DA-100 Power BI Exam Questions &
Answers (Grade A+)
Skills Measured -
correct answer ✅Prepare the Data (20-25%)
Model the Data (20-30%)
Visualize the Data (20-25%)
Analyze the Data (10-15%)
Deploy and Maintain Deliverables (10-15%)
Core components of analytics -
correct answer ✅Descriptive
Diagnostic
Predictive
Prescriptive
Cognitive
Descriptive Analytics -
correct answer ✅Help answer questions about what has
happened based on historical data. Descriptive analytics techniques
summarize large datasets to describe outcomes to stakeholders.
By developing key performance indicators (KPIs), these strategies
can help track the success or failure of key objectives. Metrics such
,DA-100 Power BI Exam Questions &
Answers (Grade A+)
as return on investment (ROI) are used in many industries, and
specialized metrics are developed to track performance in specific
industries.
An example of descriptive analytics is generating reports to provide
a view of an organization's sales and financial data.
Diagnostic Analytics -
correct answer ✅help answer questions about why events
happened. Diagnostic analytics techniques supplement basic
descriptive analytics, and they use the findings from descriptive
analytics to discover the cause of these events. Then, performance
indicators are further investigated to discover why these events
improved or became worse.
Generally, this process occurs in three steps:
1. Identify anomalies in the data. These anomalies might be
unexpected changes in a metric or a particular market.
2. Collect data that's related to these anomalies.
3. Use statistical techniques to discover relationships and trends
that explain these anomalies.
,DA-100 Power BI Exam Questions &
Answers (Grade A+)
Predictive Analytics -
correct answer ✅help answer questions about what will happen in
the future. Predictive analytics techniques use historical data to
identify trends and determine if they're likely to recur. Predictive
analytical tools provide valuable insight into what might happen in
the future.
Techniques include a variety of statistical and machine learning
techniques such as neural networks, decision trees, and regression.
Cognitive Analytics -
correct answer ✅attempt to draw inferences from existing data
and patterns, derive conclusions based on existing knowledge
bases, and then add these findings back into the knowledge base
for future inferences, a self-learning feedback loop. Cognitive
analytics help you learn what might happen if circumstances
change and determine how you might handle these situations.
Inferences aren't structured queries based on a rules database;
rather, they're unstructured hypotheses that are gathered from
several sources and expressed with varying degrees of confidence.
Effective cognitive analytics depend on machine learning
algorithms, and will use several natural language processing
, DA-100 Power BI Exam Questions &
Answers (Grade A+)
concepts to make sense of previously untapped data sources, such
as call center conversation logs and product reviews.
Business Analyst -
correct answer ✅While some similarities exist between a data
analyst and business analyst, the key differentiator between the
two roles is what they do with data. A business analyst is closer to
the business and is a specialist in interpreting the data that comes
from the visualization. Often, the roles of data analyst and business
analyst could be the responsibility of a single person.
Data Analyst -
correct answer ✅(Prepare, Model, Visualize, Analyze, Manage)
enables businesses to maximize the value of their data assets
through visualization and reporting tools such as Microsoft Power
BI. Data analysts are responsible for profiling, cleaning, and
transforming data. Their responsibilities also include designing and
building scalable and effective data models, and enabling and
implementing the advanced analytics capabilities into reports for
analysis. A data analyst works with the pertinent stakeholders to
identify appropriate and necessary data and reporting
requirements, and then they are tasked with turning raw data into
relevant and meaningful insights.
Answers (Grade A+)
Skills Measured -
correct answer ✅Prepare the Data (20-25%)
Model the Data (20-30%)
Visualize the Data (20-25%)
Analyze the Data (10-15%)
Deploy and Maintain Deliverables (10-15%)
Core components of analytics -
correct answer ✅Descriptive
Diagnostic
Predictive
Prescriptive
Cognitive
Descriptive Analytics -
correct answer ✅Help answer questions about what has
happened based on historical data. Descriptive analytics techniques
summarize large datasets to describe outcomes to stakeholders.
By developing key performance indicators (KPIs), these strategies
can help track the success or failure of key objectives. Metrics such
,DA-100 Power BI Exam Questions &
Answers (Grade A+)
as return on investment (ROI) are used in many industries, and
specialized metrics are developed to track performance in specific
industries.
An example of descriptive analytics is generating reports to provide
a view of an organization's sales and financial data.
Diagnostic Analytics -
correct answer ✅help answer questions about why events
happened. Diagnostic analytics techniques supplement basic
descriptive analytics, and they use the findings from descriptive
analytics to discover the cause of these events. Then, performance
indicators are further investigated to discover why these events
improved or became worse.
Generally, this process occurs in three steps:
1. Identify anomalies in the data. These anomalies might be
unexpected changes in a metric or a particular market.
2. Collect data that's related to these anomalies.
3. Use statistical techniques to discover relationships and trends
that explain these anomalies.
,DA-100 Power BI Exam Questions &
Answers (Grade A+)
Predictive Analytics -
correct answer ✅help answer questions about what will happen in
the future. Predictive analytics techniques use historical data to
identify trends and determine if they're likely to recur. Predictive
analytical tools provide valuable insight into what might happen in
the future.
Techniques include a variety of statistical and machine learning
techniques such as neural networks, decision trees, and regression.
Cognitive Analytics -
correct answer ✅attempt to draw inferences from existing data
and patterns, derive conclusions based on existing knowledge
bases, and then add these findings back into the knowledge base
for future inferences, a self-learning feedback loop. Cognitive
analytics help you learn what might happen if circumstances
change and determine how you might handle these situations.
Inferences aren't structured queries based on a rules database;
rather, they're unstructured hypotheses that are gathered from
several sources and expressed with varying degrees of confidence.
Effective cognitive analytics depend on machine learning
algorithms, and will use several natural language processing
, DA-100 Power BI Exam Questions &
Answers (Grade A+)
concepts to make sense of previously untapped data sources, such
as call center conversation logs and product reviews.
Business Analyst -
correct answer ✅While some similarities exist between a data
analyst and business analyst, the key differentiator between the
two roles is what they do with data. A business analyst is closer to
the business and is a specialist in interpreting the data that comes
from the visualization. Often, the roles of data analyst and business
analyst could be the responsibility of a single person.
Data Analyst -
correct answer ✅(Prepare, Model, Visualize, Analyze, Manage)
enables businesses to maximize the value of their data assets
through visualization and reporting tools such as Microsoft Power
BI. Data analysts are responsible for profiling, cleaning, and
transforming data. Their responsibilities also include designing and
building scalable and effective data models, and enabling and
implementing the advanced analytics capabilities into reports for
analysis. A data analyst works with the pertinent stakeholders to
identify appropriate and necessary data and reporting
requirements, and then they are tasked with turning raw data into
relevant and meaningful insights.
