With the rise of cloud computing, classifying enterprise data has become more important than ever. Part of the reason is that it keeps data workflows efficient, but the real driver is the cost of data transfer, which can be brought down considerably if the available data is classified on key parameters. The right time to do this is now, especially when the volume of data to be sorted in low, and it is easy to create a good classification structure and build on it.
Here are the primary steps involved in data classification:
- Organization-wide interest: The first step is to get all the stakeholders involved by educating them about the importance of data classification. Since this is going to affect all data levels in the company, it’s best if all departments are in sync on this.
- Understand key drivers: It’s important to be able to ascertain as to what the key drivers are going to be. Would the data be classified based on frequency of use? Or perhaps on the sensitivity?
- Simple rules: The best systems are also the simplest ones in terms of guiding philosophy, and so should be your data classification system. Keeping classification rules simple also ensures full compliance. In other words, it keeps the data-quality high.
- Selecting technology: Companies can consider using enterprise auto-tiering solutions as a starting point and then extend the system to cover all possibilities.
Going forward, data management and maintenance are going to be a key challenge for all businesses, and the classification principles described here will help overcome the initial hurdles.
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