Data classification is one of the most important tasks in academic research. Manually, it is a lengthy process; thus, this article aims to summarise the process by giving you an overview of a few simple data classification tools like Databox, Google data studio and SPSS. So let’s start:
Data Classification- An overview
Classification of data is the process of organising large sets of data into smaller categories or sub-categories that make it easy to retrieve and analyse at later stages. In this context, the main aim of data classification is to sort or store data in a way that is easy to retrieve. As stated in another way, it tags the data by taking its type, value, and sensitivity into consideration. Market research, it tells an organisation to value their data and find if any risk is associate with the data to implement control to mitigate risks. In academic research, that aims to add new bodies of information to the existing ones, it helps researchers maintain the confidentiality and integrity of their data. Additionally, for lowering the vulnerability of sensitive data, data classification is equally important.
Data classification offers a wide array of methods to classify data as per research requirements. It includes content-based, context-based, and user-based methods of classification. Moreover, to lower the vulnerability of sensitivity, it asks students to use three levels high, medium, or low. The dimension and state of data can be in rest, process or transit, while it can be in the form of either structure or unstructure format.
In short, academic research asks students to follow a cascade of events to finally store their data in an easy-to-retrieve format. But fortunately, we must be thankful for artificial intelligence because now we have tons of data classification tools that can complete all these tasks within a fraction of time. However, if you are facing some problems related to dissertation writing, you must look forward to dissertation writing services along with effective data classification tools.
Data Classification Tools
Data classification tools are the software and toolkits that help researchers in discovering and taging hidden or unknown data. These tools are known for catalysing the classification of data without compromising data confidentiality and sensitivity. In simple words, they are effective in giving almost the same results that you may get after following a step-by-step guide to data classification.
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Databox:
It is one of the most common user-friendly data classification tools. It compiles data in one place and helps store it for long terms. Basically, it is a cloud-based business analytical tool that allows data analysts to create custom dashboards by scrapping data from various sources. These dashboards are useful for displaying data on the screens, which makes it easier for researchers to classify or categorise the data based on sensitivity or content. Additionally, dropbox also offers a list of other existing features to its customer, like:
- API
- Acess control/permission
- Activity dashboards
- Ad hoc reporting
- Alert/ Escalation
Google Data Studio:
It is another top-rated tool in the list of data classification tools. The most probable reason for its popularity is that it can easily create files or reports on data collected from a variety of sources. Within a fraction of a time, it allows you to reach various databases such as PostgreSQL, BigQuery, and MySQL. As a data analytical tool, Google data studio gives valuable insight into websites, apps, and other internet devices that makes data classification. It is a good option for even your dissertation research. It allows its users to add, erase, and sort columns or rows where or when needed. In addition to data classification, it also helps you in better visualisation and reporting of data. Especially when you want to store it for a long period.
SPSS:
SPSS is powered by IBM; it offers a number of features but can help classify only quantitative data. It helps researchers to make categories and sort similar data under one and only one category. SPSS allows researchers to select categories, specify characteristics for classification, and present data in graphical or tabular form. These graphical representations are easy to store and retrieve as well. Even if you want to make a classification tree by using the collected data, SPSS is equally important.
Like SPSS, there are various data analysis tools or bases such as BLAST, NCBI, and CLUSTALW2 that helps researcher (especially medical or genomic) to find. classify and store them in an easy-to-read format.
Final Thoughts:
Data classification is a long process that demands researchers to follow a detailed guide. Even after following a detailed guide, the chances of missing any useful information are still very high. Thus, to speed up as well as reduce the chances of mistakes. Data classification tools like Databox, Google Data Studio, SPSS, BLAST, NCBI, and CLUSTALW2 are great potions.
