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WorksheetsBUDA quiz
Total questions: 104
Worksheet time: 26hrs 0mins
Cross-cutting decisions arise episodically
True
False
Decision support system is the information system that supports decision makers with identical system characteristics.
True
False
With more data and analysis technologies, more alternatives can be evaluated, forecasts can be improved, risk analysis can be performed quickly, and the views of experts can be collected quickly and at a reduced cost.
true
false
Setting the criteria for a choice comes in which stage of the Simon’s decision-making process?
Intelligence
Design
Choice
Implementation
Business intelligence (BI) can be characterized as a transformation of:
data to information to decisions to actions.
Big Data to data to information to decisions.
actions to decisions to feedback to information.
data to processing to information to actions.
What type of analytics answers questions like "what should I do?"
Descriptive
Predictive
Prescriptive
Business intelligence
Which of the following are the analytics accelerators in the analytic ecosystems? Select all that apply.
Data warehouse providers
Analytics-focused software developers
Academic institutions
Industry-specific application developers
An (a) problem such as new technology development has very few structured elements.
A (a) is a major component of a Business Intelligence (BI) system that holds source data.
An ultimate goal of today’s BI for organizations is to create value by acquiring and possessing piles of data and information in their systems
true
false
A business process can be monitored using data collected from the process’ activities in various functions of the organization.
true
false
In modern BI, augmented analytics enables businesses to share their data with users in low-code applications
true
false
It is essential to establish a proper infrastructure of managing data for BI development.
true
false
Knowledge derived from information in BI creates the true return in business when the knowledge is understood by professional analysts.
true
false
Which of the following is the tool for navigating data and providing a route of relevant data in a database for BI?
dashboard
data model
data pipeline
data mining
When an organization’s BI improves a customer satisfaction level, the organization obtains which of the following values?
financial value
productivity value
trust value
risk value
Which of the following professionals for a BI project performs the tasks related to integrating internal and external data with various programs?
data analyst
data warehousing specialist
application software developer
Application programming interface professional
Which of the following statements regarding data and information in BI are correct?
An objective score is chosen to establish a performance metric of business on an objective scale of success.
The value of the information created in BI is assessed higher when it is utilized for the intended purpose.
Knowledge is automatically generated from the processed data in BI processes.
BI with iterative processes helps organizations respond to dynamic shifts in business environments.
(a) can occur when overwhelmingly various and large data is available but needs to be processed in order to support decision-making.
BI is developed for the functionalities requested by all users in a project
true
false
What is the key challenge addressed in the 'Data Analysis' stage of BI development?
Designing the application
Quality of source data
Training the staff
Designing the infrastructure
What is the first step in the general approach for BI development?
justification
planning
business analysis
deployment
Which of the following types of infrastructure is evaluated during the 'Planning' stage?
Technical infrastructure only
Nontechnical infrastructure only
Both technical and nontechnical infrastructure
Neither technical nor nontechnical infrastructure
What is the role of 'Meta Data Repository Analysis' in BI development?
Storing historical data
Designing data mining algorithms
Deploying applications
Mapping technical meta data to business meta data
What should a BI development team do if a project is not yielding the expected benefits?
Continue with the original plan
Make changes as necessary to improve results
Ignore stakeholder concerns
Cancel the project
Data should be collected from various sources to improve the productivity in an organization’s analysis.
true
false
Unstructured data is easily readable and usable for analysis, preserving its original format.
true
false
What is the lowest level of abstraction in the data-to-knowledge continuum?
knowledge
data
information
wisdom
Which of the following describes structured data?
Data without a fixed format
Highly organized data with a well-defined schema
Data consisting of videos and images
Data collected from social media
What is an example of temporal data?
Customer demographic profiles
Satellite images
Stock market index
Social network relationships
What is the main purpose of a data warehouse?
Provide historical data for complex analysis
Store operational data for transactions
Manage real-time data processing
Host website content
Which type of attribute is used to measure customer satisfaction levels such as 'Dissatisfied' or 'Satisfied'?
Nominal
Ordinal
Interval
Ratio
Which of the following is an advantage of unstructured data?
Predictable schema design
Fixed format for efficient searches
Requires minimal preprocessing
Greater insights and easy collection
Data preprocessing is always simple, straightforward, and quick.
true
false
Missing values in a dataset must be measured again for analysis.
true
false
Listwise deletion does not lose any information from the collected data
true
false
Imputation results in correct analysis interpretation
true
false
The data has variables that are defined at the lowest level of details for the intended use to satisfy which of the following requirements?
Granularity
Richness
Validity
Uniqueness
Which of the following are the sources of dirty data in organization? Select all applied.
Irrelevant technologies
Lack of internal communication
Human error
Inadequate data strategies
Which of the following resources are impacted by dirty data? Select all applied.
Physical resources
Human resources
Intellectual resources
To reduce (a) in data, smoothing methods such as filtering and approximation can be applied.
Data transformation is a mandatory step to conduct an analysis for any business problem.
true
false
Normalizing data is a common step in the data consolidation process.
false
true
Discretized data provides more accurate analysis results than the original numerical
true
false
Feature extraction refers to the process of reducing the original data into a set of essential features.
true
false
Sampling is a way to reduce the number of features in a given data set.
true
false
Sampling can enable one to quickly obtain an analytical result.
true
false
Reducing a data set's volume can be a portion of which data preprocessing step?
Data Consolidation
Data Cleaning
Data Transformation
Data Reduction
Which of the following are the benefits from feature extraction? Select all that apply.
One can conduct an analysis with data from multiple data sources.
One can include essential features that are not available in the original data format.
One can avoid the impact of the proportions of skewed classes on model training.
One can build an analytical model without potential issues from the high dimensionality of data
(a) often relies on domain knowledge of experts to capture salient information in data.
Data are (a) between a certain minimum and maximum for all variables to mitigate the potential bias.
What is the primary objective of Business Intelligence (BI)?
A) To replace human decision-makers
B) To store and manage large amounts of data
C) To enable interactive access to data and support decision-making
D) To eliminate errors in organizational decisions
Which of the following is not a component of a Decision Support System (DSS)?
A) Data management subsystem
B) Model management subsystem
C) Expert system subsystem
D) User interface subsystem
In Simon’s decision-making process, which stage involves identifying and defining the problem?
choice
Intelligence
Implementation
design
Which of the following best describes analytics?
The process of analyzing past trends to make future decisions
The process of turning data into information for strategic decision-making
A set of methods used exclusively in financial sectors
D) A tool used for storing large amounts of organizational data
Which type of environment requires quick, frequent, and real-time decision-making support?
A) Simple and static business environments
B) Dynamic and complex business environments
C) Controlled and centralized business environments
D) Isolated and individual-driven business environments
What is the role of a data warehouse in Business Intelligence?
A) To provide tools for financial reporting
B) To store and process data that supports decision-making
C) To replace traditional databases with cloud solutions
D) To create automated decision-making algorithms
Which of the following types of analytics focuses on predicting future outcomes?
A) Descriptive analytics
B) Diagnostic analytics
C) Predictive analytics
D) Prescriptive analytics
What is the primary role of Business Intelligence (BI) in an organization?
A) Storing large amounts of data for future use
B) Turning data into actionable plans that drive business decisions
C) Replacing manual processes with automated systems
D) Enforcing company-wide technology policies
Which of the following is not a typical tool used in Business Intelligence?
A) Data model
B) Data pipeline
C) Performance metrics
D) Manual data entry system
What is the main goal of a data pipeline in a BI system?
A) To visualize data for easy interpretation
B) To automatically transport and transform data for storage or analysis
C) To manually extract and process data
D) To store data for future use without processing
Which of the following is an example of a Key Performance Indicator (KPI)?
A) The color of a company's website
B) The number of customer calls handled by each representative
C) The number of data pipelines in the BI system
D) The size of a company's office building
How does Business Intelligence (BI) create value for organizations?
A) By reducing data storage costs
B) By using data to improve business decisions and processes
C) By hiring more IT professionals
D) By eliminating the need for data management
What is the purpose of a dashboard in BI?
A) To process raw data into information
B) To visualize data in real-time for easy monitoring and decision-making
C) To store data for future analysis
D) To create data pipelines
What is "analysis paralysis" in the context of Business Intelligence?
A) A condition where there is too much data, causing delays in decision-making
B) The inability of BI tools to analyze data
C) The failure of data pipelines to process data
D) The situation when decision-makers act too quickly without sufficient data
What is the role of BI professionals such as BI engineers and BI analysts?
A) To maintain hardware infrastructure for the organization
B) To design, implement, and interpret data tools and insights for business decision-making
C) To develop marketing campaigns for the company
D) To handle customer service calls
Which of the following best describes a "data model"?
A) A tool for visualizing business performance
B) A graphical representation of data relationships in an information system
C) A performance metric used to measure business success
D) A physical storage unit for data in a warehouse
How does real-time analytics contribute to business success?
A) By allowing businesses to predict the future with 100% accuracy
B) By enabling organizations to respond quickly to emerging opportunities and risks
C) By replacing human decision-makers entirely
D) By storing large amounts of data in real-time
What is the first step in the BI development process according to the general engineering approach?
planning
justification
construction
business analysis
What is the primary focus during the "Planning" stage of BI development?
A) Evaluating the project's success
B) Determining the business need
C) Developing strategic and tactical plans for how the project will be accomplished
D) Building the BI application
Which of the following is a key challenge in the "Data Analysis" step of BI development?
A) Over-reliance on automated systems
B) Poor quality of source data
C) Limited access to advanced technologies
D) Lack of stakeholder involvement
What is the purpose of the "Application Prototyping" step in the BI development process?
A) To build the final BI application
B) To define the project’s scope
C) To test and refine concepts and ideas before full-scale development
D) To gather all necessary data
What is the ETL process in the context of BI development?
A) Extract, transform, and load data for storage and analysis
B) Evaluate, train, and lead teams in the development process
C) Estimate time and logistics for application deployment
D) Engage, track, and leverage data in real-time systems
During which stage of BI development is the database design created?
A) Justification
B) Business Analysis
C) Design
D) Construction
What happens during the "Implementation" step in the BI development process?
A) Planning for future projects
B) Rolling out databases and applications, and providing training
C) Developing the BI prototype
D) Analyzing user feedback for future releases
What is the primary focus of "Release Evaluation" in BI development?
A) Creating the BI architecture
B) Implementing new ETL processes
C) Learning from past project issues and making adjustments for future releases
D) Performing data mining on newly collected data
Which of the following is considered a key success metric in BI development?
A) The number of stakeholders involved
B) The accessibility of BI applications to the right users
C) The total cost of the BI tools
D) The speed of decision-making processes
Why is "business relevance" a critical expectation for BI development?
A) It ensures that the technology infrastructure is modern
B) It ensures that the BI tools are updated regularly
C) It aligns BI objectives with business performance, such as cost reduction or increased profits
D) It ensures that only technical users can access the BI tools
Which of the following best describes the nature of data?
A) A collection of processed information
B) A collection of facts
C) A collection of knowledge
D) A collection of insights
In the context of data types, which of the following is NOT a categorical attribute?
A) Nominal
B) Ordinal
C) Interval
According to W. H. Inmon, which of the following is NOT a characteristic of a data warehouse?
A) Subject-oriented
B) Integrated
C) Volatile
D) Time-variant
What is the primary difference between traditional databases and data warehouses in terms of workload?
Databases are analytical while data warehouses are operational
Databases focus on transaction processing while data warehouses focus on analytical processing
Data warehouses are more volatile than databases
Data warehouses provide real-time data while databases provide periodic updates
In a multidimensional schema for data warehouses, what is the relationship between fact tables and dimension tables?
Fact tables contain master data while dimension tables contain transactions
Fact tables contain aggregated transaction data while dimension tables contain attributes of dimensions
Fact tables and dimension tables are the same thing
Dimension tables are subsets of fact tables
What type of data consists of values that represent visual information?
Temporal data
Spatial data
Image data
Graph data
What is the main purpose of data preprocessing?
To make data collection faster
To prepare dirty, misaligned, or complex data for use
To reduce storage requirements
To create new data
Which of the following is not a major task in data preprocessing?
Data consolidation
Data cleaning
Data transformation
Data modeling
Which of the following is a characteristic of quality data?
Accuracy
Subjectivity
Incomplete
Lack of consistency
What is the primary goal of data consolidation?
A) Removing unnecessary data
B) Gathering and integrating data from multiple sources into a unified view
C) Detecting and handling missing values
D) Eliminating outliers from the data set
Which of the following describes "data inspection" in data preprocessing?
A) Developing algorithms to analyze raw data
B) Reviewing and assessing the quality of raw data before further analysis
C) Building data models to extract information from datasets
D) Performing statistical analysis on clean data
What does "subsetting data" involve?
A) Combining different datasets
B) Extracting portions of a dataset that are relevant to the analysis
C) Creating new variables based on existing data
D) Normalizing and aggregating data
Which of the following is a common issue encountered during data integration?
A) Data redundancy
B) Lack of metadata
C) Data normalization
D) Data aggregation
What is one of the key impacts of dirty data on organizations?
A) Increased confidence in decision-making
B) Decreased productivity due to time spent preparing data
C) Improved accuracy in reporting
D) Faster data processing
What is the first step in handling missing data?
A) Replacing missing data with averages
B) Understanding why the data is missing
C) Removing all records with missing data
D) Transforming the remaining data into a usable format
What is "imputation" in the context of handling missing data?
A) Deleting records with missing values
B) Replacing missing data with estimated values, such as the mean or mode
C) Combining datasets to remove missing values
D) Removing outliers from the dataset
Which of the following describes an outlier in a dataset?
A) A value that is duplicated across the dataset
B) A data point that significantly differs from other observations in the dataset
C) A data point with a missing value
D) A variable that is irrelevant to the analysis
What is the primary purpose of data transformation in data preprocessing?
A) To reduce the size of the data
B) To clean the data of missing values
C) To convert data into a format suitable for analysis
D) To remove duplicate records
What is the difference between Z-score normalization and min-max normalization?
A) Z-score normalization scales data between 0 and 1, while min-max does not
B) Z-score normalization adjusts data relative to the mean and standard deviation, while min-max normalization scales data between a specific range
C) Z-score normalization applies only to categorical data
D) Min-max normalization removes outliers while Z-score normalization does not
Which of the following is an example of data discretization?
A) Normalizing the data using Z-score normalization
B) Dividing a continuous range of values into fixed intervals
C) Converting categorical data into numerical data
D) Removing missing values from the dataset
What is the purpose of one-hot encoding in data preprocessing?
A) To remove duplicates from categorical data
B) To convert numerical data into categorical data
C) To assign binary values to each category of a categorical variable
D) To scale numerical data between a fixed range
What is the primary goal of dimensionality reduction?
A) To reduce the number of features while preserving meaningful information
B) To increase the number of features in the dataset
C) To improve data quality by removing noise
D) To convert categorical variables into numerical variables
Which of the following is a method of feature selection?
A) Z-score normalization
B) Min-max scaling
C) Wrapper methods
D) Data discretization
What is the purpose of data aggregation in data reduction?
A) To reduce the number of objects or attributes in the dataset
B) To convert categorical data into numerical data
C) To remove outliers from the dataset
D) To increase the number of data points for analysis
Which of the following is an advantage of using sampling in data reduction?
A) It guarantees perfect representation of the entire dataset
B) It allows for quicker and less costly analysis compared to processing the entire dataset
C) It removes all noise from the data
D) It always improves the accuracy of machine learning models
What is the purpose of balancing skewed data using oversampling and undersampling?
A) To increase the number of features in a dataset
B) To handle imbalanced class distributions in the data
C) To remove missing values from the dataset
D) To ensure that all data points are unique
