VALID DUMPS C_SAC_2421 PDF & SAP C_SAC_2421 LATEST EXAM SIMULATOR: SAP CERTIFIED ASSOCIATE - DATA ANALYST - SAP ANALYTICS CLOUD PASS SUCCESS

Valid Dumps C_SAC_2421 Pdf & SAP C_SAC_2421 Latest Exam Simulator: SAP Certified Associate - Data Analyst - SAP Analytics Cloud Pass Success

Valid Dumps C_SAC_2421 Pdf & SAP C_SAC_2421 Latest Exam Simulator: SAP Certified Associate - Data Analyst - SAP Analytics Cloud Pass Success

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Three Easy-to-Use and Compatible CertkingdomPDF SAP C_SAC_2421 Exam Questions

To attempt the SAP C_SAC_2421 exam optimally and ace it on the first attempt, proper exam planning is crucial. Since the SAP Certified Associate - Data Analyst - SAP Analytics Cloud (C_SAC_2421) exam demands a lot of time and effort, we designed the SAP Certified Associate - Data Analyst - SAP Analytics Cloud (C_SAC_2421) exam dumps in such a way that you won't have to go through sleepless study nights or disturb your schedule. Before starting the SAP Certified Associate - Data Analyst - SAP Analytics Cloud (C_SAC_2421) preparation, plan the amount of time you will allot to each topic, determine the topics that demand more effort and prioritize the components that possess more weightage in the SAP Certified Associate - Data Analyst - SAP Analytics Cloud (C_SAC_2421) exam.

SAP C_SAC_2421 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Planning: SAP Analytics Cloud Data Analysts are expected to demonstrate proficiency in planning within the SAP Analytics Cloud environment. The exam evaluates the ability to create and manage planning models, including setting up dimensions, accounts, and versions. Candidates should be familiar with creating planning input forms and implementing planning processes.
Topic 2
  • Data modeling, analysis, and integration: This section focuses on the core analytical capabilities of SAP Analytics Cloud. SAP Analytics Cloud Data Analysts should demonstrate proficiency in creating and managing data models, performing advanced analysis, and integrating data from various sources. The exam assesses skills in creating calculated measures, applying filters, and using advanced analytical functions.
Topic 3
  • Connections and data preparation: This domain covers the essential skills of connecting to data sources and preparing data for analysis. SAP Analytics Cloud Data Analysts are expected to show competence in establishing connections to various data sources, including on-premise and cloud-based systems.
Topic 4
  • Performance, troubleshooting, and security management: This domain covers critical aspects of maintaining and optimizing SAP Analytics Cloud environments. It assesses SAP Analytics Cloud Data Analysts' abilities in performance tuning, troubleshooting common issues, and implementing security measures.
Topic 5
  • Story Design: This section of the exam measures the skills of SAP Analytics Cloud Data Analysts and covers various aspects of story design in SAP Analytics Cloud. The exam assesses the knowledge of candidates who should be able to create effective and visually appealing stories to present data insights. This includes understanding different chart types, layout options, and interactive elements to enhance data visualization and user engagement.

SAP Certified Associate - Data Analyst - SAP Analytics Cloud Sample Questions (Q17-Q22):

NEW QUESTION # 17
You are creating a styling rule for a table. What is the context?

  • A. The table header
  • B. The location of the cursor
  • C. The most granular level in the table
  • D. The highest level in the table

Answer: B


NEW QUESTION # 18
What is required to use version management in a story?

  • A. Analytic model
  • B. Planning model
  • C. Optimized mode
  • D. Classic mode

Answer: B

Explanation:
Reference:
SAP Analytics Cloud Help Documentation: Version Management in Planning
SAP Analytics Cloud User Guide: Using Planning Models for Versioning


NEW QUESTION # 19
You input new data for a private version in a story. What must you do to ensure the new data is added to the model?

  • A. Save
  • B. Send
  • C. Nothing
  • D. Publish

Answer: D

Explanation:
When inputting new data for a private version in a story in SAP Analytics Cloud, it is necessary to "Publish" the data to ensure it is added to the model. Publishing the private version commits the changes to the underlying model, making the new data visible and accessible to other users according to their permissions. This step is crucial for ensuring that the updated data is incorporated into the shared model for further analysis and decision-making.
Reference:
SAP Analytics Cloud Help Documentation: Private Versions and Publishing SAP Analytics Cloud User Guide: Working with Private Versions in Stories


NEW QUESTION # 20
You are creating a styling rule for a table with a hierarchy of Country, Region, and City. You want to apply the styling rule only to countries. Which level option must you use?

  • A. Self and Siblings
  • B. Self
  • C. Self and Descendants
  • D. Self and Children

Answer: B

Explanation:
To apply a styling rule only to countries in a table with a hierarchy of Country, Region, and City in SAP Analytics Cloud, you must use the "Self" level option. This option ensures that the styling rule is applied specifically to the level of the hierarchy representing countries, without affecting the styling of regions, cities, or any other hierarchical levels.
Reference:
SAP Analytics Cloud Help Documentation: Styling Hierarchical Tables
SAP Analytics Cloud User Guide: Hierarchical Styling Options


NEW QUESTION # 21
You import data into a dataset. One of the columns imported is Year, and SAP Analytics Cloud interprets it as a measure. How can you ensure that it is treated as a calendar year?

  • A. Add the month as a suffix to the Year measure.
  • B. Includes the Year measure in a level-based time hierarchy in the dataset.
  • C. Change the Year measure to a dimension in the dataset.
  • D. Insert a character into the Year measure using the transform bar.

Answer: C

Explanation:
If SAP Analytics Cloud interprets a 'Year' column as a measure instead of a dimension, it should be changed to a dimension to ensure it is treated as a calendar year. This adjustment can be made within the model or dataset settings, where the column's role can be switched from a measure (quantitative value) to a dimension (qualitative value). Treating 'Year' as a dimension allows it to be used appropriately in time-based analyses, such as trends over time, without being aggregated like a numerical measure.


NEW QUESTION # 22
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