CompTIA CompTIA Certifications DA0-001 Questions & Answers

• Question 141:

  Which of the following will MOST likely be streamed live?

  A. Machine data

  B. Key-value pairs

  C. Delimited rows

  D. Flat files

  Correct Answer: A

  Explanation: Machine data is the most likely type of data to be streamed live, as it refers to data generated by machines or devices, such as sensors, web servers, network devices, etc. Machine data is often produced continuously and in large volumes, requiring real-time processing and analysis. Other types of data, such as key-value pairs, delimited rows, and flat files, are more likely to be stored in databases or files and processed in batches.

• Question 142:

  Which one of the following in NOT a common data integration tool?

  A. XSS

  B. ELT

  C. ETL

  D. APIs

  Correct Answer: A

  Cross-site Scripting (XSS) is a security vulnerability usually found in websites and/or web applications that accept user input.

  XSS is a client-side vulnerability that targets other application users, while SQL injection is a server-side vulnerability that targets the application's database. How do I prevent XSS in PHP? Filter your inputs with a whitelist of allowed

  characters and use type hints or type casting.

• Question 143:

  What analytics suite is offered by Microsoft and directly integrates with SQL Server Databases?

  A. Qlik.

  B. Power BI.

  C. Domo.

  D. Dataroma.

  Correct Answer: B

  Power BI is a collection of software services, apps, and connectors that work together to turn your unrelated sources of data into coherent, visually immersive, and interactive insights. Your data may be an Excel spreadsheet or a collection of cloud-based and on- premises hybrid data warehouses.

• Question 144:

  An analyst has received the requirements for an internal user dashboard. The analyst confirms the data sources and then creates a wireframe. Which of the following is the NEXT step the analyst should take in the dashboard creation process?

  A. Optimize the dashboard.

  B. Create subscriptions.

  C. Get stakeholder approval.

  D. Deploy to production.

  Correct Answer: C

  Getting stakeholder approval is the next step the analyst should take in the dashboard creation process, after confirming the data sources and creating a wireframe. Stakeholder approval means getting feedback and validation from the intended users or clients of the dashboard, to ensure that it meets their expectations and requirements. This step helps to avoid rework and ensure customer satisfaction. References: CompTIA Data+ Certification Exam Objectives, page 14

• Question 145:

  Which of the following describes the method of sampling in which elements of data are selected randomly from each of the small subgroups within a population?

  A. Simple random

  B. Cluster

  C. Systematic

  D. Stratified

  Correct Answer: D

  Explanation: This is because stratified is a type of sampling in which elements of data are selected randomly from each of the small subgroups within a population, such as age groups, gender groups, or income groups. Stratified sampling can be used to ensure that the sample is representative and proportional of the population, as well as reduce the sampling error or bias. For example, stratified sampling can be used to select a sample of voters from different political parties based on their proportion in the population. The other types of sampling are not the types of sampling in which elements of data are selected randomly from each of the small subgroups within a population. Here is why:

  Simple random is a type of sampling in which elements of data are selected randomly from the entire population, without dividing it into any subgroups. Simple random sampling can be used to ensure that every element in the population has an equal chance of being selected, as well as avoid any systematic error or bias. For example, simple random sampling can be used to select a sample of students from a school by using a lottery or a computer-generated number. Cluster is a type of sampling in which elements of data are selected randomly from a few large subgroups within a population, such as regions, districts, or schools. Cluster sampling can be used to reduce the cost and complexity of sampling, as well as increase the feasibility and convenience of sampling. For example, cluster sampling can be used to select a sample of households from a few neighborhoods by using a map or a list. Systematic is a type of sampling in which elements of data are selected at regular intervals from an ordered list or sequence within a population, such as every nth element or every kth element. Systematic sampling can be used to simplify and speed up the sampling process, as well as ensure that the sample covers the entire range or scope of the population. For example, systematic sampling can be used to select a sample of books from a library by using an alphabetical order or a numerical order.

• Question 146:

  Joe. an analyst. tests the loading time on a dashboard he is preparing to go live and finds it is slower than he would like. Which of the following must occur to decrease the loading time?

  A. Deploy the dashboard to production.

  B. Change the field definitions.

  C. Update the dashboard subscribers.

  D. Optimize the dashboard.

  Correct Answer: D

  Optimizing the dashboard is the process of improving its performance and reducing its loading time by applying various techniques and best practices. Some of the common ways to optimize a dashboard are: Reducing the size and complexity of the data model, such as removing unnecessary columns, aggregating data at the source, or using data compression techniques12 Leveraging caching strategies, such as setting appropriate cache refresh intervals or utilizing Power BI's built-in caching mechanisms, to minimize data retrieval delays2 Utilizing query folding, direct query, or live connection to enhance data processing efficiency and enable real-time data updates23 Optimizing DAX queries, such as avoiding nested calculations, using variables, or simplifying measures, to improve data calculation speed23 Reducing visualizations and calculations, such as using fewer or simpler charts, filters, or parameters, to speed up dashboard rendering12 Evaluating the impact of custom visuals on dashboard load time and avoiding or replacing those that are slow or inefficient2 Applying aggregation and summarization techniques, such as using extract filters, context filters, or level of detail expressions, to reduce the amount of data displayed on the dashboard1 Troubleshooting and resolving any issues that may cause slow dashboard load, such as network latency, server overload, or hardware limitations24

• Question 147:

  What R package makes it easy to work with dates?

  A. Lubridate.

  B. Datemath.

  C. Stringr.

  D. ggplot.

  Correct Answer: A

  Lubridate is an R package that makes it easier to work with dates and times.

• Question 148:

  A collections manager has a team calling customers who are past due on their accounts in an attempt to collect payments. The manager receives the call list in the form of a printed report that is generated by the accounting department at the beginning of each week. Consequently, the collections team calls some customers who have made payments in the time since the report was last printed. Which of the following reporting enhancements could the accounting department implement to best reduce the number of calls on current accounts?

  A. Modify the date range on the report

  B. Include a time stamp on the report.

  C. Increase the frequency of report generation.

  D. Add a report run date to the report.

  Correct Answer: C

  The best reporting enhancement that the accounting department could implement to reduce the number of calls on current accounts is C. Increase the frequency of report generation. By increasing the frequency of report generation, the accounting department could provide the collections manager with more up-to-date information on the customers who are past due on their accounts. This would help to avoid calling customers who have made payments in the time since the last report was printed, and thus reduce the number of calls on current accounts. Increasing the frequency of report generation would also improve the accuracy and timeliness of the data, and enhance the efficiency and effectiveness of the collections process. Modifying the date range on the report, including a time stamp on the report, or adding a report run date to the report would not be sufficient to reduce the number of calls on current accounts. These enhancements would only provide information on when the report was generated or what period it covers, but they would not change the fact that the report could be outdated by the time it reaches the collections manager. Therefore, these enhancements would not solve the problem of calling customers who have already paid their accounts.

• Question 149:

  While reviewing survey data, an analyst notices respondents entered "Jan," "January," and "01" as responses for the month of January. Which of the following steps should be taken to ensure data consistency?

  A. Delete any of the responses that do not have "January" written out.

  B. Replace any of the responses that have "01".

  C. Filter on any of the responses that do not say "January" and update them to "January".

  D. Sort any of the responses that say "Jan" and update them to "01".

  Correct Answer: C

  Explanation: Filter on any of the responses that do not say "January" and update them to "January". This is because filtering and updating are data cleansing techniques that can be used to ensure data consistency, which means that the data is uniform and follows a standard format. By filtering on any of the responses that do not say "January" and updating them to "January", the analyst can make sure that all the responses for the month of January are written in the same way. The other steps are not appropriate for ensuring data consistency. Here is why:

  Deleting any of the responses that do not have "January" written out would result in data loss, which means that some information would be missing from the data set. This could affect the accuracy and reliability of the analysis. Replacing any of the responses that have "01" would not solve the problem of data inconsistency, because there would still be two different ways of writing the month of January: "Jan" and "January". This could cause confusion and errors in the analysis. Sorting any of the responses that say "Jan" and updating them to "01" would also not solve the problem of data inconsistency, because there would still be two different ways of writing the month of January: "01" and "January". This could also cause confusion and errors in the analysis.

• Question 150:

  What category of data stewardship work is focused on ensuring that the organization respects the wishes of data subjects?

  A. Data quality.

  B. Data privacy.

  C. Data security.

  D. Regulatory compliance.

  Correct Answer: B

  Data privacy defines who has access to data, while data protection provides tools and policies to actually restrict access to the data. Compliance regulations help ensure that user's privacy requests are carried out by companies, and

  companies are responsible to take measures to protect private user data.

  Why is data privacy important?

  When data that should be kept private gets in the wrong hands, bad things can happen. A data breach at a government agency can, for example, put top secret information in the hands of an enemy state. A breach at a corporation can put

  proprietary data in the hands of a competitor.