DUMPS
BASE
EXAM DUMPS
QLIKVIEW
QSBA2024
28% OFF Automatically For You
Qlik Sense Business Analyst Certification Exam -
2024
,1.Two customers in an organization want to use an app that contains a finance data
set. With different analysis objectives, each customer will only use a subset of that
data.
Which procedure should the business analyst follow?
A. Apply Section Access to manage the data for each customer
B. Create multiple visualizations using set analysis
C. Duplicate and rename the apps for each customer
D. Unpivot, then re-associate the data tables for each customer
Answer: B
Explanation:
In Qlik Sense, Set Analysis is one of the most powerful tools available to a Business
Analyst for managing different subsets of data within the same app. Since both
customers are working with the same finance dataset but have different objectives,
t
en
creating multiple visualizations using set analysis allows the analyst to tailor the data
m
ve
views for each customer without duplicating the app or creating complex data models.
ie
ch
Key Concepts:
A
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ou
Set Analysis: This feature enables the creation of expressions that define subsets of
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ce
data, allowing you to filter data within specific visualizations. This is ideal when
an
nh
multiple users need different insights from the same underlying dataset.
-E
Flexibility: Using set analysis, you can specify conditions within individual
ns
io
visualizations so that each user can focus on their own segment of the data without
st
ue
impacting others.
Q
m
Efficiency: This method avoids redundancy by ensuring you only need one app and
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lE
one data model, instead of duplicating and maintaining multiple apps or applying
ea
R
complex logic such as Section Access.
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it
w
Why the Other Options Are Less Suitable:
)
02
A. Apply Section Access: While Section Access is useful for managing security and
8.
(V
limiting what users can see in the entire dataset, it is primarily designed to restrict
ps
um
data access based on user roles. In this case, both users need access to the same
D
24
dataset but will conduct different analyses. Section Access would be an overly
20
A
restrictive and complex solution for this scenario.
B
S
Q
C. Duplicate and rename the apps: This is inefficient because it leads to redundancy
lik
Q
and makes maintenance harder (e.g., any changes to the dataset or visualizations
would need to be applied to both apps). It also increases the risk of inconsistencies
across versions of the app.
D. Unpivot and re-associate the data tables: This option is not relevant to the
problem, as unpivoting is more appropriate for transforming datasets rather than
tailoring views for different users within
the same app. It does not address the need for customer-specific analysis objectives.
References for Qlik Sense Business Analyst:
Set Analysis: In the Qlik Sense Business Analyst's toolkit, Set Analysis is covered as
a method to manage diverse data subsets within single apps, providing the flexibility
needed in multi-user environments without duplicating content.
, Efficient Application Design: Best practices suggest maintaining a single app where
possible to ensure consistency and ease of maintenance, which aligns with the
approach of using Set Analysis.
By using Set Analysis, you provide both customers with tailored data views that are
easily managed and updated within a single app. This is why option B is the most
effective and verified solution.
2.An app needs to load a few hundred rows of data from a .csv text file. The file is the
result of a concatenated data dump by multiple divisions across several countries.
These divisions use different internal systems and processes, which causes country
names to appear differently. For example, the United States of America appears in
several places as 'USA', 'U.S.A.', or 'US'.
t
en
For the country dimension to work properly in the app, the naming of countries must
m
ve
be standardized in the data model.
ie
ch
Which action should the business analyst complete to address this issue?
A
r
ou
A. Create a calculated master dimension expression
Y
ce
B. Load a lookup table to convert values
an
nh
C. Cleanse the source text file prior to loading -E
D. Use the Replace option in Data manager
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io
Answer: B
st
ue
Explanation:
Q
m
In Qlik Sense, when dealing with inconsistent naming conventions across different
xa
lE
systems or divisions (like the variation in country names), the best practice is to
ea
R
standardize the data during the loading process. Using a lookup table is the most
h
it
w
efficient approach to achieve this. This involves loading a separate table that contains
)
02
all variations of a country name along with the standardized version. During the load
8.
(V
process, Qlik Sense can then map the varying names to a common value. Key
ps
um
Concepts:
D
24
Lookup Table: A lookup table contains key-value pairs where different versions of a
20
A
data element (like country names) are mapped to a single standard value. In this
B
S
Q
case, the lookup table could have entries like USA, U.S.A., US all mapped to United
lik
Q
States of America.
Data Standardization: This is crucial in ensuring consistent analysis across datasets.
By converting variations of country names into a single consistent value, the business
analyst ensures that all data visualizations and analysis will treat "USA", "US", etc., as
the same entity.
Why the Other Options Are Less Suitable:
A. Create a calculated master dimension expression: While this could theoretically
work by creating a calculated expression to handle variations, it's not scalable or
maintainable, especially as new variations in country names could appear in future
data loads.
C. Cleanse the source text file prior to loading: This option would require modifying
BASE
EXAM DUMPS
QLIKVIEW
QSBA2024
28% OFF Automatically For You
Qlik Sense Business Analyst Certification Exam -
2024
,1.Two customers in an organization want to use an app that contains a finance data
set. With different analysis objectives, each customer will only use a subset of that
data.
Which procedure should the business analyst follow?
A. Apply Section Access to manage the data for each customer
B. Create multiple visualizations using set analysis
C. Duplicate and rename the apps for each customer
D. Unpivot, then re-associate the data tables for each customer
Answer: B
Explanation:
In Qlik Sense, Set Analysis is one of the most powerful tools available to a Business
Analyst for managing different subsets of data within the same app. Since both
customers are working with the same finance dataset but have different objectives,
t
en
creating multiple visualizations using set analysis allows the analyst to tailor the data
m
ve
views for each customer without duplicating the app or creating complex data models.
ie
ch
Key Concepts:
A
r
ou
Set Analysis: This feature enables the creation of expressions that define subsets of
Y
ce
data, allowing you to filter data within specific visualizations. This is ideal when
an
nh
multiple users need different insights from the same underlying dataset.
-E
Flexibility: Using set analysis, you can specify conditions within individual
ns
io
visualizations so that each user can focus on their own segment of the data without
st
ue
impacting others.
Q
m
Efficiency: This method avoids redundancy by ensuring you only need one app and
xa
lE
one data model, instead of duplicating and maintaining multiple apps or applying
ea
R
complex logic such as Section Access.
h
it
w
Why the Other Options Are Less Suitable:
)
02
A. Apply Section Access: While Section Access is useful for managing security and
8.
(V
limiting what users can see in the entire dataset, it is primarily designed to restrict
ps
um
data access based on user roles. In this case, both users need access to the same
D
24
dataset but will conduct different analyses. Section Access would be an overly
20
A
restrictive and complex solution for this scenario.
B
S
Q
C. Duplicate and rename the apps: This is inefficient because it leads to redundancy
lik
Q
and makes maintenance harder (e.g., any changes to the dataset or visualizations
would need to be applied to both apps). It also increases the risk of inconsistencies
across versions of the app.
D. Unpivot and re-associate the data tables: This option is not relevant to the
problem, as unpivoting is more appropriate for transforming datasets rather than
tailoring views for different users within
the same app. It does not address the need for customer-specific analysis objectives.
References for Qlik Sense Business Analyst:
Set Analysis: In the Qlik Sense Business Analyst's toolkit, Set Analysis is covered as
a method to manage diverse data subsets within single apps, providing the flexibility
needed in multi-user environments without duplicating content.
, Efficient Application Design: Best practices suggest maintaining a single app where
possible to ensure consistency and ease of maintenance, which aligns with the
approach of using Set Analysis.
By using Set Analysis, you provide both customers with tailored data views that are
easily managed and updated within a single app. This is why option B is the most
effective and verified solution.
2.An app needs to load a few hundred rows of data from a .csv text file. The file is the
result of a concatenated data dump by multiple divisions across several countries.
These divisions use different internal systems and processes, which causes country
names to appear differently. For example, the United States of America appears in
several places as 'USA', 'U.S.A.', or 'US'.
t
en
For the country dimension to work properly in the app, the naming of countries must
m
ve
be standardized in the data model.
ie
ch
Which action should the business analyst complete to address this issue?
A
r
ou
A. Create a calculated master dimension expression
Y
ce
B. Load a lookup table to convert values
an
nh
C. Cleanse the source text file prior to loading -E
D. Use the Replace option in Data manager
ns
io
Answer: B
st
ue
Explanation:
Q
m
In Qlik Sense, when dealing with inconsistent naming conventions across different
xa
lE
systems or divisions (like the variation in country names), the best practice is to
ea
R
standardize the data during the loading process. Using a lookup table is the most
h
it
w
efficient approach to achieve this. This involves loading a separate table that contains
)
02
all variations of a country name along with the standardized version. During the load
8.
(V
process, Qlik Sense can then map the varying names to a common value. Key
ps
um
Concepts:
D
24
Lookup Table: A lookup table contains key-value pairs where different versions of a
20
A
data element (like country names) are mapped to a single standard value. In this
B
S
Q
case, the lookup table could have entries like USA, U.S.A., US all mapped to United
lik
Q
States of America.
Data Standardization: This is crucial in ensuring consistent analysis across datasets.
By converting variations of country names into a single consistent value, the business
analyst ensures that all data visualizations and analysis will treat "USA", "US", etc., as
the same entity.
Why the Other Options Are Less Suitable:
A. Create a calculated master dimension expression: While this could theoretically
work by creating a calculated expression to handle variations, it's not scalable or
maintainable, especially as new variations in country names could appear in future
data loads.
C. Cleanse the source text file prior to loading: This option would require modifying
