Which of the following makes data unreadable without a required key?
A.Anonymization
B.Role-based access control
C.EncryptionCorrect
D.Masking
Explanation
Encryption transforms data into ciphertext that cannot be read until it is decrypted with the correct key. Masking and anonymization hide or remove identifying values but do not depend on a key to reverse them, and role-based access control restricts who can reach the data rather than making the data itself unreadable.
An analyst is building a reporting deck. The deck must include tracking and visualizing metrics and row-level security. Which of the following actions should the analyst take after meeting the initial requirements?
A.Show a mock-up to the team.Correct
B.Explain the desired level of reporting detail.
C.Present an analysis of the data.
D.Find out the project due date.
Explanation
Once the initial requirements (the metrics to track and visualize and row-level security) are gathered, the next step is to build a mock-up or wireframe and show it to stakeholders so they can confirm the layout and content before full development. Explaining the level of detail and finding the due date are part of gathering requirements, which is already done, and presenting an analysis comes after the report is built.
A data analysis team needs to segment customers based on customer spending behavior. The team has one million rows of data like the information in the following sales order table:
| Customer_ID | Region | Amount_spent | Product_category | Quantity_of_items |
|---|---|---|---|---|
| 00123 | East | 200000 | Baby | 4 |
| 00124 | West | 300000 | Home | 6 |
| 00125 | South | 400000 | Garden | 7 |
| 00126 | North | 500000 | Furniture | 8 |
| 00127 | East | 600000 | Baby | 10 |
Which of the following techniques should the team use for this task?
A.Standardization
B.Concatenate
C.BinningCorrect
D.Appending
Explanation
Binning groups a continuous numeric variable such as Amount_spent into ranges (for example low, medium and high spenders), which directly produces customer segments by spending behavior. Standardization rescales values but does not group them, while concatenating and appending combine fields or data sets rather than segmenting records.
Which of the following pieces of information, if made public, results in a data privacy violation?
A.Gender
B.Driver’s licenseCorrect
C.Age
D.Employment status
Explanation
A driver's license number is a government-issued identifier that ties data to a specific person, so it is personally identifiable information and exposing it is a privacy violation. Gender, age and employment status are demographic attributes that on their own do not identify an individual.
A data analyst is analyzing the following data set:
| Transaction Date | Qty | Item | Item Price |
|---|---|---|---|
| 12/12/12 | 11 | USB Cords | 9.99 |
| 11/11/11 | 3 | Charging Block | 8.89 |
| 10/10/10 | 5 | Headphones | 50.15 |
Which of the following methods should the analyst use to determine the total cost for each transaction?
A.Parsing
B.Scaling
C.Compressing
D.DerivingCorrect
Explanation
The total cost is not in the data set, so the analyst derives a new field by calculating it from existing ones: Qty multiplied by Item Price. Parsing splits a value into parts, scaling changes the range of values, and compressing reduces storage size; none of them creates the needed total.
A data analyst needs to use one table's data to refine data selection from a second table. Which of the following is the most efficient way?
A.SubqueryCorrect
B.Aggregate
C.Union
D.Join
Explanation
A subquery uses the result of a query on one table as a filter for the selection from another table (for example WHERE id IN (SELECT ...)), which is exactly refining the selection with another table's data. A join combines columns from both tables into the result rather than only filtering, a union stacks rows from both tables, and an aggregate summarizes values.
Metadata is data about data: it describes where a data set came from, who owns it, how it was transformed and how it moved between systems. That record of origin and movement is data lineage, which the Data+ governance objectives list with documentation and versioning as data management practices. Transformations and syntax are part of the processing logic itself rather than descriptive information kept about the data.
Which of the following allows the transfer of isolated applications to multiple environments?
A.Virtualization
B.Version control
C.Continuous integration
D.ContainerizationCorrect
Explanation
Containerization packages an application with its libraries and dependencies into an isolated container that runs the same way on any host with a container runtime, so it moves easily between development, test and production. Virtualization isolates whole operating systems and is heavier to move, while version control and continuous integration manage code changes and builds rather than packaging isolated applications.
A data breach occurs at a company. Which of the following actions should be taken?
A.Make an announcement on social media so customers are aware as soon as possible.
B.Tell the company management team and then tell regulatory agencies.Correct
C.Keep the incident a secret until the issue is resolved.
D.Inform the entire IT sector, but ask for discretion.
Explanation
After a breach, the incident is escalated through the company's internal chain first, so management can activate the incident response plan, and then reported to the regulatory agencies that breach notification laws require. Announcing it on social media first skips the response plan and may release unverified details. Keeping it secret violates notification obligations, and telling the whole IT sector is neither required nor appropriate.
A data analyst is modeling a new data warehouse to analyze sales. One of the requirements is to analyze sales by region. Which of the following best describes the region table?
A.Fact
B.DimensionalCorrect
C.Bridge
D.Snowflake
Explanation
A region table holds descriptive attributes (region name, country, territory) that the sales facts are sliced by, so it is a dimension table in a star schema. The fact table holds the measurable sales transactions with keys to the dimensions. A bridge table resolves many-to-many relationships, and snowflake describes a schema design in which dimensions are normalized, not the role of a single table.
Which of the following data repositories stores unformatted data in its original, raw form?
A.Data warehouse
B.Data silo
C.Data mart
D.Data lakeCorrect
Explanation
A data lake stores structured, semi-structured and unstructured data in its original raw form, applying a schema only when the data is read. A data warehouse and a data mart hold cleaned, structured data modeled for analysis, with a data mart covering a single subject or department. A data silo is an isolated store that other teams cannot easily access, not a repository type defined by raw storage.
A data analyst must combine service calls into low-, medium-, and high-priority levels in order to analyze organizational responses. Which of the following techniques should the analyst use for this task?
A.Augmentation
B.Imputation
C.Scaling
D.BinningCorrect
Explanation
Binning groups continuous or many-valued data into a small number of categories, such as sorting service calls into low, medium and high priority. Imputation fills in missing values, scaling rescales numeric values to a common range, and augmentation adds new or derived data to a dataset. None of those creates categories from existing values.
Which of the following explains the purpose of UAT?
A.To begin the software application development process to enhance user experience
B.To ensure all parts of the software application work together after each sprint
C.To review software application crashes, create patches, and deploy to users
D.To validate and verify that a software application meets the needs and requirements of usersCorrect
Explanation
User acceptance testing (UAT) is the final testing phase in which real users validate and verify that the application meets their business needs and requirements before it goes live. Checking that components work together after each sprint is integration or regression testing. Reviewing crashes and deploying patches is maintenance, and UAT comes at the end of development, not the beginning.
A data analyst notices that a certain field that stores customer IDs in a defined format has incorrect values. Which of the following could help the analyst identify the issue?
A.Outliers
B.ValidationCorrect
C.Redundancy
D.Completeness
Explanation
Validation checks values against defined rules, such as a required pattern, length or character set for a customer ID, so it reveals entries that do not follow the defined format. Outliers are unusual numeric values, redundancy is duplicated data, and completeness concerns missing values; none of those checks whether a value matches its expected format.
Which of the following tools would a data analyst most likely use to modify a simple data connection property in a configuration file?
A.RStudio
B.SSMS
C.Notepad++Correct
D.Toad
Explanation
A configuration file is plain text (for example XML, JSON, INI or YAML), so a simple text editor such as Notepad++ is the most likely tool for changing a connection property in it. RStudio is an IDE for R, SSMS is for managing SQL Server databases, and Toad is a database management and development tool; none is needed to edit a text file.
After a database upgrade, a report using datetime calculations does not complete due to an arithmetic overflow error. Which of the following is the best way for a data analyst to troubleshoot the issue?
A.Changing the report filter
B.Reviewing error logs
C.Verifying the columns' data typesCorrect
D.Checking that the data has refreshed
Explanation
An arithmetic overflow error means a calculated value does not fit the data type that holds it, which often happens when an upgrade changes column types or defaults, for example a datetime difference that exceeds the range of an int. Verifying the columns' data types goes straight to that cause. Changing a filter only hides the symptom, checking the refresh does not explain a type error, and the error message already names the problem, so reviewing logs adds little.
A data analyst is preparing a report for external users. The analyst must ensure that visuals can be identified as belonging to the organization. Which of the following should the analyst add to the report to best meet this requirement?
A.Legal disclaimer
B.Infographic
C.Subtitle
D.WatermarkCorrect
Explanation
A watermark (such as the company logo or name placed on each visual) marks the visuals as belonging to the organization, even when they are copied out of the report. A legal disclaimer covers liability and usage terms, not visual ownership. An infographic is a type of visual, and a subtitle describes content rather than branding it.
Given the following data set:
| Value |
|---|
| 41 |
| 7 |
| 16 |
| 25 |
| 94 |
| 35 |
| 41 |
Which of the following is the mode?
A.35
B.37
C.41Correct
D.43
Explanation
The mode is the value that occurs most often in a data set. Only 41 appears twice; every other value appears once, so the mode is 41. The value 35 is the median of the sorted list (7, 16, 25, 35, 41, 41, 94), and about 37 is the mean, which are different measures of central tendency.
A data analyst is evaluating all conditions in a query. Which of the following is the best logical function to accomplish this task?
A.OR
B.NOT
C.ANDCorrect
D.IF
Explanation
AND returns true only when every condition is true, so it evaluates all of the conditions together. OR returns true when any single condition is met, NOT negates one condition, and IF branches on a single test rather than requiring all conditions.
A data analyst is helping a company achieve its strategic goals. Which of the following types of analytics should the analyst incorporate into the dashboards and tools delivered to the company?
A.PrescriptiveCorrect
B.Predictive
C.Diagnostic
D.Descriptive
Explanation
Prescriptive analytics recommends the actions to take to reach a desired outcome, which directly supports achieving strategic goals. Predictive analytics forecasts what is likely to happen but does not say what to do about it. Diagnostic analytics explains why something happened, and descriptive analytics summarizes what has already happened.
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