Practice Test for DA0-001 Certification Real 2023 Mock Exam
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CompTIA DA0-001 certification exam, also known as the CompTIA Data+ certification, is a vendor-neutral credential that validates the skills and knowledge of IT professionals in data management, analysis, and interpretation. CompTIA Data+ Certification Exam certification is ideal for individuals who want to demonstrate their proficiency in working with data to their employers and enhance their career prospects in the field of data analysis.
NEW QUESTION # 95
Which one of the following is a common data warehouse schema?
- A. Spiral.
- B. Snowflake.
- C. Square.
- D. Sphere.
Answer: B
Explanation:
Snowflake enables data storage, processing, and analytic solutions that are faster, easier to use, and far more flexible than traditional offerings. The Snowflake data platform is not built on any existing database technology or "big data" software platforms such as Hadoop.
NEW QUESTION # 96
A publishing group has requested a dashboard to track submissions before publication. A key requirement is that all changes are tracked, as multiple users will be checking out documents and editing them before submissions are considered final. Which of the following is the BEST way to meet this stakeholder requirement?
- A. Present a data refresh date at the top of the dashboard.
- B. Display the version number next to each submission on the dashboard.
- C. Confirm the dashboard is adhering to the corporate style guide.
- D. Use permissions to ensure users only see certain versions of the submissions.
Answer: D
NEW QUESTION # 97
A data analyst is asked to create a sales report for the second-quarter 2020 board meeting, which will include a review of the business's performance through the second quarter. The board meeting will be held on July 15,
2020, after the numbers are finalized. Which of the following report types should the data analyst create?
- A. Real-time
- B. Static
- C. Dynamic
- D. Self-service
Answer: B
Explanation:
Explanation
A dynamic report is a type of report that shows data that changes or updates automatically based on certain criteria or parameters. A dynamic report can allow users to interact with the data, filter it, drill down into it, or visualize it in different ways. A dynamic report is suitable for situations where the data changes frequently or where real-time or near-real-time data is needed for decision making or analysis. In this case, the data analyst is asked to create a sales report for the second-quarter 2020 board meeting, which will include a review of the business's performance through the second quarter. The board meeting will be held on July 15, 2020, after the numbers are finalized. This means that the data analyst does not need to show real-time or dynamic data, but rather a fixed and accurate view of the sales data for the second quarter. Therefore, a static report would be the best way to meet this stakeholder requirement. Therefore, the correct answer is A. References: [What are Dynamic Reports? | Sisense], Static vs Dynamic Reports - What's The Difference? | datapine
NEW QUESTION # 98
Which of the following are reasons to conduct data cleansing? (Select two).
- A. To perform web scraping
- B. To improve accuracy
- C. To track KPls
- D. To review data sets
- E. To increase the sample size
- F. To calculate trends
Answer: B,F
Explanation:
Explanation
Two reasons to conduct data cleansing are:
To improve accuracy: Data cleansing helps to ensure that the data is correct, consistent, and reliable.
This can improve the quality and validity of the analysis, as well as the decision-making and outcomes based on the data12 To calculate trends: Data cleansing helps to remove or resolve any errors, outliers, or missing values that could distort or skew the data. This can help to identify and measure the patterns, changes, or relationships in the data over time13
NEW QUESTION # 99
An analyst modified a data set that had a number of issues. Given the original and modified versions:
Which of the following data manipulation techniques did the analyst use?
- A. Recoding
- B. Deriving
- C. Imputation
- D. Parsing
Answer: A
Explanation:
Explanation
The correct answer is B. Recoding.
Recoding is a data manipulation technique that involves changing the values or categories of a variable to make it more suitable for analysis. Recoding can be used to simplify or group the data, to correct errors or inconsistencies, or to create new variables from existing ones12 In the example, the analyst used recoding to change the values of Var001, Var002, Var003, and Var004 from numerical to textual form. The analyst also used recoding to assign meaningful labels to the values, such as
"Absent" for 0, "Present" for 1, "Low" for 2, "Medium" for 3, and "High" for 4. This makes the data more understandable and easier to analyze.
NEW QUESTION # 100
How many variables are normally shown on a standard heat map?
- A. 0
- B. 1
- C. 2
- D. 3
Answer: C
NEW QUESTION # 101
Which of the following will MOST likely be streamed live?
- A. Machine data
- B. Delimited rows
- C. Key-value pairs
- D. Flat files
Answer: D
NEW QUESTION # 102
Given the table below:
Which of the following boxes indicates that a Type Il error has occurred?
- A. 0
- B. 1
- C. 2
- D. 3
Answer: C
Explanation:
Explanation
A Type II error is a false negative conclusion, which means failing to reject a null hypothesis that is actually false. In the table, box 3 indicates that a Type II error has occurred, because it shows that the null hypothesis is accepted when it is false in reality. This means that the statistical test failed to detect a significant difference or relationship that actually exists. References: Type I & Type II Errors | Differences, Examples, Visualizations - Scribbr, Type I and type II errors - Wikipedia
NEW QUESTION # 103
What is an example of data in transit?
- A. Data on a hard disk.
- B. Data on a smartphone.
- C. Data on a network.
- D. Data in memory on a computer.
Answer: C
Explanation:
A data network is a system designed to transfer data from one network access point to one other or more network access points via data switching, transmission lines, and system controls. Data networks consist of communication systems such as circuit switches, leased lines, and packet switching networks.
NEW QUESTION # 104
Which of the following is an example of a discrete variable?
- A. The number of people in an office
- B. The height of a horse
- C. The temperature of a hot tub
- D. The time to complete a task
Answer: A
NEW QUESTION # 105
Which of the following database schemas features normalized dimension tables?
- A. Hierarchical
- B. Flat
- C. Star
- D. Snowflake
Answer: D
Explanation:
Explanation
The correct answer is B. Snowflake.
A snowflake schema is a type of database schema that features normalized dimension tables. A database schema is a way of organizing and structuring the data in a database. A dimension table is a table that contains descriptive attributes or characteristics of the data, such as product name, category, color, etc. A normalized table is a table that follows the rules of normalization, which is a process of reducing data redundancy and improving data integrity by organizing the data into smaller and simpler tables12 A snowflake schema is a variation of the star schema, which is another type of database schema that features denormalized dimension tables. A denormalized table is a table that does not follow the rules of normalization, and may contain redundant or duplicated data. A star schema consists of a central fact table that contains quantitative measures or facts, such as sales amount, order quantity, etc., and several dimension tables that are directly connected to the fact table. A snowflake schema differs from a star schema in that the dimension tables are further split into sub-dimension tables, creating a snowflake-like shape13 A snowflake schema has some advantages and disadvantages over a star schema. Some advantages are:
It reduces the storage space required for the dimension tables, as it eliminates the redundant data.
It improves the data quality and consistency, as it avoids the update anomalies that may occur in denormalized tables.
It allows more detailed analysis and queries, as it provides more levels of dimensions.
Some disadvantages are:
It increases the complexity and number of joins required to retrieve the data from multiple tables, which may affect the query performance and speed.
It reduces the readability and simplicity of the schema, as it has more tables and relationships to understand.
It may require more maintenance and administration, as it has more tables to manage and update13
NEW QUESTION # 106
Which of the following variable name formats would be problematic if used in the majority of data software programs?
- A. First_Name
- B. First Name
- C. FirstName
- D. First_Name_
Answer: B
NEW QUESTION # 107
An e-commerce company recently tested a new website layout. The website was tested by a test group of customers, and an old website was presented to a control group. The table below shows the percentage of users in each group who made purchases on the websites:
Which of the following conclusions is accurate at a 95% confidence interval?
- A. In France, the increase in conversion from the new layout was not significant.
- B. In Germany, the increase in conversion from the new layout was not significant.
- C. The new layout has the lowest conversion rates in the United Kingdom.
- D. In general, users who visit the new website are more likely to make a purchase.
Answer: B
Explanation:
Explanation
The p-value is a measure of how likely it is to observe a difference in conversion rates as large or larger than the one observed, assuming that there is no difference between the groups. A common threshold for statistical significance is 0.05, meaning that there is a 5% or less chance of observing such a difference by chance alone.
The table shows the p-values for each country, and we can see that only Germany has a p-value above 0.05 (0.13). This means that we cannot reject the null hypothesis that there is no difference in conversion rates between the test and control groups in Germany. Therefore, the increase in conversion from the new layout was not significant in Germany. For the other countries, the p-values are below 0.05, indicating that the increase in conversion from the new layout was statistically significant. Option A is correct.
Option B is incorrect because the increase in conversion from the new layout was significant in France (p-value = 0.002).
Option C is incorrect because it does not account for the variation across countries. While the overall conversion rate for the test group (8.4%) is higher than the control group (6.8%), this difference may not be statistically significant when we consider the country-specific effects.
Option D is incorrect because the new layout has the highest conversion rate in the United Kingdom (9.6%), not the lowest.
References:
P-value Calculator & Statistical Significance Calculator
p-value Calculator | Formula | Interpretation
How to obtain the P value from a confidence interval | The BMJ
Confidence Intervals & P-values for Percent Change / Relative Difference
NEW QUESTION # 108
You are working with a dataset and need to swap the values in rows with those in columns.
What action do you need to perform?
- A. Filtering.
- B. Transposition.
- C. Recording
- D. Aggregation.
Answer: B
Explanation:
Transpose creates a new data file in which the rows and columns in the original data file are transposed so that cases (rows) become variables and variables (columns) become cases. Transpose automatically creates new variable names and displays a list of the new variable names.
Transposing data is useful for data analysis. At times, we have to pull data from various files with different formats for analysis and preparing reports. In such circumstances, we may have to transpose some data from one file to the other. In excel, we can transpose data in multiple ways.
NEW QUESTION # 109
A customer list from a financial services company is shown below:
A data analyst wants to create a likely-to-buy score on a scale from 0 to 100, based on an average of the three numerical variables: number of credit cards, age, and income. Which of the following should the analyst do to the variables to ensure they all have the same weight in the score calculation?
- A. Recode the variables.
- B. Normalize the variables.
- C. Calculate the standard deviations of the variables.
- D. Calculate the percentiles of the variables.
Answer: B
NEW QUESTION # 110
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