SAP HANA 1.0 Exam Test

Hierarchy refers to a system or structure in which individuals or elements are organized into different levels or ranks, with each level having a parent-child relationship. This means that each element in a hierarchy has a direct relationship with another element, with one being the parent and the other being the child. Therefore, the statement that hierarchy has a parent-child relationship is true.

Measures are indeed data that can be quantified and calculated. They represent numerical values that can be used for analysis, comparison, and decision-making. By measuring data, we can gain insights, track progress, and make informed judgments. Therefore, the statement "Measures are the data that can be quantified and calculated" is true.

In Hana 1.0, data modeling is indeed done using the Information Modeler features in Studio. This means that users can utilize the Information Modeler tool within the Studio environment to create and manage data models. This tool provides a user-friendly interface for designing and defining data structures, relationships, and attributes. It allows users to visually create and modify data models, making it easier to organize and manipulate data within the Hana 1.0 system.

Attributes are indeed descriptive data or characteristics in SAP BW. In SAP BW, attributes provide additional information about the main data objects, such as master data or transaction data. They help in providing context and details to the main data objects. For example, in a sales transaction, attributes can include information like the customer's name, address, or contact details. These attributes help in analyzing and understanding the data better. Therefore, the given answer, "True," is correct.

Analytic Views in SAP HANA are indeed similar to InfoCubes in SAP BW. Both are used for analytical purposes and provide a multidimensional data model. Analytic Views in HANA allow users to define complex calculations, aggregations, and hierarchies, just like InfoCubes in BW. They both support business intelligence reporting and analysis, enabling users to gain insights from large volumes of data. Therefore, the statement "Analytic Views are like InfoCubes in BW" is true.

Analytical Views in data modeling allow us to link attributes to fact tables. Fact tables store the quantitative data that we want to analyze, while attributes provide additional context or descriptive information about the data. By linking attributes to fact tables, we can enrich our analysis by including relevant information such as dimensions, hierarchies, or metadata. This helps to provide a comprehensive view of the data and enables more in-depth analysis and reporting. Therefore, the statement "Attributes can be linked to fact tables in Analytical Views" is true.

Attributes are pieces of information that provide context and describe the characteristics or properties of data. They add meaning and help in understanding the data better. By adding attributes, data becomes more informative and can be analyzed and interpreted more effectively. Therefore, the statement "Attribute add context to data" is true.

In SAP BW, measures are indeed referred to as key figures. Key figures are numerical values that are used for analysis and calculations in SAP BW. They represent the quantitative data that is stored and processed in the system. By using key figures, users can perform various calculations, aggregations, and comparisons to gain insights and make informed decisions based on the data. Therefore, the statement "Measures are known as key figures in SAP BW" is true.

Hierarchies are leveled-based on multiple attributes, meaning that they are structured in a way that reflects different levels or ranks based on various criteria. This suggests that hierarchies are not solely determined by a single attribute but rather by a combination of multiple attributes. Therefore, the correct answer is true.

Attribute Views in BW are used to define and manage the characteristics or dimensions of data. They provide a way to organize and structure data in a hierarchical manner, similar to dimensions in a multidimensional data model. Attribute Views allow users to analyze and navigate data based on different attributes or characteristics, such as product, location, or customer. Therefore, the statement that Attribute Views are like dimensions in BW is true.

Attribute Views are a type of modeling view in data warehousing that are used to represent attributes or characteristics of data. These views provide a simplified and consolidated view of attributes from multiple tables or sources. By using attribute views, users can easily access and analyze attributes without having to navigate through complex data structures. Therefore, the statement "Attributes are modeled using Attribute Views" is true, as attribute views are specifically designed to model and represent attributes in a data warehouse environment.

The statement suggests that Import/Export is a feature of Information Modeler. This means that Information Modeler allows users to import and export data or models, which can be useful for sharing or transferring information between different systems or applications.

The statement is true because attributes can indeed be regarded as master data tables. Master data refers to the core data that is used as a reference for business transactions and decision-making. Attributes, on the other hand, are characteristics or properties of an entity. When attributes are organized in a structured manner, they can be stored in tables, similar to how master data is stored. These attribute tables can then be used as a reference for various purposes, such as data analysis, reporting, and data integration. Therefore, it is correct to say that attributes can be regarded as master data tables.

Calculation Views in SAP HANA are similar to virtual Providers with services concept in SAP BW. Both Calculation Views and virtual Providers are used to create reusable data models that can be accessed by different applications or reports. They provide a layer of abstraction between the underlying data sources and the consuming applications, allowing for flexibility and reusability. Therefore, the statement "Calculation Views are similar to virtual Provider with services concept in BW" is true.

By selecting the Data Preview tab, you can view the physical tables. This means that you can see the actual tables that store the data in a database. This feature allows users to get a glimpse of the structure and content of the tables, which can be helpful for data analysis and understanding the data model. It provides a visual representation of the physical data storage in the database.

Weight is a characteristic or property that can be measured and quantified. It is considered an attribute because it is a quality or feature that can be assigned to an object or entity. By measuring weight, we are assigning a numerical value to the attribute of weight possessed by an object. Therefore, the statement that a measure like weight can be defined as an attribute is true.

The correct answer is "Import source system metadata,Provision Data,Create Information Models, Deploy, Consume." This is the correct flow of the HANA Modeling Process. First, you import the metadata from the source system. Then, you provision the data to make it available for modeling. Next, you create the information models based on the provisioned data. After that, you deploy the models to make them accessible. Finally, you consume the deployed models to analyze and report on the data.

The correct answer outlines the correct sequence of steps in the process of creating an Attribute View. The process starts with setting parameters, followed by selecting tables, joining tables and setting properties, selecting attributes, creating hierarchies, saving and activating the view, and finally previewing the data. This sequence ensures that all necessary steps are completed in the correct order to successfully create the Attribute View.

Analytic Views in BW are not like dimensions. Analytic Views are used in SAP HANA to define complex calculations and aggregations on data, while dimensions in BW are used to categorize and organize data. Therefore, the statement that Analytic Views are like dimensions in BW is false.

Calculation Views are not like Info Cubes in BW. Calculation Views are used in SAP HANA to define complex calculations and aggregations on data. They are used for creating analytical models and are more flexible and powerful than Info Cubes in BW. Info Cubes, on the other hand, are a type of data structure used in SAP BW for storing and analyzing data in a multidimensional format. So, the statement that Calculation Views are like Info Cubes in BW is false.