Data classification (data management)

In the field of data management, data classification as a part of Information Lifecycle Management (ILM) process can be defined as a tool for categorization of data to enable/help organization to effectively answer following questions:

When implemented it provides a bridge between IT professionals and process or application owners. IT staff is informed about the data value and on the other hand management (usually application owners) understands better to what segment of data centre has to be invested to keep operations running effectively. This can be of particular importance in risk management, legal discovery, and compliance with government regulations. Data classification is typically a manual process; however, there are many tools from different vendors that can help gather information about the data.

Note that this classification structure is written from a Data Management perspective and therefore has a focus for text and text convertible binary data sources. Images, videos, and audio files are highly structured formats built for industry standard API's and do not readily fit within the classification scheme outlined below.

First step is to evaluate and divide the various applications and data into their respective category as follows:

Types of data classification - note that this designation is entirely orthogonal to the application centric designation outlined above. Regardless of structure inherited from application, data may be of the types below

1. Geographical : i.e. according to area (supposing the rice production of a state or country etc.) 2. Chronological: i.e. according to time (sale of last 3 months) 3. Qualitative  : i.e. according to distinct categories. (E.g.: population on the basis of poor and rich) 4. Quantitative : i.e. according to magnitude(a) discrete and b)continuous

Note that any of these criteria may also apply to Tabular or Relational data as "Basic Criteria". These criteria are application specific, rather than inherent aspects of the form in which the data is presented..

These criteria are usually initiated by application requirements such as:

Note that any of these criteria may also apply to semi/poly structured data as "Basic Criteria". These criteria are application specific, rather than inherent aspects of the form in which the data is presented.

Benefits of effective implementation of appropriate data classification can significantly improve ILM process and save data centre storage resources. If implemented systemically it can generate improvements in data centre performance and utilization. Data classification can also reduce costs and administration overhead. "Good enough" data classification can produce these results:

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