Getting Started with Data Warehousing and BI Analytics | Coursera Quiz Answers

Getting Started with Data Warehousing and BI Analytics | Coursera

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Week 01 Quiz Answer

Graded Quiz: An Introduction to Data Warehouses, Data Marts, and Data Lakes

1. What is a data warehouse? Choose the best answer.

• A data distribution system
• A data storage
• A system that aggregates data from one or more sources into a single consistent data store to support data analytics
• None of the above.

2. What data warehouse vendors offer “on premises and cloud” services?

• Amazon RedShift
• Google BigQuery4
• IBM Db2 Warehouse
• Snowflake

3. What are data marts used for?

• Better data quality
• Scalable storage capacity
• Can quickly repurpose data for a wide range of use cases
• Help end users focus only on relevant data

4. What are data lake benefits?

• Handles specifically unstructured date
• Medium storage capacity
• Modifiable navigation paths
• Handles all types of data – unstructured, semi-structured, and structured

5. What are the benefits of a data warehouse?

• Hosted on-premises
• Large-scale data warehousing management overhead
• Faster business insights
• None of the answers is correct.

6. Where have we started hosting data warehouses in the last decade?

• On-premises
• In the cloud
• On the shelf
• None of the answers above is correct.

Week 02 Quiz Answer

Graded Quiz: Designing, Modeling and Implementing Data Warehouses

1. Considering a general architectural model for an Enterprise Data Warehouse, which of these components is holding data and developing workflows?

• Enterprise data warehouse repository
• Staging and sandbox areas
• Data sources
• Data marts

2. Materialized views can be used to __________.

• safely work with affecting source database
• synchronize updates
• automatically safe query results
• replicate data

3. Accumulating snapshot fact tables are used to __________.

• record events
• load data
• process events
• extract data

4. What do we call a normalized version of the star schema?

• Normalized schema
• Snowflake schema
• Parent dimension
• Product schema

5. In what location is data from source systems extracted to?

• Staging area
• Business intelligence platform
• Target systems
• Operating system

6. Materialized Views can be set up to have different refresh options, such as: (Select 1 answer).

• Populated
• Never, upon request, and immediately
• Automatically
• Manually refresh

Week 03 Quiz Answer

Graded Quiz: Data Warehouse Analytics

1. In the “How to Sign Up” video, which item in the account form is described as the key one to take note of when you sign up for a trial of Cognos Analytics?

• Your country /region
• Your closest data center
• Your name
• Your address

2. What is the first step to build a dashboard in Cognos Analytics?

• Choose a template
• Upload a spreadsheet or workbook
• Provide questions and answers to the assistant
• Select visualizations

3. Which of the following methods can be used in Cognos Analytics to create visualizations? (Select all 3 correct answers)

• By using widgets
• By using the Assistant to suggest questions and suggested visualizations
• By using automatic recommended visualizations
• By manually populating by dragging and dropping

4. How can you create infographics in Cognos Analytics?

• Use Exclude to filter out some data
• Modify navigation paths
• Ask the Assistant different questions
• Drag and drop a widget shape icon onto a visualization

5. There are many solutions available in the market that empower organizations with the ability to perform advanced analytics. Which solution offers scalability for small and large organizations?

• Tableau
• Tibco Spotfire
• Oracle Analytics
• Microsoft Power BI

6. Organizations can use BI tools’ built-in expertise to analyze data and find patterns using machine learning based on statistical modeling. Today’s analytical tools have reduced the time to churn data so much that results are now almost real-time.

• prescriptive
• promising
• unspecified
• retrospective

Week 04 Quiz Answers

1. ESPs are a middle layer between multiple event sources and destinations. ESPs may have different architectures and components but also some common components. Which of the following common components receives and consumes events?

• Event broker

2. The core component of any ESP is the event broker. Which event broker sub-component performs encryption on data?

• Processor

3. The Kafka server side is a cluster with many associated servers. What are the associated servers called?

• Brokers

4. Which of the following Kafka main features provides consumption without a deadlin

• Permanent persistency

5. Which of the following Kafka core components publish events into topics

• Producers

6. Which of the Kafka CLI script files manages topics

• Kafka-topics

7. Which of the following is Kafka Streams API based on?

• Computational graph

8. Which of the following do stream processors do?

• Receives, transforms, and forwards

9. Kafka Streams API is based on a computational graph called a stream processing topology. And in the topology, each node is a stream processor, while edges are the I/O streams. In this topology we find two special types of processors: What are they called

• Source and sink processor

10. Once events are published and properly stored in topic partitions, you can create _________ to read them.

• Consumers

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