Google Cloud Professional Data Engineer Certification Exam With 100%
Correct Answers
Data Life Cycle Steps - ANSWER Ingest, Store, Process/Analyze, Explore/Visualize
Define Ingest - ANSWER pull in raw data
-streaming/real-time data from devices
-on premises batch data
-application logs
Define Store - ANSWER data needs to be stored in format and location
Define Process/Analyze - ANSWER transform data from raw format to usable insights
Define Explore/Visualize - ANSWER create visualizations that are presentable
Ingest applications - ANSWER app engine
compute engine
kubernates engine
cloud pub/sub
stackdriver logging
cloud transfer
transfer appliance
Store applications - ANSWER cloud storage
SQL
,data store
bigtable
bigquery
cloud spanner
Process/Analyze applications - ANSWER dataflow
data proc
dataprep
bigquery
cloud ML
vision api
speech api
translate api
natural language api
video intelligence api
Explore/Visualize applications - ANSWER datalab
datastudio
Is data life cycle a set order? - ANSWER nope
example of batch data - ANSWER migrating files onto GCS
example of streaming data - ANSWER sensors in transportation vehicles
name a combination of software to manage streaming data - ANSWER pub/sub and
dataflow
, Cloud Storage Control Access - ANSWER globally available multi-region buckets
control access - project, bucket, or object level
Storage Transfer Service - ANSWER corporate data center to GCS
Data Transfer Appliance - ANSWER physically ship hard-drive to put data onto GCP
bucket
What are the 2 database types? - ANSWER relational/SQL, Non-relational/NoSQL
Pros/Cons of SQL - ANSWER pros: data integrity, consistency, durability
cons: poor scaling, not good for semi-structured data
Pros/Cons of NoSQL - ANSWER pros: scalable, high performance
cons: lack of consistency, data integrity
Examples of NoSQL - ANSWER Redis, MondoDB, Cassandra, HBase, BigTable,
RavenDB
Unmanaged DB No SQL Monitoring - Built-in v Add'l Monitoring - ANSWER Built-In - no
additional configuration needed; no visibility on actual application logs or performance
metrics
Additional Monitoring - download logging agent for application logs and monitoring
agent for monitoring logs metrics and performance
Stackdriver logging v stackdriver monitoring - ANSWER stackdriver logging - logs who
created an instance
Correct Answers
Data Life Cycle Steps - ANSWER Ingest, Store, Process/Analyze, Explore/Visualize
Define Ingest - ANSWER pull in raw data
-streaming/real-time data from devices
-on premises batch data
-application logs
Define Store - ANSWER data needs to be stored in format and location
Define Process/Analyze - ANSWER transform data from raw format to usable insights
Define Explore/Visualize - ANSWER create visualizations that are presentable
Ingest applications - ANSWER app engine
compute engine
kubernates engine
cloud pub/sub
stackdriver logging
cloud transfer
transfer appliance
Store applications - ANSWER cloud storage
SQL
,data store
bigtable
bigquery
cloud spanner
Process/Analyze applications - ANSWER dataflow
data proc
dataprep
bigquery
cloud ML
vision api
speech api
translate api
natural language api
video intelligence api
Explore/Visualize applications - ANSWER datalab
datastudio
Is data life cycle a set order? - ANSWER nope
example of batch data - ANSWER migrating files onto GCS
example of streaming data - ANSWER sensors in transportation vehicles
name a combination of software to manage streaming data - ANSWER pub/sub and
dataflow
, Cloud Storage Control Access - ANSWER globally available multi-region buckets
control access - project, bucket, or object level
Storage Transfer Service - ANSWER corporate data center to GCS
Data Transfer Appliance - ANSWER physically ship hard-drive to put data onto GCP
bucket
What are the 2 database types? - ANSWER relational/SQL, Non-relational/NoSQL
Pros/Cons of SQL - ANSWER pros: data integrity, consistency, durability
cons: poor scaling, not good for semi-structured data
Pros/Cons of NoSQL - ANSWER pros: scalable, high performance
cons: lack of consistency, data integrity
Examples of NoSQL - ANSWER Redis, MondoDB, Cassandra, HBase, BigTable,
RavenDB
Unmanaged DB No SQL Monitoring - Built-in v Add'l Monitoring - ANSWER Built-In - no
additional configuration needed; no visibility on actual application logs or performance
metrics
Additional Monitoring - download logging agent for application logs and monitoring
agent for monitoring logs metrics and performance
Stackdriver logging v stackdriver monitoring - ANSWER stackdriver logging - logs who
created an instance
