CompTIA Updated DA0-001 Exam Questions and Answers by minahil

Year-over-year (YoY) comparison is a method of evaluating two or more measured events to compare the results at one period with those from a comparable period on an annual basis. For a year-over-year comparison of Q2 2020 sales, the analyst should compare the sales figures from Q2 2020 with those from Q2 2019. This comparison will show the growth, stagnation, or decline in sales over the year and is a common practice in financial analysis to assess performance.

Logical functions are used in spreadsheets to create conditions that return YES/NO or TRUE/FALSE results. These functions include IF, AND, OR, NOT, etc., which are specifically designed for decision-making processes in data analysis. For example, the IF function in Excel evaluates a condition and returns one value if TRUE and another if FALSE, perfectly implementing YES/NO logic.

CompTIA Data+ Reference:

CompTIA Data+ Study Guide (Exam DA0-001), Chapter 4: Data Manipulation and Analysis, Section “Data Manipulation Functions – Logical”, Official CompTIA CertMaster Learn for Data+, Module 4.3 “Logical Functions in Spreadsheets”.

In data management,duplicate datarefers to identical records that appear multiple times within a dataset. Such duplicates can lead to inaccurate analyses, inflated metrics, and erroneous business decisions. Identifying and removing duplicate records is a critical step in the data cleansing process to ensure data quality and reliability.

Option A:Duplicate data

Rationale:The dataset shows that the record with ID 376, Amount $400, and SKU ABV-DYH appears twice. This repetition indicates the presence of duplicate data, which can skew analysis results if not addressed.

Option B:Imputed data

Rationale:Imputed data refers to missing or incomplete data that has been estimated or filled in based on other available information. There is no evidence in the provided dataset to suggest that any data has been imputed.

Option C:Redundant data

Rationale:Redundant data involves unnecessary repetition of data across different fields or tables, leading to inefficiencies. While duplicate data is a form of redundancy, in this context, the specific issue is the exact repetition of entire records, making "duplicate data" the more precise term.

Option D:Corrupt data

Rationale:Corrupt data refers to data that has been altered or damaged, making it incorrect or unusable. The dataset provided does not exhibit signs of corruption, such as garbled text or invalid formats.

A star schema has a central fact table linked to multiple dimension tables. The dimension tables are typically denormalized, meaning data is stored in a flat, non-normalized format for faster query performance. This design enables efficient queries in data warehousing and business intelligence.

CompTIA Data+ Reference:

CompTIA Data+ Study Guide (Exam DA0-001), Chapter 3: Databases and Data Sources, Section “Star Schema Design and Usage”, Official CompTIA CertMaster Learn for Data+, Module 3.6 “Data Warehousing Schemas”.

References Used:

CompTIA Data+ Study Guide (Exam DA0-001) – Official Sybex/CompTIA Book

CompTIA CertMaster Learn for Data+ – Official CompTIA Learning Modules

CompTIA Data+ Objectives (DA0-001)