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NEW QUESTION # 145
An analyst is required to run a text analysis of data that is found in articles from a digital news outlet. Which of the following would be the BEST technique for the analyst to apply to acquire the data?
- A. Data wrangling
- B. Sampling
- C. Web scraping
- D. ETL
Answer: C
Explanation:
This is because web scraping is a technique that allows the analyst to extract data from web pages, such as articles from a digital news outlet. Web scraping can be done using various tools and methods, such as Python libraries, browser extensions, or online services. The other techniques are not suitable for acquiring data from web pages. Here is why:
Sampling is a technique that involves selecting a subset of data from a larger population, usually for statistical analysis or testing purposes. Sampling does not help the analyst to acquire data from web pages, but rather to reduce the amount of data to be analyzed.
Data wrangling is a technique that involves transforming and cleaning data to make it suitable for analysis or visualization. Data wrangling does not help the analyst to acquire data from web pages, but rather to improve the quality and usability of the data.
ETL stands for Extract, Transform, and Load, which is a process that involves moving data from one or more sources to a destination, such as a data warehouse or a database. ETL does not help the analyst to acquire data from web pages, but rather to store and organize the data.
NEW QUESTION # 146
An analyst needs to provide a chart to identify the composition between the categories of the survey response data set:
Which of the following charts would be BEST to use?
- A. Histogram
- B. Scatter pot
- C. Waterfall
- D. Line
- E. Pie
Answer: E
Explanation:
Explanation
The best chart to use to identify the composition between the categories of the survey response data set is a pie chart. A pie chart is a circular chart that shows the relative proportions of different categories in a whole. A pie chart is divided into slices that represent the percentage or frequency of each category. A pie chart is suitable for displaying categorical data that has a few categories and does not have any hierarchical or temporal relationship. In this case, a pie chart can show the composition of the favorite colors among the survey respondents, as well as the percentage of each color. The other options are not as good as a pie chart for this purpose, as they are more suitable for displaying numerical data that has some kind of distribution, trend, correlation, or comparison. A histogram is a bar chart that shows the frequency distribution of a single numerical variable. A line chart is a chart that shows the change of one or more numerical variables over time or another continuous variable. A scatter plot is a chart that shows the relationship between two numerical variables by plotting them as points on a Cartesian plane. A waterfall chart is a chart that shows how an initial value is increased or decreased by a series of intermediate values, resulting in a final value. Reference:
[Choosing the Right Chart Type - DataCamp]
NEW QUESTION # 147
A data analyst is creating a dashboard and trying to identify the type of information that should be included.
Which of the following should the analyst consider first?
- A. Access permissions
- B. Data sources and attributes
- C. Consumer types
- D. Data refresh rate
Answer: B
Explanation:
Explanation
The answer is D. Data sources and attributes.
Short explanation: The data analyst should consider the data sources and attributes first when creating a dashboard, because they determine what kind of information can be included and how it can be displayed. The data sources and attributes define the origin, quality, format, and structure of the data that will be used for the dashboard. They also affect the data refresh rate, the consumer types, and the access permissions of the dashboard12 A: Data refresh rate is not the first thing to consider, because it depends on the data sources and attributes. The data refresh rate is how often the data in the dashboard is updated or refreshed to reflect the latest changes. The data refresh rate can vary depending on the type, frequency, and availability of the data sources1 B: Consumer types are not the first thing to consider, because they depend on the data sources and attributes.
The consumer types are the intended audiences or users of the dashboard, who may have different needs, preferences, and expectations for the dashboard. The consumer types can influence the design, layout, and functionality of the dashboard. However, the consumer types cannot be determined without knowing what kind of data is available and relevant for them1 C: Access permissions are not the first thing to consider, because they depend on the data sources and attributes. The access permissions are the rules or policies that govern who can view, edit, or share the dashboard. The access permissions can protect the confidentiality, integrity, and availability of the data in the dashboard. However, the access permissions cannot be set without knowing what kind of data is involved and who needs to access it1
NEW QUESTION # 148
What test formatting option indicates that a field is required in an entity relationship diagram?
- A. Boldfacing.
- B. Capitalization.
- C. Italicization.
- D. Underlining.
Answer: A
NEW QUESTION # 149
When would you show time on a standard line chart?
- A. Y-axis
- B. Color
- C. Legend
- D. X-axis
Answer: D
NEW QUESTION # 150
You are working with a dataset and want to change the names of categories that you used for different types of books.
What term best describes this action?
- A. Aggregating.
- B. Recording.
- C. Summarizing
- D. Filtering.
Answer: B
Explanation:
The term that best describes the action of changing the names of categories that you used for different types of books is recoding. Recoding is a process of transforming or modifying the values of a variable or a category to make them more meaningful, consistent, or accurate. For example, you can recode the names of book genres from "Fiction", "Non-Fiction", "Biography", etc. to "FIC", "NF", "BIO", etc. to make them shorter and easier to use. Reference: Recoding Data - SPSS Tutorials - LibGuides at Kent State University
NEW QUESTION # 151
Encryption is a mechanism for protecting data.
When should encryption be applied to data?
Choose the best answer.
- A. When data is in transit.
- B. When data is at rest or in transit.
- C. When data is at rest.
- D. When data is at rest, unless you are using local storage.
Answer: B
Explanation:
Correct answer B. When data is at rest or in transit.
To provide maximum protection, encrypt data both in transit and at rest.
NEW QUESTION # 152
Emma is working in a data warehouse and finds a finance fact table links to an organization dimension, which in turn links to a currency dimension that not linked to the fact table.
What type of design pattern is the data warehouse using?
- A. Star.
- B. Snowflake.
- C. Sun.
- D. Comet.
Answer: B
Explanation:
Correct answer C. Snowflake.
Since the dimension links to a dimension that isn't connected to the fact table, it must be a Snowflake, with a Star, all dimensions link directly to the fact table, Sun and Comet are not data warehouse design patterns.
NEW QUESTION # 153
Which of the following can be used to translate data into another form so it can only be read by a user who has a key or a password?
- A. Data encryption.
- B. Data masking.
- C. Data transmission.
- D. Data protection.
Answer: A
Explanation:
Data encryption is a way of translating data from plaintext (unencrypted) to ciphertext (encrypted). Users can access encrypted data with an encryption key and decrypted data with a decryption key.
NEW QUESTION # 154
A financial institution is reporting on sales performance to a company at the account level. Due to the sensitive nature of the government the does il with, some account information is not shown. Which of the following fields should be masked?
- A. Product name
- B. Start date
- C. Customer name
- D. Sales volume
Answer: C
Explanation:
Explanation
Customer name is the field that should be masked, because it contains sensitive information that could identify the government accounts that the financial institution deals with. Masking is a technique that replaces or obscures sensitive data with dummy or random data, such as asterisks or hashes. Masking can help protect the privacy and security of the data, while still allowing for some analysis and reporting. Therefore, the correct answer is D. References: [Data Masking | Definition, Techniques & Examples - Talend], [Data masking - Wikipedia]
NEW QUESTION # 155
Which of the following is an example of a data-mining ETL tool?
- A. SPSS
- B. Cognos
- C. Stata
- D. SSIS
Answer: D
Explanation:
Explanation
A data-mining ETL tool is a software application that performs extract, transform, and load (ETL) operations on data for data mining purposes. Data mining is the process of discovering patterns, trends, and insights from large and complex data sets. ETL tools help to prepare the data for analysis by extracting data from various sources, transforming data into a consistent and suitable format, and loading data into a data warehouse or other destination. SSIS (SQL Server Integration Services) is an example of a data-mining ETL tool that is part of Microsoft SQL Server. SSIS provides graphical tools and wizards for building and debugging ETL packages that can work with various data sources and destinations. Therefore, the correct answer is A.
References: [Data Mining - SQL Server Integration Services (SSIS) | Microsoft Docs], [What Is Data Mining?
| Oracle]
NEW QUESTION # 156
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: A
NEW QUESTION # 157
Which of the following would be the best way to identify multicollinear attributes in a data set?
- A. Two-way ANOVA
- B. Correlation coefficient
- C. Two-sample f-test
- D. Chi-squared test
Answer: B
NEW QUESTION # 158
Alex wants to use data from his corporate sale, CRM, and shipping systems to try and predict future sales.
Which of the following systems is the most appropriate?
Choose the best answer.
- A. Data mart.
- B. Data Warehouse.
- C. OLAP.
- D. OLTP.
Answer: B
Explanation:
Correct answer: C. Data Warehouse.
Data warehouse bring together data from multiple systems used by an organization.
A data mart is too narrow, as Alex needs data from across multiple divisions.
OLAP is a broad term of analytical processing, and OLTP systems are transactional and not ideal for this task.
NEW QUESTION # 159
What colors are commonly used for the change bars in a waterfall chart?
- A. Blue and Yellow
- B. Red and Green
- C. Blue and Green
- D. Red and Yellow
Answer: B
NEW QUESTION # 160
Which of the following is a characteristic of a relational database?
- A. It uses minimal memory.
- B. It is structured in nature.
- C. It utilizes key-value pairs.
- D. It has undefined fields.
Answer: B
Explanation:
It is structured in nature. This is because a relational database is a type of database that organizes data into tables, which consist of rows and columns. A relational database is structured in nature, which means that the data has a predefined schema or format, and follows certain rules and constraints, such as primary keys, foreign keys, or referential integrity. A relational database can be used to store, query, and manipulate data using a structured query language (SQL). The other characteristics are not true for a relational database. Here is why:
It utilizes key-value pairs. This is not true for a relational database, because key-value pairs are a way of storing data that associates each value with a unique key, such as an identifier or a name. Key-value pairs are typically used in non-relational databases, such as NoSQL databases, which do not have tables, rows, or columns, but rather store data in various formats, such as documents, graphs, or columns.
It has undefined fields. This is not true for a relational database, because fields are another name for columns in a table, which define the attributes or properties of each row or record in the table. Fields have defined names, types, and lengths in a relational database, which specify the format and size of the data that can be stored in each field.
It uses minimal memory. This is not true for a relational database, because memory is the amount of space or storage that is used by a database to store and process data. Memory usage depends on various factors, such as the size, complexity, and number of tables and queries in a relational database. A relational database can use a lot of memory if it has many tables with many rows and columns, or if it performs complex or frequent queries on the data.
NEW QUESTION # 161
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. Optimize the dashboard.
- B. Update the dashboard subscribers.
- C. Change the field definitions.
- D. Deploy the dashboard to production.
Answer: A
Explanation:
Explanation
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
NEW QUESTION # 162
A data analyst has been asked to derive a new variable labeled "Promotion_flag" based on the total quantity sold by each salesperson. Given the table below:
Which of the following functions would the analyst consider appropriate to flag "Yes" for every salesperson who has a number above 1,000,000 in the Quantity_sold column?
- A. Date
- B. Logical
- C. Mathematical
- D. Aggregate
Answer: B
Explanation:
A logical function is a type of function that returns a value based on a condition or a set of conditions. For example, the IF function in Excel can be used to check if a certain condition is met, and then return one value if true, and another value if false. In this case, the data analyst can use a logical function to check if the Quantity_sold column is greater than 1,000,000, and then return "Yes" if true, and "No" if false. This would create a new variable called Promotion_flag that indicates whether the salesperson has sold more than 1,000,000 units or not. Reference: CompTIA Data+ Certification Exam Objectives, Logical functions (reference)
NEW QUESTION # 163
A data analyst is asked on the morning of April 9, 2020, to create a sales report that identifies sales year to date. The daily sales data is current through the end of the day. Which of the following date ranges should be on the report?
- A. January 1, 2020 to April 7, 2020
- B. January 1, 2020 to April 8, 2020
- C. January 1, 2020 to April 9, 2020
- D. January 1, 2020 to April 1, 2020
Answer: C
Explanation:
This is because sales year to date refers to the sales that have occurred from the beginning of the current year until the current date. By creating a sales report that identifies sales year to date, the analyst can measure and compare the sales performance and progress of the current year. Since the analyst is asked to create the sales report on the morning of April 9, 2020, and the daily sales data is current through the end of the day, the date range that should be on the report is January 1, 2020 to April 9, 2020. The other date ranges are not correct for identifying sales year to date. Here is why:
January 1, 2020 to April 1, 2020 would not include the sales that occurred in the first eight days of April, which would underestimate the sales year to date.
January 1, 2020 to April 7, 2020 would not include the sales that occurred in the last two days of April, which would also underestimate the sales year to date.
January 1, 2020 to April 8, 2020 would not include the sales that occurred on April 9, which would also underestimate the sales year to date.
NEW QUESTION # 164
A data analyst has been asked to create an ad-hoc sales report for the Chief Executive Officer (CEO).
Which of the following should be included in the report?
- A. YTD total sales.
- B. The customers' first and last names.
- C. Line-item SKU numbers.
- D. The sales representatives' home addresses.
Answer: A
Explanation:
The report for the CEO should include YTD total sales, as this will provide a high-level overview of the sales performance of the company and show how it is meeting its annual goals. The other options are not appropriate for the CEO, as they are either too detailed or irrelevant for the report. The sales representatives' home addresses, line-item SKU numbers, and customers' first and last names are not related to the sales performance and might compromise the privacy and security of the data. Reference: CompTIA Data+ (DA0-001) Practice Certification Exams | Udemy
NEW QUESTION # 165
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