool will alert the user of the suspected problem.
Businesses can also use organizational methods to detect data fragmentation. These processes typically include performing audits, conducting user surveys, and running a process analysis. So, what should you do if one of your approaches indicates the presence of data fragmentation? Thankfully, you can take advantage of a few strategies that can resolve the problem.
Effective Strategies for Ending Data Fragmentation
Here’s a look at some of the strategies you can use to resolve your issues with data fragmentation.
Create and Enforce Data Management Policies
If you don’t have an effective data management policy, fragmentation usually occurs. Your policy should cover how data is accessed, stored, and handled. You also want to detail how the data should be protected.
Don’t forget about industry compliance requirements when it comes to data usage. Fines and penalties for being out of compliance can be steep, and this is before you factor in the hit to your brand’s reputation if a security breach occurs.
After creating the policy, ensure all staff have access to the guidelines. The policy should be easily enforceable and clear penalties laid out for non-compliance.
Consider Investing in Data Warehouses or Data Lakes
Some organizations may need both a data warehouse and a data lake. Others may be able to get by using one or the other. Both are types of data repositories but there are differences.
If you’re storing raw data, a data lake may be the better option. The data is processed in the lake and you can access it anytime you need to gain new insights. Data warehouses make it easier for businesses to analyze their information. The primary difference is the data is structured instead of raw.
Take Advantage of the Cloud
The cloud automatically comes with advantages any business can benefit from. The cloud is flexible, and scalable, and gives users access to a suite of data management tools. Some of the tools even work to prevent data fragmentation in databases.
Moving your data to the cloud allows you to centralize storage so your data doesn’t exist on multiple systems and apps. Everything is stored in a centralized location.
Implement AI-Driven Solutions
Manually running quality checks is an effective way to detect and eliminate data fragmentation issues but it’s time-consuming and frustrating. Implementing AI-driven solutions can effectively take care of your data monitoring needs, while also providing insights and analytics you can use to make operational decisions.
Some of the tools you can use include automating quality checks and searching for abnormal data patterns. AI solutions can also help identify areas that may be at risk for developing issues with data fragmentation.
Encourage Communication Between Stakeholders
Your stakeholders can include your IT department, data owners, and teams accessing the information. Even with an effective data management policy in place, you’re still going to run into issues with fragmentation if no one is communicating with each other.
By encouraging communication, you’re reducing the risk of data being duplicated across systems. You’re also reducing the risk of errors in the data. Along with encouraging communication, you also want to stress the importance of collaboration, as this helps ensure everyone is on the same page and following company-standardized data measures.
Don’t Ignore Privacy and Security Concerns
Whenever a business implements a new data management policy, questions about privacy and security generally come up. Don’t ignore these concerns, and be ready to address them to the best of your ability.
This may mean demonstrating security controls or improving your data encryption techniques. Remember, the more your team knows, the easier it is for them to stay in regulatory compliance. With a little work and taking advantage of other storage options, you can all but eliminate issues with data fragmentation in your workplace.