SE
Power
R
U
N
BI DA-100
L
EA
ID
,What are the divisions of the core components of analytics? - ANSTo analyze data, core
components of analytics are divided into the following categories:
-Descriptive
-Diagnostic
-Predictive
-Prescriptive
-Cognitive
What are descriptive analytics? - ANSDescriptive analytics help answer questions about
what has happened based on historical data. Descriptive analytics techniques summarize large
datasets to describe outcomes to stakeholders.
SE
What are examples of descriptive analytics? - ANSAn example of descriptive analytics is
generating reports to provide a view of an organization's sales and financial data.
What are diagnostic analytics? - ANSDiagnostic analytics help answer questions about why
R
events happened. Diagnostic analytics techniques supplement basic descriptive analytics, and
they use the findings from descriptive analytics to discover the cause of these events.
U
What are the steps of diagnostic analytics? - ANSPerformance indicators are further
investigated to discover why these events improved or became worse. Generally, this process
occurs in three steps:
N
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.
L
3. Use statistical techniques to discover relationships and trends that explain these anomalies.
EA
What are predictive analytics? - ANSPredictive analytics 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.
What techniques does predictive analytics use? - ANSTechniques include a variety of
statistical and machine learning techniques such as neural networks, decision trees, and
ID
regression.
What are prescriptive analytics? - ANSPrescriptive analytics help answer questions about
which actions should be taken to achieve a goal or target. By using insights from predictive
analytics, organizations can make data-driven decisions. This technique allows businesses to
make informed decisions in the face of uncertainty.
What tools does prescriptive analytics rely on? - ANSPrescriptive analytics techniques rely
on machine learning strategies to find patterns in large datasets.
, What are cognitive analytics? - ANSCognitive analytics 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.
How are inferences structured for cognitive analytics? - ANSInferences 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 concepts to make sense of previously untapped data sources, such as call center
SE
conversation logs and product reviews.
What are the different data roles? - ANS-Business analyst
-Data analyst
-Data engineer
R
-Data scientist
-Database administrator
U
What is the role of the business analyst? - ANSWhile 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
N
comes from the visualization.
What is the role of the data analyst? - ANSA data analyst enables businesses to maximize
the value of their data assets through visualization and reporting tools such as Microsoft Power
L
BI. Data analysts are responsible for profiling, cleaning, and transforming data. Their
responsibilities also include designing and building scalable and effective data models, and
EA
enabling and implementing the advanced analytics capabilities into reports for analysis.
What are the responsibilities of the data analyst with respect to Power BI - ANSA data
analyst is also responsible for the management of Power BI assets, including reports,
dashboards, workspaces, and the underlying datasets that are used in the reports. They are
tasked with implementing and configuring proper security procedures, in conjunction with
ID
stakeholder requirements, to ensure the safekeeping of all Power BI assets and their data.
How do data analyst interreact with the data engineer and database administrator? -
ANSData analysts work with data engineers to determine and locate appropriate data sources
that meet stakeholder requirements. Additionally, data analysts work with the data engineer and
database administrator to ensure that the analyst has proper access to the needed data
sources. The data analyst also works with the data engineer to identify new processes or
improve existing processes for collecting data for analysis.
Power
R
U
N
BI DA-100
L
EA
ID
,What are the divisions of the core components of analytics? - ANSTo analyze data, core
components of analytics are divided into the following categories:
-Descriptive
-Diagnostic
-Predictive
-Prescriptive
-Cognitive
What are descriptive analytics? - ANSDescriptive analytics help answer questions about
what has happened based on historical data. Descriptive analytics techniques summarize large
datasets to describe outcomes to stakeholders.
SE
What are examples of descriptive analytics? - ANSAn example of descriptive analytics is
generating reports to provide a view of an organization's sales and financial data.
What are diagnostic analytics? - ANSDiagnostic analytics help answer questions about why
R
events happened. Diagnostic analytics techniques supplement basic descriptive analytics, and
they use the findings from descriptive analytics to discover the cause of these events.
U
What are the steps of diagnostic analytics? - ANSPerformance indicators are further
investigated to discover why these events improved or became worse. Generally, this process
occurs in three steps:
N
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.
L
3. Use statistical techniques to discover relationships and trends that explain these anomalies.
EA
What are predictive analytics? - ANSPredictive analytics 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.
What techniques does predictive analytics use? - ANSTechniques include a variety of
statistical and machine learning techniques such as neural networks, decision trees, and
ID
regression.
What are prescriptive analytics? - ANSPrescriptive analytics help answer questions about
which actions should be taken to achieve a goal or target. By using insights from predictive
analytics, organizations can make data-driven decisions. This technique allows businesses to
make informed decisions in the face of uncertainty.
What tools does prescriptive analytics rely on? - ANSPrescriptive analytics techniques rely
on machine learning strategies to find patterns in large datasets.
, What are cognitive analytics? - ANSCognitive analytics 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.
How are inferences structured for cognitive analytics? - ANSInferences 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 concepts to make sense of previously untapped data sources, such as call center
SE
conversation logs and product reviews.
What are the different data roles? - ANS-Business analyst
-Data analyst
-Data engineer
R
-Data scientist
-Database administrator
U
What is the role of the business analyst? - ANSWhile 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
N
comes from the visualization.
What is the role of the data analyst? - ANSA data analyst enables businesses to maximize
the value of their data assets through visualization and reporting tools such as Microsoft Power
L
BI. Data analysts are responsible for profiling, cleaning, and transforming data. Their
responsibilities also include designing and building scalable and effective data models, and
EA
enabling and implementing the advanced analytics capabilities into reports for analysis.
What are the responsibilities of the data analyst with respect to Power BI - ANSA data
analyst is also responsible for the management of Power BI assets, including reports,
dashboards, workspaces, and the underlying datasets that are used in the reports. They are
tasked with implementing and configuring proper security procedures, in conjunction with
ID
stakeholder requirements, to ensure the safekeeping of all Power BI assets and their data.
How do data analyst interreact with the data engineer and database administrator? -
ANSData analysts work with data engineers to determine and locate appropriate data sources
that meet stakeholder requirements. Additionally, data analysts work with the data engineer and
database administrator to ensure that the analyst has proper access to the needed data
sources. The data analyst also works with the data engineer to identify new processes or
improve existing processes for collecting data for analysis.
