Data classification: Performance and optimization

In this article we present an extended description of the third area mentioned by Gartner. The improvement of which is ensured by the implementation of File Analysis Software. The case may be of particular interest to data analysts and system architects responsible for data processes and systems in organization. It is true that it is difficult to describe a use case more generally than “performance and optimization”, but we will do our best to detail it.

Gartner in their File Analysis Software Market Guide extends the description a bit by writing about:

• optimization of resources related to the management of unstructured data,

• ensuring the operational efficiency of users when using data.

See more: INFORMATION CLASSIFICATION VERSUS DATA CLASSIFICATION – WE WERE HERE BEFORE IT!

And further lists the following sub-items which points directly to data classifiers, as they:

• Provide effective access to content based on type, usage, etc.

• Locate outdated or redundant data.

• Help to optimize processes, eg identify heavily used data for transfer to faster technologies or infrastructure in the cloud.

Organizational effectiveness is based on users getting data users where and how they want to use it, such as in CCP (Cisco Container Platform) or SaaS collaboration solutions, across accounts and devices, and having that data available from anywhere.

The most common use cases related to performance and optimization

1. Reducing disk space occupied and/or to improve storage efficiency.

They are often triggered by events such as cloud migration, file share updates, or datacenter consolidation. Such events include content scanning and deciding whether to move content to a new destination or delete to optimize performance and reduce costs.

This includes situations such as:

• Enable organizations to optimize storage.

• Find and eliminate redundant and outdated data that may lead to business difficulties, such as multiple copies of a contract.

• Migration of data to the appropriate repositories.

• Enable safe removal of unnecessary data.

Watch also:

Enable better access to unstructured data by helping to move data to more used repositories such as CCPs and through Google-like search interfaces with access to indexes created during data scanning.

Opinion? The classifier allows you to determine which data is unnecessarily redundant, unnecessary or inadequately stored.

2. Reduce the process time in terms of three qualities: cost, time, quality

The introduction of the classifier allows process owners to track the data flowing within them and react to:

• Unnecessary delays.

• Unnecessary actors in the flow.

• Redundant data in the process.

All based on the analysis of metadata assigned to files processed as part of the process.

3. Shortening the time of access to data – I don’t think we need to explain.

Scan and classify unstructured data in local, cloud or hybrid environments:. Identify and classify based on content, usage, age, unused, redundant, etc.

We also covered this point in the article on the impact of classification on corporate governance and compliance. The ability to classify on the basis of content, according to the Gartner report, increases the efficiency of working with data by over 40%. Thanks to the automated implementation of labels on data, people will make fewer errors related to their processing . Which will overall affect the efficiency of work in the organization.

These activities help reduce costs in IT and the entire organization while improving the efficiency of employees. Unstructured data management and compliance is virtually impossible without a clear understanding and mapping of the various data repositories, which is provided by file analysis.

In conclusion, we cannot talk about working effectively with data without classifying it. The mere possibility of assessing the value of a document at a glance by looking at its label saves you a few seconds working with each document.