ALA Data Analytics Practice Test

These questions are part of the practice quiz. Start practicing

• What are heat maps in data visualization, and how could they be used to analyze library space usage?
• What is a primary purpose of a data quality scorecard?
• What does data schema evolution mean, and how should a library manage changes over time without breaking analytics?
• Which of the following is an AI capability described?
• Which data model is typically favored for simpler, faster analytics queries due to fewer joins?
• Which statement best describes Tableau's drag-and-drop interface?
• Which of the following is NOT listed as a use of data analytics?
• When are nonparametric tests preferred over parametric tests in library data analysis?
• Which components are essential in a metadata ingestion process to support reliable analytics from multiple data sources such as an ILS, discovery layer, and web analytics?
• Which of the following is an example of data transformation focusing on standardization across data sets?
• Explain the concept of power in hypothesis testing and how it affects study design.
• What is heteroscedasticity, and how could it affect regression results in library analytics?
• Describe how to perform a simple linear regression with library usage as the dependent variable and time as the predictor, including interpretation of coefficients.
• In library analytics, when is dimensionality reduction like PCA particularly helpful?
• Which method is commonly used to detect data drift in a predictive model?
• Explain a common ETL challenge in library analytics and data integration.
• When reconciling usage data across systems, what is the role of deduplication?
• Which statement best describes how AI differs from traditional computing technologies?
• Which option describes the final step in the three-step data visualization process?
• What is a data model, and how does it differ from a data schema in analytics?
• Which is a standardization example in feature engineering for library usage data?
• What is a surrogate key, and why might you use it in data integration for library systems?
• What is a CTE (Common Table Expression), and how can it help in readable library analytics queries?
• Which of the following is a typical example of personally identifiable information (PII)?
• Which outcome is typically associated with data analysis for management?
• Which practice is NOT a standard feature of Tableau's data visualization tool?
• Which metrics would you use to evaluate a digital repository's discovery experience in a library?
• Descriptive, predictive, and prescriptive analytics with library examples. Which option best aligns?
• A SQL statement is used to ask a question or communicate a request of the BLANK management system.
• Which of the following describes a monotonic relationship between two variables?
• Which type of analytics is focused on forecasting future events and outcomes?
• The seasonality index by month is an example of which data science concept in library analytics?
• A data _____ uses the knowledge of processing software, business strategy, and analytical skills to deliver data and reports that guide management and executives.
• Which program is a popular data analytics tool that offers business intelligence and data visualization?
• Data analysts must blend facts and data with knowledge about the ___.
• Which of the following is a valid SQL keyword?
• Which of the following is a trend in data analytics?
• In a relational database, which term describes a single item of data stored in a table?
• Which of the following is an advantage of using SQL in relational database management systems?
• End-to-end traceability in data pipelines helps ensure what?
• What is multicollinearity, and why is it a concern in regression modeling for library data?
• Which analytics type would identify the root causes behind changes in resource usage patterns?
• Which product offers licenses for Creators, Explorers, and Viewers?
• What best describes a star schema in a library analytics data warehouse?
• What is the role of metadata and lineage in governance?
• In time series decomposition, which set of components is typically identified to analyze library usage data?
• Which of the following is a challenge associated with using Tableau?
• Explain data provenance and its importance for analytics outputs.
• RBAC and ABAC are examples of which security mechanism?
• Which statement best describes the role of color in data visualizations?
• What is a sample size calculation, and why is it important for experiments in library services?
• Entry-level data analysts frequently start with no prior BLANK, but go through extensive on-the-job training that teaches them how to apply information learned in college as well as training on organizational policies and procedures.
• When would you use a surrogate key in a library analytics data model?
• In the data project life cycle, which stage is the final one?
• Which practice improves accessibility of data visualizations and aligns with WCAG guidelines?
• How would you validate a new analytics model before deploying it to production in a library context?
• What is regularization in regression, and why might you apply it to analytics models?
• Explain ethical considerations when analyzing patron data and one strategy to mitigate privacy risks.
• If you want to measure the relationship between an ordinal satisfaction rating and the number of visits, which correlation measure is appropriate?
• List three common data quality issues in library analytics and one mitigation for each.
• Which of the following is a capability of AI as described?
• What are the main types of visuals that Power BI supports?
• If web interoperability and ease of harvesting are priorities, which schema is typically preferred?
• What is the fundamental difference between a data warehouse and a data mart, and when might you choose a data mart for library analytics?
• Which statement describes the purpose of metadata standards in library data exchange and name two common standards?
• In a database, a single row of data in a table is commonly referred to as a ___.
• Which approach helps stay within API rate limits when extracting data for analytics?
• What is COUNTER and why is it critical in library analytics for evaluating electronic resource usage?
• In Tableau, which of the following is NOT a role a user can assume?
• Which of the following is a typical responsibility of a data analyst?
• For data to be open data, what must databases provide?
• Explain the difference between regression and classification in predictive analytics with library data examples.
• In computer programming, a set of rules and guidelines that define a specific computer language is referred to as the language's ___.
• Which statement about data visualization is true?
• Which of the following is a commonly cited best practice for data visualizations?
• Providing the ability to explore and analyze data in seconds using a drag-and-drop interface and NLP describes which product that offers licenses for Creators, Explorers, and Viewers?
• In evaluating classifiers with imbalanced classes, which metric is often more informative than accuracy?
• Which step in the data visualization workflow emphasizes deciding what visuals to create before building them?
• In library analytics, what is the effect of normalization in a snowflake schema on data redundancy?
• When using color to compare temperature, which color best conveys cold?
• Which of the following is a data transformation example?
• Which SQL feature would you use to assign a rank to libraries by average weekly circulations within each city?
• PII stands for which term?
• Which program is typically limited to one user at a time?
• In a library analytics context, which statement best distinguishes data quality measurement for accuracy?
• Data lag is best described as what?
• Which scenario best illustrates the need for data normalization before aggregation?
• Explain loop-in and loop-out in data processing pipelines and their importance for data quality.
• What is a common data integration challenge associated with ETL in library analytics?
• How is timeliness defined in data delivery, and what are two strategies to improve it in a library analytics pipeline?
• What is the Microsoft analytics software that enables processing, manipulation, and visualization of data?
• Which of the following describes who specifies the collections referred to as fields in a database?
• What is a canonical data model?
• Define the difference between a realized metric and a leading indicator in library analytics.
• Describe a correct approach to implementing role-based access control (RBAC) for analytics dashboards in a library setting.
• Which metric is least relevant to a data quality scorecard?
• The data tools set includes spreadsheets, databases, query languages, and data BLANK tools. Which is the BLANK?
• Name and describe two common data security controls applicable to analytics environments.
• Which statement best describes the primary purpose of SQL?
• The 68-95-99.7 rule describes what in normal distributions?
• Which statement about the Python programming language is true?
• How would you assess and improve accessibility of data visualizations for diverse library stakeholders?
• Which statement best contrasts MARC with Dublin Core for metadata?
• When would you use a SQL window function in library analytics?
• Define bias and fairness in data analytics, and provide a library-specific example.
• Which statement about spreadsheets is true?
• What term describes assembling components from data sources and analytics platforms to create a more user-friendly analytics experience?
• Explain the difference between statistical significance and practical significance with an example from library analytics.
• Which of the following are uses of IoT analytics in business?
• Why would you integrate discovery-layer logs with ILS data for analytics?
• What is the purpose of data normalization in multi-source library analytics, and what is one practical approach?
• Which of the following is a typical question data analysts ask?
• Which of the following is NOT a Power BI tier?
• What is a ROC curve, and when might it be used in library analytics?
• Which option best represents a common challenge when using SQL databases?
• Which approach is a practical way to mitigate data skew in analytics?
• Measurable and counted data that can have almost any numeric value is called what data type?
• What is a key step to reconcile usage data from an ILS with COUNTER reports for accuracy?
• What best describes data drift in a predictive library model that predicts resource demand?
• What is data normalization, and why is it important before aggregation in analytics?
• Which of the following is a step in the six-step process used by analysts to create data-driven decision making?
• What is the effect of high multicollinearity on the interpretation of predictor effects in regression?
• Define the difference between a primary key and a foreign key in a library data warehouse schema.
• There are three main tools data analysts use to analyze data. They are spreadsheets, databases and query languages, and data BLANK tools.
• If you are displaying data as a percentage of a whole, which chart is typically best?
• Which role delivers data and reports that guide management and executives by applying knowledge of processing software, business strategy, and analytical skills?
• In the six-step process analysts use to create data-driven decisions, the step during which data cleansing occurs to ensure that high-quality data is ready for processing is the __ step.
• There are three main steps in the Harvard University's Data Science Ready Project life cycle; Which term is NOT listed as a step?
• What is the role of data governance in managing patron privacy and data access controls?
• Which of the following is NOT listed as a type of analytics in the data analytics process?
• Explain the concept of data lag and its impact on timely decision-making in library analytics.
• In a database, data is organized into complex and meaningful collections specified by the database administrator. These collections are referred to as BLANK.
• Which statement about open data is NOT true?
• What is the final step in the described three-step data visualization process (explore, plan, then ... )?
• SQL stands for ___ query language.
• What is the term for shortening the y-axis on a graph to exaggerate differences?
• Which of the following best describes the role of data analysts in organizations?
• Which statement best describes descriptive analytics?
• Describe how to perform a basic exploratory data analysis on a library usage dataset.
• Which of the following is a best practice for effective data visualizations?
• SQL is useful for querying data contained in a database.
• Selecting data that supports a desired conclusion is known as what?
• Which statement describes the purpose of data visualization in data analysis?
• What is a 95% confidence interval, and how would you interpret it for average weekly circulations?
• How would you design an A/B test to decide whether adding a library chat widget increases reference transaction counts?
• DDDM refers to Data Driven BLANK Making.
• Define overfitting and underfitting in the context of building predictive models for library usage.
• Which feature combines drag-and-drop capability with natural language processing for data exploration?
• Which set lists the four core components of data governance in library analytics?
• Explain the role of data visualization storytelling and how to structure an effective library analytics narrative.
• Which regularization technique penalizes the sum of absolute values of coefficients?
• Describe a scenario where dimensionality reduction (e.g., PCA) could be useful in library analytics.
• Collections of related fields in a database are referred to as ___.
• Data that is sold by an entity that did not actually collect the data is considered which type of data?
• Which statement correctly describes when to use Pearson correlation versus Spearman rank correlation?
• Which system is designed as a structured, curated repository optimized for reporting and analysis?
• Which term describes data that lacks a predefined structure?
• Which platform is known for licensing three roles: Creators, Explorers, and Viewers?
• The six-step process analysts use to create data-driven decision making includes which of the following steps?
• What is data lineage and why is it important in a library analytics data pipeline?
• What is feature engineering, and provide two examples relevant to library usage analytics.
• How would you interpret a sudden spike in digital resource downloads during a holiday period?
• Which of the following is NOT a trend in data analytics?
• Why is choosing the correct unit of analysis critical in analytics projects?
• What is the difference between a feature and a label in supervised learning?
• During metadata ingestion, what is the primary purpose of deduplication rules across multiple data sources?
• Which feature makes Tableau popular with data analysts?
• Which best describes a data quality scorecard in a library analytics context?
• What is data skew in a library analytics context?
• Which of the following is a common SQL term?
• What does the data dictionary's 'allowed values' refer to in the context of data element definitions?
• Describe a scenario where a snowflake schema is more appropriate than a star schema in library data modeling.
• Explain the difference between population and sample, and why sampling is often used in library data analysis.
• What is a unit of analysis, and why is selecting the correct unit important in analytics projects?
• The process of converting the format of data from one form to another is called data BLANK.
• In supervised learning, which data split is used to assess final model performance after training?
• At the start of their careers, data analysts are most likely to hold which level of education?
• What is a key benefit of integrating Python with Excel for data analysis?
• A major trend in data analytics is the use of artificial intelligence to focus on small data which is more precise, using small datasets that are capable of impacting decisions in the present. This is known as __ AI.
• Explain what a data dictionary is and why it is important in a library analytics project.
• Which statements about Power BI support for different users are true?
• Which item is a type of analytics included in the data analytics process?
• Define a time series decomposition and its relevance to library usage data.
• What is a box-and-whisker plot best used to illustrate in library analytics?
• Which of the following is NOT one of the competencies organizations invest in to support data-driven decision making (DDDM)?
• What is a p-value, and why is it important in evaluating hypothesis tests in analytics?
• Which of the following is NOT a benefit of IoT data analytics?
• A data mart is best described as which of the following, and when would you choose it for library analytics?
• What is the role of audit logs in an RBAC-enabled analytics environment?
• Which component best describes ensuring data across the organization is defined and managed consistently, including roles and responsibilities?
• Which attribute among the following is identified as part of analytical thinking in data analytics?
• Which statement about IoT data analytics is true?
• Which features make Tableau popular with data analysts?
• What are key considerations before sharing open data externally?
• When visualizing the relationship between two numerical variables, which chart is commonly used?
• In SQL, which form of comment is recognized as a line comment that SQL ignores?
• What is a hypothesis in analytics?
• A chi-square test is used to examine what in library analytics?
• Which of the following is listed as a healthcare-related use of data analytics?
• Which data quality dimension addresses whether data accurately reflect real-world entities, and how might you measure it for MARC records?
• What term describes the IT architecture and infrastructure used for the collection, storage, analysis, and interpretation of meaningful data?
• Which description best captures the focus of predictive analytics?
• Which items are typically considered examples of PII?
• Tableau licenses are categorized into which roles?
• What is a baseline model, and why is it useful in evaluating new analytics approaches in libraries?
• What is a discovery layer in library systems, and how does it affect analytics?
• In library analytics, which task is best framed as a regression problem?
• The graphical and structured representation of data is known as what?
• What are API rate limits, and how can they impact data extraction for analytics?
• Compare SQL vs a scripting language like Python for data transformation in analytics projects.
• How would you implement data retention policies for patron data in a library organization?
• When designing data visualizations, how should you tailor for a senior library administrator versus frontline staff?
• Which statement reflects IoT data analytics' role in proactive decision making?
• Which of the following is NOT one of the three major data format varieties?
• In relational databases, which term describes a single item of data stored with a record?
• Which of the following are best practices for data visualizations in library dashboards?
• What is data lineage, and how does it support reproducibility in library analytics projects?
• Curiosity, understanding context, having a technical mindset, data design, and data strategy are among the five essential aspects of which kind of thinking and skills?
• Which statement best describes a data lake in analytics use cases?
• What happens to PII when data is anonymized?
• Which statement correctly identifies three ethical pitfalls when releasing library analytics dashboards to the public and a typical mitigation?
• Which of the following describes data transformation's role?
• To be considered open data, databases must provide access rights so that they can be redistributed.
• The process of converting the format of data from one form to another is called data BLANK.
• What is a data warehouse, and how does it differ from a data lake in terms of analytics use cases?