CompTIA Updated DA0-001 Exam Questions and Answers by casey

R is a statistical programming language that is specifically designed for data analysis and statistical modeling, making it highly suitable for creating a multiple linear regression model. It has extensive libraries such as lm() for linear modeling, which simplifies the process of model creation, diagnostics, and interpretation. R also provides robust tools for data manipulation and visualization, which are essential for preparing data for regression analysis and understanding the results123.

While Microsoft Power BI, SQL, and Tableau have capabilities for regression analysis, they are more limited compared to R. Power BI and Tableau are primarily business intelligence tools that offer some built-in analytics capabilities, but they are not as comprehensive as R. SQL is a database query language that can perform some statistical calculations, but it is not inherently designed for statistical modeling4567.

References:

Multiple Linear Regression in R: Tutorial With Examples - DataCamp1.

Implementing linear regression in Power BI - SQLBI5.

Choosing a Predictive Model - Tableau6.

How Predictive Modeling Functions Work in Tableau7.

When updating a legacy data source, it is a best practice to create a codebook to document field changes. A codebook serves as a detailed guide and record of the data structure, definitions, and any transformations or modifications made to the data fields. This documentation is crucial for maintaining data integrity, ensuring consistency, and facilitating future data use and understanding. It provides a reference that can be invaluable for data analysts, developers, and any stakeholders who need to work with the data.

Creating a codebook is preferred over placing old data in new fields, which can lead to confusion and data integrity issues. Keeping only the most recent data may result in the loss of valuable historical information. Removing the data source from production is not a practice related to updating data but rather to retiring a data source1234.

References:

Legacy Data Migration: A Comprehensive Guide | OpenGeeksLab

How to Successfully Complete Legacy Database Migration

Methods for Saving and Integrating Legacy Data - DATAVERSITY

Legacy Data Digitization - Learn The Best Practices