Question

A data analyst is working on a project. They need additional data from a third party to complete the analysis. What type of information would the data analyst consider to confirm that the data is reliable?

O Table names
O Database names
O Metadata
O Database access logs

Answer 1

The data analyst would consider metadata and database access logs to confirm that the data is reliable.

Step-by-step explanation:

The data analyst would consider the following types of information to confirm that the data is reliable:

1. Metadata: This includes information about the data, such as its source, date of collection, and any transformations that have been applied.
2. Database access logs: These logs can provide information about who has accessed the data, when, and what actions have been performed.

By analyzing metadata and database access logs, the data analyst can verify the integrity and quality of the data before using it in their analysis.

Answer 2

A data analyst should look at the metadata to confirm the reliability of additional third-party data. Metadata includes details such as the author, date, purpose, and data collection methodology, which are critical for assessing data relevance and accuracy.

Step-by-step explanation:

When a data analyst is seeking to use additional data from a third party, reliability of the data is crucial for accurate analysis. To ensure the reliability of the data, the analyst would need to consider various aspects that assure the data's validity and appropriateness for the task at hand. One of the key elements to look at is the metadata, which provides information about the data itself, including how it was collected, by whom, when, and what the data values represent. This information is vital as it allows the analyst to assess the relevance, accuracy, and potential biases within the data, which could affect the outcomes of the project.

Metadata can include details such as the data's author, date of creation, the purpose behind the data collection, and the methodology used. This level of detail can help the analyst ascertain the credibility of the source and the likely accuracy of the data. Additionally, the metadata might reveal the structure of the database through attributes like column names, data types, and records count, which are integral for mapping the data correctly into the analyst's working environment and for understanding the context and content of the data.

Given that reliability is paramount in data analysis, metadata checks are a systematic approach that enables analysts to have a deeper understanding of the secondary data they incorporate into their work, helping them make informed decisions when interpreting results and drawing conclusions.