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NEW QUESTION # 31
Which of the following activities does SAP Business Data Cloud cockpit support? Note: There are 2 correct answers to this question.
Answer: B,C
Explanation:
The SAP Business Data Cloud (BDC) Cockpit serves as the central administrative and operational interface for managing the BDC environment. Among its core functionalities, it directly supports the ability to configure SAP Business Data Cloud. This includes setting up connections, managing spaces, configuring system parameters, and generally overseeing the platform's infrastructure. It provides administrators with the necessary tools to tailor the BDC environment to specific organizational needs. Additionally, the cockpit is instrumental in allowing users to discover and activate data products. Data products are pre-built, semantically rich data assets that encapsulate business logic and data from various sources, offered within the BDC ecosystem. The cockpit acts as a marketplace or catalog where users can find relevant data products, understand their content, and activate them for use in their analytics and applications. While "Enhance Analytic Models" is done in tools like SAP Datasphere's Data Builder and debugging authorization issues might involve various tools, direct configuration and data product management are key features of the BDC Cockpit.
NEW QUESTION # 32
Which components support semantic enrichment of data in SAP Business Data Cloud?
There are 2 correct answers to this question.
Response:
Answer: B,D
NEW QUESTION # 33
Which entity can be used as a direct source of an SAP Datasphere analytic model?
Answer: C
Explanation:
An SAP Datasphere analytic model is specifically designed for multi-dimensional analysis, and as such, it requires a central entity that contains the measures (key figures) to be analyzed and links to descriptive dimensions. Therefore, a View of semantic type Fact (B) is the most appropriate and commonly used direct source for an analytic model. A "Fact" view typically represents transactional data, containing measures (e.g., sales amount, quantity) and foreign keys that link to dimension views (e.g., product, customer, date). While "Dimension" type entities (A) provide descriptive attributes and are linked to the analytic model, they are not the direct source of the model itself. Tables of semantic type Hierarchy (C) are used within dimensions, and remote tables of semantic type Text (D) typically provide text descriptions for master data, not the core fact data for an analytic model. The Fact view serves as the central point for an analytic model's measures and its connections to all relevant dimensions.
NEW QUESTION # 34
What is required to use version management in an SAP Analytics Cloud story?
Answer: A
Explanation:
To leverage version management capabilities within an SAP Analytics Cloud (SAC) story, it is a fundamental requirement that the story is built on a planning model. Version management is a core feature specifically designed for planning functionalities. It enables users to create, manage, and compare different scenarios or iterations of data, such as "Actual," "Budget," "Forecast," or various planning versions. This is critical for budgeting, forecasting, and what-if analysis, allowing planners to work on different data sets concurrently and track changes over time. While analytic models are used for general reporting and analysis, they do not inherently support the robust version management features that are integral to planning processes. Therefore, if you intend to utilize version management to compare different data scenarios or manage planning cycles, your SAC story must be connected to a planning model.
NEW QUESTION # 35
Which of the following is true about data access control in SAP Business Data Cloud?
Please choose the correct answer.
Response:
Answer: A
NEW QUESTION # 36
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