data modeling in power bi coursera week 1 answers

Self-review: Transforming multiple data sources

Introduction

In the exercise Configuring a Flat schema, you configured a Flat schema using Power BI. Your final Flat schema should resemble the following screenshot:

Answer the questions that follow to test your understanding of the process. Remember that you can refer to the previous lesson items if required.

1. How many tables were displayed in the Model View once the dataset was loaded?

  • A single table with one-to-many relationships.
  • A data structure that included multiple related tables.
  • A single table with multiple columns that included different data.

2. How many rows were present in the dataset after all duplicate rows were removed from the OrderID column in the Adventure Works dataset?

  • 37
  • 48
  • 96

3. What was the data type of the Product Price column after you loaded the data to Power BI before applying a transformation to the dataset?

  • Decimal Number
  • Whole Number
  • Date Text

Knowledge check: Introduction to data models

4. In Power BI, relationships are established between the tables based on _____________ that match between the tables.

  • Column fields
  • Table properties
  • Rows

5. What is the primary characteristic differentiating a Snowflake schema from a Star schema?

  • Normalized dimension tables.
  • Denormalized dimension tables.
  • A hierarchical structure.
  • A central Fact table.

6. What are the limitations of using a Flat schema in Power BI? Select all that apply.

  • A Flat schema offers limited capacity for storing large volumes of data.
  • A Flat schema cannot be used to perform aggregations.
  • A Flat schema offers a lack of flexibility for organizing data from multiple sources.

7. True or False: In Power BI, a schema is automatically created when you import data from various sources and establish relationships between tables.

  • True
  • False

8. Which property cannot be adjusted for a table or column in Power BI?

  • Data type
  • Sort order
  • Table relationship

Knowledge check: Introduction to cardinality and cross-filter direction

9. In the context of Power BI, which of the following descriptions best outlines the main purpose of a Fact table?

  • A Fact table is primarily used for storing descriptive attributes of business dimensions.
  • A Fact table is primarily used for storing detailed, transactional business data.
  • A Fact table is primarily used for storing measured, quantitative data about a business process.

10. Which of the following statements are true regarding cardinality and cross-filter direction in Power BI? Select all that apply:

  • Cardinality defines the number of unique values in one column compared to another.
  • Setting a cross-filter direction to Both allows filters to be applied from either direction in a relationship.
  • Cardinality and cross-filter direction are two key elements of model relationships in Power BI.

11. True or False: In Power BI, you can create a many-to-many relationship between tables.

  • True
  • False

12. In data analysis, __________ refers to the level of detail or summarization of your data.

  • Data granularity
  • Data cardinality
  • Cross-filter direction

13. What is the role of dimension tables in Power BI?

  • They store transactional data related to a business process.
  • They store the descriptive attributes of a business process.
  • They store measured, quantitative data about a business process.

Self-review: Configuring a Star schema

Introduction

In the exercise Configuring a Star schema, you learned how to configure a Star schema in Microsoft Power BI.

You imported the Sales, Products, Region, and Salesperson tables into Power BI. You then created a data model with a central fact table (Sales) linked to dimension tables (Products, Salesperson, and Region). This configuration provided a simplified, efficient, and optimized data model for querying and reporting purposes.

A screenshot of the final data model is included for reference:

Now it’s time to review your understanding of the tasks you completed by answering the following questions. Don’t forget that you can refer to previous lesson items to recap your process steps.

14. True or False: The Sales table was identified as a dimension table in the exercise.

  • True
  • False

15. Which relationship type was configured between the Fact table and dimension tables in the exercise?

  • Many-to-many
  • One-to-one
  • Many-to-one

16. True or False: The default cross-filter direction is set to Single, meaning that filters applied to the Products table will also apply to the Sales table, but not vice versa.

  • True
  • False

Knowledge check: Working with advanced data models

17. Which of the following statements is correct regarding a Star schema Fact table?

  • A Fact table must have a unique column
  • A Fact table stores an accumulation of business entities.
  • A Fact table stores an accumulation of business events.

18. How are dimension tables structured in a Snowflake schema?

  • They are normalized with a separate table for each attribute.
  • They are connected in a hierarchical structure with multiple levels.
  • They are fully denormalized, with all attributes in a single table.

19. What is the primary benefit of normalizing dimension tables in Power BI?

  • It improves data quality and accuracy.
  • It reduces storage requirements.
  • It simplifies data querying and reporting.

20. Which of the following statements is true about relationships in Power BI?

  • Relationships can only be created between tables with the same number of rows.
  • Relationships can be created between tables that contain different types of data.
  • Relationships can only be created between columns that contain the same data type.

21. True or False: A Star schema is more suitable for complex hierarchies and relationships.

  • True
  • False

Module quiz: Concepts for data modeling

22. Which of the following types of data is most suited to a Fact table?

  • Sales Revenue
  • Product Categories
  • Customer Information

23. Which of the following is an example of high-granularity data?

  • Sales data aggregated by month.
  • Sales data aggregated by region.
  • Sales data aggregated by product category.

24. You are working on a data model for a supply chain management system. You have a Suppliers table and a Products table in your dataset. Each supplier in the Suppliers table can provide multiple products, but each product in the Products table comes from a single supplier. What type of relationship must you establish between these tables?

  • One-to-many
  • Many-to-many
  • One-to-one

25. In an e-commerce data model, what would be the most suitable primary key for the Fact table?

  • A Customer ID column that lists the unique ID of each customer.
  • A Product ID column that lists the unique ID of each product.
  • A Sales transaction ID column that lists the unique ID of each transaction.

26. When establishing relationships between tables in Power BI, which of the following options can be used as the basis of the relationship? Select all that apply:

  • Primary keys and foreign keys.
  • Unique identifiers.
  • Common fields or columns.

27. You are working as a data modeler for a customer support system. You have a table called Tickets to track customer inquiries and an Agents table to store agent information. Each ticket is assigned to a single agent, but each agent can handle multiple tickets. What type of relationship can you establish between these tables?

  • Many-to-many
  • One-to-one
  • One-to-many

28. What is the impact of selecting the Both cross-filter direction in Power BI?

  • A filter applied to one table affects the other but not vice versa.
  • Filters applied to either table in the relationship affect the other table.
  • Filters applied to either table do not affect the other table.

29. Which of the following is not a component of a Star schema?

  • A dimension table.
  • A Fact table.
  • A denormalized table.

30. Which of the following tables are examples of dimension tables in a data model? Select all that apply:

  • Sales
  • Product
  • Employees
  • Customer

31. Which of the following statements describes the impact of retaining duplicated values in a dataset? Select all that apply:

  • They can skew analytical results and lead to incorrect insights.
  • They create difficulty in establishing relationships between data tables.
  • They increase the storage requirements and slow down query performance.

32. Which of the following statements accurately describes a Fact table in Power BI?

  • A table that provides descriptive attributes.
  • A table that contains numerical data.
  • A table used for storing Measures.

33. What does data granularity mean?

  • The nature of the relationship between two tables.
  • The level of detail that is represented in the dataset.
  • A filter direction associated with the relationship between two tables.

34. Adventure Work’s data warehouse includes a Products table that stores data on products, a ProductCategories table that stores product categories. Each product can belong to multiple categories, and each category can have multiple products. Which cardinality type should you set to represent the relationships between these two tables in the model?

  • One-to-one
  • Many-to-many
  • One-to-many

35. True or False: Fact tables in Power BI are denormalized to optimize query performance.

  • True
  • False

36. You are working as a data modeler for a bank. You have a table called Branches and a table called Accounts. What happens if you select Both cross-filter direction between the Accounts Fact table and the Branches dimension table?

  • Selecting a specific branch will filter the account table for that branch.
  • Selecting a value from either table will filter the related table.
  • Selecting an account will filter the branch for that account.

37. A Power BI model contains two tables called Products and Orders. The Orders table contains information about each customer’s orders. The Products table contains details about the products sold. You need to filter the Products table based on the selected values in the Orders table. Which cross-filter direction should you apply?

  • Single
  • Both
  • None

38. Which of the following statements is true regarding Snowflake schemas in Power BI? Select all that apply:

  • A Snowflake schema requires fewer tables compared to a Star schema.
  • A Snowflake schema improves query performance.
  • A Snowflake schema reduces data redundancy.

39. True or False: The default state of dimension tables in Power BI is denormalized.

  • False
  • True

40. Which of the following tools can be used to configure table and column properties in Power BI? Select all that apply:

  • The Power BI Properties pane in the model view.
  • The Power BI Visualization pane
  • The Power Query editor.

41. What is the benefit of high data granularity?

  • It simplifies the data modeling process.
  • It reduces the need for data transformation and cleaning.
  • It allows for more detailed and precise analysis.

42. What are the benefits of establishing relationships between tables? Select all that apply:

  • It reduces storage requirements for the data model.
  • It allows you to combine data from multiple tables for analysis.
  • It facilitates drill-down analysis from high-level to detailed data.

43. You want to merge two tables in Power BI. Which function can you use in the Power Query editor to combine the two tables?

  • Merge queries
  • Column tools
  • Table tools

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