CompTIA Data+ (DA0-001) — All Questions
22 questions
A database is optimized for many small, fast insert and update operations from a business application, such as recording individual sales transactions. Which type of system is this?
- a.OLAP (online analytical processing)
- b.OLTP (online transaction processing)✓
- c.A flat CSV export
- d.A data visualization dashboard
OLTP systems are optimized for numerous short, fast transactions such as inserts and updates from operational applications. OLAP systems, by contrast, are optimized for complex analytical queries over large historical datasets, which is a different workload.
Which description best fits semi-structured data?
- a.Data stored strictly in fixed rows and columns of a relational table
- b.Raw video footage with no organizing information at all
- c.Numeric data that can never contain text
- d.Data such as JSON or XML that has tags or keys but no rigid table schema✓
Semi-structured data, such as JSON or XML, carries organizational markers like tags or keys but does not conform to the rigid rows and columns of a relational schema. Fully structured data lives in fixed tables, while unstructured data such as raw video lacks a predefined model.
An organization stores vast amounts of raw data in its native format, both structured and unstructured, to be processed later as needed. Which environment is this?
- a.A data lake✓
- b.A normalized OLTP database
- c.A single spreadsheet
- d.A dimension table
A data lake stores large volumes of raw data in its native format, deferring structure until the data is read and used. A normalized OLTP database enforces a strict schema up front, and a spreadsheet or single dimension table cannot hold the scale and variety described.
During data preparation, an analyst finds the same customer recorded three times with identical details. Which data-cleansing task removes these repeats?
- a.Imputation
- b.Normalization of numeric ranges
- c.Deduplication✓
- d.Aggregation
Deduplication removes duplicate records so each entity appears once, preventing inflated counts and skewed analysis. Imputation fills in missing values, normalization rescales numeric ranges, and aggregation summarizes groups; none of those address duplicate rows.
A dataset has a numeric column where about 3 percent of values are missing at random. The analyst replaces the missing values with the column's median. What is this technique called?
- a.Imputation✓
- b.Deduplication
- c.Parsing
- d.Encryption
Imputation fills in missing values using a strategy such as the mean, median, or a model-based estimate so that records remain usable. Deduplication removes repeats, parsing splits or extracts fields, and encryption protects confidentiality, none of which replace missing values.
An analyst needs to combine a customer table and an orders table so that each order row is enriched with the matching customer's name using a shared customer ID. Which operation accomplishes this?
- a.A pivot
- b.A histogram
- c.A moving average
- d.A join✓
A join combines rows from two tables based on a related key, such as customer ID, enriching each order with the matching customer details. A pivot reshapes data, a histogram visualizes a distribution, and a moving average smooths a time series; none merge tables on a key.
Before analysis, an analyst reviews a new dataset to summarize its structure, value ranges, null counts, and data types to assess its quality. What is this process called?
- a.Data visualization
- b.Data profiling✓
- c.Data encryption
- d.Data archiving
Data profiling examines a dataset's structure, distributions, ranges, null counts, and types to understand its content and quality before deeper work. Visualization presents findings, encryption protects data, and archiving stores it long-term; none of those characterize the data upfront.
A pipeline extracts data from source systems, transforms it into a consistent format, and then loads it into a data warehouse. Which term describes this sequence?
- a.OLAP
- b.RAID
- c.ETL✓
- d.DNS
ETL stands for extract, transform, load, the classic pattern of pulling data from sources, cleaning and reshaping it, then loading it into a warehouse. OLAP is an analytical query style, RAID is a storage-redundancy scheme, and DNS is a naming system, none of which describe this data pipeline.
A report summarizes what happened last quarter, showing total sales, average order value, and month-over-month change. Which type of analytics is this?
- a.Descriptive analytics✓
- b.Predictive analytics
- c.Prescriptive analytics
- d.Diagnostic analytics
Descriptive analytics summarizes what has already happened using measures such as totals and averages. Diagnostic analytics explains why it happened, predictive forecasts what will happen, and prescriptive recommends what action to take.
An analyst observes that ice cream sales and drowning incidents both rise in the same months, but concludes that neither causes the other. Which statistical caution does this illustrate?
- a.A larger sample always guarantees causation
- b.Correlation does not imply causation✓
- c.The mean is always equal to the median
- d.Outliers can never affect an average
Two variables can move together because both are influenced by a third factor, here warm weather, so correlation does not by itself prove that one causes the other. Establishing causation requires additional evidence such as controlled experiments.
A dataset of household incomes contains a few extremely high values that pull the average upward. Which measure of central tendency is least affected by these extreme values and better represents the typical household?
- a.The mean
- b.The range
- c.The sum
- d.The median✓
The median is the middle value and is resistant to extreme outliers, so it better represents a typical value in a skewed distribution. The mean is pulled toward extreme values, while the range and sum are not measures of central tendency.
In hypothesis testing, an analyst obtains a p-value of 0.02 with a significance level (alpha) set at 0.05. What is the appropriate conclusion?
- a.Accept the null hypothesis as definitely true
- b.The result is inconclusive and no decision can be made
- c.Reject the null hypothesis because the p-value is below alpha✓
- d.Increase alpha to 0.50 to be safe
When the p-value is less than the chosen significance level, the result is statistically significant and the null hypothesis is rejected in favor of the alternative. A p-value of 0.02 is below 0.05, so the analyst rejects the null; testing never proves the null definitively true.
Which statistic best describes how spread out a set of values is around their mean?
- a.Standard deviation✓
- b.Mode
- c.Count
- d.Median
Standard deviation measures the dispersion of values around the mean, with larger values indicating greater spread. The mode is the most frequent value, count is the number of observations, and the median is the middle value, none of which quantify spread.
An analyst wants to show the trend of monthly website visits over the past three years. Which chart type is most appropriate?
- a.A pie chart
- b.A line chart✓
- c.A single-value scorecard
- d.A word cloud
A line chart is ideal for showing how a value changes over a continuous time period, making trends and seasonality easy to read. A pie chart shows parts of a whole at one moment, a scorecard shows a single number, and a word cloud displays text frequency.
To examine the relationship between two continuous variables, such as advertising spend and revenue, which chart is most suitable?
- a.A pie chart
- b.A stacked bar of categories
- c.A single gauge
- d.A scatter plot✓
A scatter plot places each observation by its two continuous values, revealing correlation, clusters, and outliers between the variables. Pie charts, category bars, and gauges are not designed to show the relationship between two continuous measures.
An analyst wants to display the distribution of a single continuous variable by grouping values into ranges (bins) and showing how many fall in each. Which chart should be used?
- a.A histogram✓
- b.A pie chart
- c.A line chart of raw values
- d.A geographic map
A histogram groups a continuous variable into bins and shows the frequency in each, revealing the shape of the distribution such as skew or modality. A pie chart shows composition, a line chart shows trends, and a map shows geography, none of which display a distribution this way.
When designing an executive dashboard, which practice best supports clear communication?
- a.Use as many colors and 3-D effects as possible to look impressive
- b.Include every available metric on one crowded screen
- c.Highlight the key KPIs and choose chart types that match the data and message✓
- d.Remove all titles and axis labels to reduce clutter
Effective dashboards focus on the key performance indicators the audience needs and use chart types suited to the data and message, keeping the design clean and labeled. Excessive decoration, overcrowding, and removing labels all hinder understanding.
A regional sales manager wants to compare total sales across the 50 U.S. states at a glance, with color intensity showing higher versus lower values. Which visualization is most appropriate?
- a.A single line chart
- b.A choropleth (filled geographic map)✓
- c.A pie chart with 50 slices
- d.A one-row data table
A choropleth map shades geographic regions by value, making spatial patterns across states immediately visible. A pie chart with 50 slices would be unreadable, a single line chart shows trends over time, and a raw table does not convey spatial patterns at a glance.
Which data-quality dimension is concerned with whether all required values are present and no fields are unexpectedly empty?
- a.Timeliness
- b.Consistency
- c.Accuracy
- d.Completeness✓
Completeness measures whether all required data is present, with missing values reducing it. Accuracy concerns correctness, consistency concerns agreement across systems, and timeliness concerns whether data is current, each a distinct dimension of quality.
An organization designates one authoritative source for customer records so that every system references the same trusted definition of a customer. Which practice is this?
- a.Master data management (MDM)✓
- b.Data visualization
- c.Encryption in transit
- d.A moving average
Master data management establishes a single, authoritative source for core business entities such as customers or products, so all systems share a consistent, trusted definition. Visualization, encryption, and moving averages address other concerns entirely.
A dataset contains personally identifiable information (PII). Which control most directly limits who can view this sensitive data?
- a.Adding more chart colors
- b.Increasing the sample size
- c.Role-based access controls✓
- d.Converting the file to CSV
Role-based access controls restrict data access according to a user's role, ensuring only authorized people can view sensitive PII. Chart styling, sample size, and file format have no bearing on who is permitted to access the data.
Why is a data retention policy an important part of data governance?
- a.It guarantees that every chart uses the same color palette
- b.It defines how long data is kept and when it is securely disposed of✓
- c.It automatically increases query performance
- d.It replaces the need for data backups
A retention policy specifies how long different types of data are kept and when they must be securely destroyed, supporting compliance and reducing risk from holding data longer than necessary. It is unrelated to chart styling, query speed, or backups.