Three Main Approaches to Data Discovery | CCSP Exam Preparation

Not one of the three main approaches to data discovery

Question

When data discovery is undertaken, three main approaches or strategies are commonly used to determine what the type of data, its format, and composition are for the purposes of classification.

Which of the following is NOT one of the three main approaches to data discovery?

Answers

Explanations

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A. B. C. D.

B.

Hashing involves taking a block of data and, through the use of a one-way operation, producing a fixed-size value that can be used for comparison with other data.

It is used primarily for protecting data and allowing for rapid comparison when matching data values such as passwords.

Labels involve looking for header information or other categorizations of data to determine its type and possible classifications.

Metadata involves looking at information attributes of the data, such as creator, application, type, and so on, in determining classification.

Content analysis involves examining the actual data itself for its composition and classification level.

Data discovery is an essential step in the data classification process, which involves identifying sensitive or confidential data, determining its value and potential risks, and applying appropriate security controls to protect it. The main goal of data discovery is to gain an understanding of the data and its characteristics, such as its type, format, structure, and location, so that it can be classified correctly and managed accordingly.

Three primary approaches or strategies are commonly used for data discovery:

A. Content analysis: Content analysis involves examining the actual data to determine its type, format, and composition. This approach is typically used for unstructured or semi-structured data, such as text, images, audio, or video files. Content analysis may involve using automated tools, such as data mining or pattern recognition algorithms, to identify keywords, phrases, or patterns that are indicative of sensitive or confidential information.

B. Hashing: Hashing involves creating a unique digital signature or "hash" of the data, which can be used to identify and compare similar or identical data across different systems or environments. Hashing is often used for structured data, such as databases or spreadsheets, and can be performed on the entire data set or specific fields or columns.

C. Labels: Labeling involves applying pre-defined or custom tags or labels to data based on its classification status or other attributes. Labels can be used to identify data that is sensitive, confidential, or requires specific security controls or handling procedures. Labels can also be used to track data throughout its lifecycle and ensure that it is managed appropriately.

D. Metadata: Metadata involves collecting and analyzing data about the data, such as its file name, size, creation date, author, or location. Metadata can be used to identify data that is sensitive or confidential, track data usage or access patterns, and ensure compliance with regulatory or legal requirements.

Therefore, the answer to the question is B. Hashing, as it is not one of the three primary approaches to data discovery.