Many companies need to have and implement a data classification policy. One of the reasons is because some data needs to comply with certain laws and regulations, especially those that deal with personal information. Another reason is because companies can ease their work by tagging all their data, which helps employees, and everyone involved in the business find it efficiently and quickly.
A well designed data classification policy helps every company meet legal requirements and regulatory ones in cases of retrieving specific information within a set timeframe. This is the main motivation for the implementation of a proper data classification technology. Of course, a company can also benefit from de-duplicating their information, which helps minimize storage and back-up costs, and increases the speed of data searches.
Data strategies are different from one company to another, because each business generates different types and volumes of data. A company’s data may contain everything from office documents, customer and product information, e-mail correspondence, images, video files, to financial data. Although it may seem like a good idea to classify and tag the entire database of a company, many experts in the field say this shouldn’t be the case.
Data classification of the entire database is not only a very expensive activity, but very few companies manage to do it well. Certified database technologies can be very helpful and tag every data item, but this is something only governments do because of the high costs. Instead of doing this, companies should choose only certain type of data to classify, usually the data required by regulations and laws, and the data that is important in the company’s business, such as commercially valuable data.
Most companies should begin to classify their data in line with their confidentiality requirements, adding more security for increasingly confidential data, like salary data for example. This type of data could do a lot of harm both externally and internally, and this is why some information should be more protected than other. Companies should also consider the integrity of the data, aside from the confidentiality, because low-quality data should not be trusted. Another thing to consider is the availability of the data, because if it is highly available, then it will require a strong storage and networking environment.
The data should be tagged the right way, with the help of an effective metadata strategy. Most companies are overwhelmed with data, some relational and some non-relational, and a big part of it is redundant and has different quality degrees. This means the company needs to create a plan, and can do so with the help of a data architecture team. The data’s structure and general content needs to be documented, along with any known business rules and regulations. After the platform of initial metadata is established, the company can then create and implement what it is called “classification taxonomy”.