CloudAcademy: Knowledge Check: Databases (SAA-C03) 2 of 2

Question 1

With Amazon QLDB, you can rest assured that nothing has changed or can be changed through the use of a _____.

A. ledger distributed across multiple hosts
B. database journal
C. server
D. node slice

Answer 1

B. database journal

Explanation:
This means you can rest assured that nothing has changed or can be changed through the use of a database journal, which is configured as append-only.

Question 2

Which type of Amazon DocumentDB endpoint allows connectivity to read replicas but not primary instances?

A. Reader
B. Instance
C. Writer
D. Cluster

Answer 2

A. Reader

Explanation:
A Reader endpoint allows connectivity to any read replicas that you have configured within the region.

Question 3

In relation to Amazon QLDB, what is a database journal?

A. the immutable transaction log that records all entries in a sequenced manner over time
B. the list of all users that are authorized to access the database
C. the settings of your ledger, such as ID, journal size, index storage size, ARN, and region
D. the list of all users that have accessed the database

Answer 3

A. the immutable transaction log that records all entries in a sequenced manner over time

Explanation:
This means you can rest assured that nothing has changed or can be changed through the use of a database journal, which is configured as append-only–essentially, the immutable transaction log that records all entries in a sequenced manner over time.

Question 4

Amazon Redshift operates as a _____ database management system.

A. NoSQL
B. relational
C. object
D. graph

Answer 4

B. relational

Explanation:
Redshift operates as a relational database management system, and therefore is compatible with other RDBMS applications.

Question 5

Amazon QLDB is a _____ database.

A. ledger
B. document
C. graph
D. relational

Answer 5

A. ledger

Explanation:
What actually is Amazon QLDB? It’s yet another fully managed and serverless database service, which has been designed as a ledger database.

Question 6

Amazon Keyspaces is compatible with _____.

A. MySQL
B. MongoDB
C. Firebase
D. Apache Cassandra

Answer 6

D. Apache Cassandra

Explanation:
Keyspaces is a serverless, fully-managed service designed to be highly scalable, highly available, and, importantly, compatible with Apache Cassandra, meaning you can use all the same tools and code as you do normally with your existing Apache Cassandra databases.

Question 7

Which of the following tasks is not one of the five challenges that a good data lake will deal with well?

A. normalization
B. generic analytics
C. predictive analytics
D. data movement

Answer 7

A. normalization

Explanation:
A good data lake will deal with these five challenges well: storage (the lake itself), data movement (how the data gets to the lake), data cataloging and discovery (finding the data and classifying it), generic analytics (making sense of that data), and predictive analytics (making educated guesses about the future based on the data).

Question 8

When using Amazon Keyspaces, how can you run queries using CQL?

A. programmatically using an Apache 2 licensed Cassandra client driver
B. through the CQL editor in the Amazon Keyspaces dashboard within the AWS management console
C. all of these
D. on a CQLSH client

Answer 8

C. all of these

Explanation:
There are a number of ways to run queries using CQL. Firstly, from within the Amazon Keyspaces dashboard within the AWS management console, you can use the CQL editor, which can return as many as a thousand records per query. If you are querying more than a thousand records, then you will need to run multiple queries together. You can run them on a CQLSH client, or you can run them programmatically using an Apache 2 licensed Cassandra client driver.

Question 9

_______________ allows you to set up your secure data lake by identifying existing data sources that you want to move into your data lake, and then crawling, cataloging, and preparing all that data for you to perform analytics on.

A. Amazon OpenSearch Service
B. Amazon Athena
C. AWS Glue
D. AWS Lake Formation

Answer 9

D. AWS Lake Formation

Explanation:
We can use the AWS Lake Formation service, which promises to make setting up your secure data lake take only a matter of days, instead of weeks or months. It does this by identifying existing data sources within Amazon S3, relational databases, and NoSQL databases that you want to move into your data lake. It then will crawl and catalog and prepare all that data for you to perform analytics on.

Question 10

What is a node slice in Amazon Redshift?

A. a grouping of compute nodes
B. a cached copy of query results
C. a query performed on the data in your warehouse
D. a partition of a compute node where the node’s memory and disk spaces split

Answer 10

D. a partition of a compute node where the node’s memory and disk spaces split

Explanation:
A node slice is simply a partition of a compute node where the node’s memory and disk spaces split.

Question 11

The AWS Lake Formation service’s functionally is managed by using _____.

A. partitions
B. logs
C. schemas
D. blueprints

Answer 11

D. blueprints

Explanation:
All of Lake Formation’s functionally is managed by using “blueprints” where you simply: point to the source data, point where you want to load that data in the data lake, and specify how often you want to load that data.

Question 12

Amazon Redshift is a fast, fully-managed, _____-scale data warehouse.

A.megabyte
B. gigabyte
C. petabyte
D. terabyte

Answer 12

C. petabyte

Explanation:
Amazon Redshift is a fast, fully-managed, petabyte-scale data warehouse.

Question 13

The Amazon DocumentDB replicas are responsible for _____.

A. only write operations
B. neither read nor write operations
C. both read and write operations
D. only read operations

Answer 13

D. only read operations

Explanation:
The replicas will only process read requests to the cluster volume.

Question 14

Which of the following statements about AWS Lake Formation service is false?

A. It ties data access with access control policies with each individual service instead of within the data catalog.
B. It will take care of user security by creating self-service access to data through your choice of analytics services.
C. It can pull data all at once, or it can pull it incrementally.
D. When you use the Lake Formation service, you have to pay a fee for it, plus you have to pay for all the services it uses.

Answer 14

D. When you use the Lake Formation service, you have to pay a fee for it, plus you have to pay for all the services it uses.

Explanation:
We can use the AWS Lake formation service, which promises to make setting up your secure data lake take only a matter of days, instead of weeks or months. It does this by identifying existing data sources within Amazon S3, relational databases, and NoSQL databases that you want to move into your data lake. All this data can be grabbed all at once, or it can be taken incrementally. AWS Lake Formation will take care of user security by creating self-service access to that data through your choice of analytics services. It does this by setting up users’ access within Lake Formation, by tying data access with access control policies within the data catalog instead of with each individual service. There is no additional pricing for using the Lake Formation service, but you do have to pay for all the services it uses, though.

Question 15

In Amazon DocumentDB, a cluster is composed of _____.

A. multiple DB instances
B. a single DB instance
C. exactly two read replicas
D. a single or multiple DB instances

Answer 15

D. a single or multiple DB instances

Explanation:
The database itself is comprised of a core component–a cluster–and this cluster is composed of a single or multiple DB instances, up to 16 in total, which can span across different availability zones within a single region.

Question 16

Which of the following statements about data lakes and data warehouses is true?

A. A data warehouse is a specialized tool that allows you to perform analysis on a portion of data from a data lake.
B. Generally, a data lake is a subset of the data from a data warehouse with a specialized purpose.
C. A data warehouse is a formless blob of information.
D. A data lake is an optimized database dealing with normalized, transformed, and cleaned-up versions of the data from a data warehouse.

Answer 16

A. A data warehouse is a specialized tool that allows you to perform analysis on a portion of data from a data lake.

Explanation:
A data lake is a formless blob of information. It is a pool of knowledge where we try to capture any relevant data from our business so that we can perform analytics on it. A data warehouse is a specialized tool that allows you to perform analysis on a portion of that data, so you can make meaningful decisions from it. Generally, it is a subset of the data from the data lake with a specialized purpose. Your data warehouse Is an optimized database that is dealing with normalized, transformed, and cleaned-up versions of the data from the data lake.

Question 17

How many primary DB instances can perform write operations in a cluster at one time in Amazon DocumentDB?

A. 2
B. 4
C. 3
D. 1

Answer 17

D. 1

Explanation:
There will only ever be a single primary DB instance performing write operations in the cluster at any one time.

Question 18

How often does Amazon DocumentDB create snapshots of your storage volume?
A. monthly
B. daily
C. every 30 minutes
D. hourly

Answer 18

B. daily

Explanation:
The automated backups themselves are performed daily. The backup retention period determines how long DocumentDB will keep and maintain your backups and can be set anywhere between 0 and 35 days.

Question 19

Which of the following is automatically discovered by an AWS Lake Formation service blueprint?
A. how often to load the data in the data lake
B. where to load the data in the data lake
C. the source’s table schema
D. the location of the source data

Answer 19

C. the source’s table schema

Explanation:
All of the functionality of Lake Formation is managed by using “blueprints” where you simply:

Point to the source data
Point where you want to load that data in the data lake
Specify how often you want to load that data and the blueprint
Discover the sources table schema
Automatically converts to a new target format
Partitions the data based on partitioning schema
Keeps track of the data that was already processed
Allows you to customize all the above actions

Question 20

Which data lake challenge deals with how the data gets to the lake?

A. storage
B. data cataloging and discovery
C. data movement
D. generic analytics

Answer 20

C. data movement

Explanation:
A good data lake will deal with these five challenges well: storage (the lake itself), data movement (how the data gets to the lake), data cataloging and discovery (finding the data and classifying it), generic analytics (making sense of that data), and predictive analytics (making educated guesses about the future based on the data).