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07. July 2021

The Data Life Cycle: Where Is Your Information Most Vulnerable?

As data travels through the data life cycle, it faces unique risks and security challenges in each phase. Understanding the differences between these phases and the obstacles they present is crucial to data security.

Data security is now a top priority for organizations worldwide. Breaches are costly and added fines from regulators only make matters worse. However, as your data travels through the data life cycle, it faces unique risks and security challenges in each phase. Understanding the differences between these phases and the obstacles they present is crucial to ensuring maximum data security and usability.

Phase One: Data Creation

For our intents and purposes, data creation includes data created by your organization's daily operations as well as data brought into your organization from outside sources. This phase is especially important. Proper security and data management at this phase will reduce data risk going forward through the cycle. Unfortunately, many organizations fail to apply any sort of security protocol at this phase.

If you don't track data from the moment it's created, you'll have a difficult time finding it again later in the cycle. It's easy for this data to end up as dark data or ROT data if you're not careful. In addition, many programs and employees create data that's not intended for future use, which poses additional security risks. You should use an automated platform that detects new data and tags it accordingly.

Risk Assessment: Moderate

While brand new files are unlikely to end up in a breach, poor management in this phase can lead to problems down the road. Ensure that your newly created data is being properly catalogued and stored to prevent security issues later on.

Phase Two: Data Processing

Once data has been created, it needs to be organized and compiled for analysis. Your data analysts will take this data and feed it into your business intelligence(BI) tools. If your data was properly ingested into your file system, you should have little to no trouble with this step. Problems generally arise when data doesn't get labeled correctly and bypasses this step entirely.

Data processing also acts as a useful filter.Bad data can be discarded early, or it can be corrected. However, you want your analysts to spend the bulk of their time analyzing, so make sure they can retrieve the data they need quickly.

Risk Assessment: Low

In the processing phase, data is generally kept in a closed environment and is being curated by professional analysts. Your data is in good hands, for now.

Phase Three: Data Usage

With your data created and processed, it's time to put it to use. Other departments start to access this data in this phase, and that's where problems can begin.For starters, if your organization doesn't handle data uniformly from one department to the next, you could end up with unintentional duplicates all over your company. Data silos also complicate data sharing from one department to the next.

Duplicates duplicate your risk. Silos prevent IT managers from seeing all the data in your organization. It becomes very difficult to know your data when multiple people start to access it and use it in their own way. Does your organization have a powerful search tool that can bypass silos and ensure everyone is working on the same file?

Risk Assessment: High

This is absolutely the riskiest part of the data life cycle. Previously, only a couple of people used your data, and they were generally people with knowledge of cybersecurity and data management. But now, many employees are using data indifferent ways. They may not all follow best practices and could expose your data to intruders.

Further complicating matters is the fact that you may not be able to control every device that accesses this data. Suppose a worker is at home on their personal computer and accesses your files. How can you be certain that their computer is secure? You need to be able to know your data, regardless of where it goes.

Phase Four: Data Archival

Once data has served its purpose, it ought to be locked away in storage for future use. Most companies are reluctant to do this until they're absolutely sure that data is no longer needed. However, smart data management combined with intelligent storage solutions can solve this problem automatically.

Risk Assessment: Moderate

You can reduce your risk here by archiving data as soon as it's not needed. Consider configuring automatic archival of documents that haven't been touched in a given interval.

Phase Five: Data Deletion

Here's where you get to send that data down the memory hole and say goodbye to your risk once and for all. Your risk is very low here unless you forget to do this step, in which case your risk skyrockets.

Ask Aparavi for a data assessment to find out how your company's data risk stacks up. We can help you reduce it and get to know your data better than ever before.