UDEMY Test2 Flashcards
Which GCP service provides a scalable, fully-managed Enterprise Data Warehouse (EDW) with SQL and fast response times? Google Cloud Bigtable Google Cloud Datastore Google Cloud Storage Google BigQuery
Google BigQuery
(Correct)
Explanation
Please refer https://cloud.google.com/storage-options/
K Means Clustering can be used to identify groups of numerical variables. These groups can then be used as categorical variables for models which requires categorical variables as an input (True/False) TRUE FALSE
TRUE
Correct
A user wishes to store structured data for a high-throughput analytics use case. The storage solution must also provide Low-latency read/write access. Which storage option is appropriate for this use case? Google Cloud Bigtable Google Cloud Datastore Google Cloud Storage Google BigQuery
Google Cloud Bigtable
(Correct)
Explanation
Please refer https://cloud.google.com/storage-options/
Cloud SQL PostgreSQL Instance supports Point-in-time recovery (PITR) (True/False) TRUE FALSE
FALSE
(Correct)
Explanation
Please refer https://cloud.google.com/sql/docs/features
\_\_\_\_\_\_\_\_\_ provides a managed Jupyter notebook environment to provide interactive tool for data exploration, analysis, visualization and machine learning Dataflow Datalab (Correct) Cloud SQL Dataproc
Datalab
(Correct)
Explanation
Please refer https://cloud.google.com/datalab/
Which GCP service provides mission-critical, relational database service with transactional consistency, global scale, and high availability? Google Cloud Spanner Google Cloud Datastore Google Cloud Storage Google Cloud Bigtable
Google Cloud Spanner (Correct) Explanation Please refer https://cloud.google.com/storage-options/
Cloud Composer is a managed \_\_\_\_\_\_\_\_\_\_ service that helps you create, schedule, monitor and manage workflows Apache Crunch Apache Beam Apache Airflow (Correct) Apache Nifi
Apache Airflow
(Correct)
Explanation
Please refer https://cloud.google.com/composer/docs/
\_\_\_\_\_\_\_\_\_\_\_ is a type of Machine Learning which aims to maximize a cumulative measure (say a reward) based on interactions with a given system. Eg: A robotic car needs to figure out the best way to traverse a path. The best way is the one with limited hurdles and the shortest path. Supervised Machine Learning Unsupervised Machine Learning Reinforcement Learning (Correct) Dimensionality Reduction Techniques
Reinforcement Learning
(Correct)
Explanation
It is based on definition of Reinforcement learning
Which GCP ML Service can help detect popular product logos within an image? Cloud Vision (Correct) Cloud Translation Cloud Video Intelligence Cloud Natural Language
Cloud Vision
(Correct)
Explanation
Please refer GCP ML Services Documentation https://cloud.google.com/products/ai/
Cloud Dataflow can be used to deploy both batch and streaming data processing pipelines (True/False) TRUE FALSE
TRUE (Correct) Explanation Please refer https://cloud.google.com/dataflow/docs/
\_\_\_\_\_\_\_\_ Google Cloud Storage is optimized for geo-redundancy and end-user latency Multi Regional Nearline Regional Coldline
Multi Regional
(Correct)
Explanation
Please refer https://cloud.google.com/storage/
The data mining project manager meets with the data warehousing manager to discuss how the data will be collected. Which stage in CRISP-DM does this scenario refer to? Data Preparation Modeling Phase Data Understanding Evaluation Phase
Data Understanding
Correct
Which GCP Service makes it easy for one to design and integrate a conversational user interface into a mobile app, web application, device, bot, interactive voice response systems, and so on? Cloud Video Intelligence Cloud Natural Language Cloud Vision Dialogflow
Dialogflow
(Correct)
Explanation
Please refer GCP ML Services Documentation https://cloud.google.com/products/ai/
A user wishes to develop an application that caters to the operational aspects of the business. For this, he needs an OLTP system to store the data. Which GCP service is appropriate for this use? Google Cloud SQL Google Cloud Storage Google Cloud Bigtable (Incorrect) Google Cloud Datastore
Google Cloud SQL
(Correct)
Explanation
Please refer https://cloud.google.com/storage-options/
Which among below is an inefficient practice while loading data in Cloud Spanner?
Partition your data by primary key
Commit between 1 MB to 5 MB mutations at a time
Sequentially add all rows in primary key order
(Correct)
Upload data before creating secondary indexes
Sequentially add all rows in primary key order
(Correct)
Explanation
Please refer https://cloud.google.com/spanner/docs/bulk-loading