What is Data Classification

Data Classification is the process of organizing data into categories and subcategories so that the data can be used more effectively. It is helpful in data management, data security and its compliance. Written procedures and guidelines for data classification should define what category of data will the organization be using and what will be the role of each employee in classifying the data after that data life cycle should be focused upon.

With the advent of technology, there are lots of data available but managing the data is not that easy as what it looks as but the data classification comes into importance as it makes the work a lot easier as data can be maintained regularly keeping it aligns with the business objectives. In data security, data classification aids the proper secrecy of the types of data being retrieved or transmitted.

Data Discovery

Will it be easy to draw conclusions from the huge amount of data for your business system solutions? Through data discovery, it is quite easy as this term is related to business intelligence technology. It is the process of scanning data repositories and reports. It can find content for your organization, assists you in data governance and also perform data analysis and visualization. With data discovery, user searches for specific items in a data set and various visual tools make the process at your ease. By data discovery, you can also figure out various trends in patterns which would be difficult to figure it out otherwise.

Types of Data Classification

• Content – It checks files for confidential information
• Context – It looks at creator among other variables indirectly indicating sensitive information
• User – Relies upon user-based knowledge and at the user discretion to create and edit the documents

Or it can be in the form of

• Geographical
• Chronological
• Qualitative
• Quantitative

Benefits of Data Classification

• It can generate improvements in data centre performance and utilization
• It can reduce costs and administration overhead
• Can improve user access time by taking the assistance of data indexing
• Recovery time objective is improved redefining data protection

Business Data Classification approaches

There are basically three approaches to data classification within a business environment:

• Paper-based classification policy – This policy contains how any employees in the organization will deal with types of data keeping the overall data security policy into consideration. As the policy will be well devised, it will aid in taking quick decisions about data handling and management. The key to paper-based classification policy is that each and everyone should be aware of what is mentioned in the policy and should abide by it.
• Automated classification policy – In these classifications are applied by solutions that use software algorithms based on keywords in the content to analyze it. There is no certainty about the automated classification as sometimes it can predict inaccurate results which can result in organizations loss even.
• User-driven classification policy – In this the user is ultimately made responsible for selecting the label according to his own choice with the assistance of software at the time of creating it. The underlying reason for user involvement is that they can see through the context themselves and can further make informed decisions about which label to apply. This policy is often considered much safer than others as it also adds to other organizational benefits improving the ability to demonstrate compliance and managers can also foresee certain insider contingencies and take steps such as tightening the policy or providing training to prevent them.
•  

Steps for Effective Data Classification

• Get familiar with your data – Knowing beforehand which data type is to be used and where it is located will make you effectively classify the data.
• Create a policy – You have to stay consistent with the data protection principles and that is only possible by following and implementing proper policy. The policy should be short and simple and should necessarily contain elements like objectives, workflows, data schemes, data owners, etc
• Discover data – You have to find out that whether you are going to classify new data but care should be taken that old data must not be forgotten as it also needs to be automated besides the new data discovery application tools
• Apply labels – You can assign each data asset a label in order to further improve data classification. You can also automate your labels according to your data classification schemes
• Organize the data – When you have enough knowledge about your data and its policies then you can organize the data according to your organization’s needs
• Evaluate results – The results should be evaluated as it lets you know what all sensitive data you have and where it is stored. You can also review your data that whether is it protected or not. By evaluating your results you can control costs and improve the data management process
• Repeat– Data keeps on changing with different trends and patterns and it is dynamic in nature so the files are created and moved from one storage to another. Thus data classification should never stop in the business working environment as proper management of data will lead to making sure that the data is safely secure
•  

Data Classification Process

• Define the objectives – Before starting off with data classification process you must know what are you aiming for and whether the data you are targeting is relevant to your business or not and if not then you must look what is wrong with the objectives and how quickly it can be sorted out
• Create workflows – When classifying data you will be getting new as well old data but you should figure out how are you going to classify them and what process are you going to follow and also look out that you have or not have to create a new data classification criteria
• Define the categories – Which are the types of data you should be looking out for? The focus should be more on how will you evaluate those results after getting the desired categories for the various types of data
• Plan out for outcomes – After all the above-mentioned steps, you should organize your results so that they can be aligned with the business objectives and can produce efficient results

Data Categorization

Most of the employees in the organization don’t know the difference between various types of category of data. So here comes the ultimate significance of data categorization as the category is assigned by the user, the algorithms have information that can be used to appropriately assign the classification.

The first important step of categorization is to create category buckets and then to figure out which type of category would be useful for prediction and reporting.

Though categorization looks small it has the potential to make a huge impact. Data categorization is another great way which can let you know whether your data identification and data classification initiative are successful or not.

The categorization of data requires revaluation in the age of big data to make sure that secrecy of different types of data is maintained. Data categorization efforts with clear purposes result in improvement and prediction. There is various software with the help of which you can organize and streamline your useful data. Data categorization helps you to categorize various segments making it easier for you to deal with any kind of data.

The key to going for software or tools for your data categorization is that they have the potential to organize your data much better by applying various algorithms. It saves the time of data scientists as with the assistance of software they can able to contribute their time to many resourceful projects as tools can help churn through thousands of data rows so that your models get the fuel for working in the real world.

In the age of abundant and ubiquitous data, some data can be of paramount significance to us. The data needs to refine in a much more systematic and rigorous fashion whether done by machines or humans. AI may anytime take over the world but various types of thinking machines will have to work together to make various marketing efforts. All the data created from its inception until is destroyed can help your organization make sure that their data is safely secure.

Together with data categorization, as well as data classification and predictive analytics, work closely in assisting the business in growing to its utmost success as data is managed with the aid of these two processes. For data to be imported into the organization’s workforce, it is paramount to check its verifiability whether it is relevant to the organization or not and needs to be filtered initially.

The ability to discover the truth behind your data can go a long way to guarantee your company achieves and maintain its competitive edge. With the assistance of proper classification and categorization scheme, data threats can be reduced for your business. So commit to it, set up proper frameworks and rules and move onto automation on the organization is ready for it