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Integrate Azure Synapse Analytics with Azure Data and AI services Microsoft Quiz Answers
Get Integrate Azure Synapse Analytics with Azure Data and AI services Microsoft Quiz Answers
Learn how Azure Synapse Analytics integrates with other Azure Data and AI services.
Prerequisites:
- It is recommended that students have completed Data Fundamentals before starting this learning path.
- It is recommended that students understand how Azure Synapse Analytics and its components work.
Module 1: Build reports using Power BI within Azure Synapse Analytics
In this module, you will learn how you can build Power BI reports from within Azure Synapse Analytics.
Learning objectives:
In this module, you will:
- Describe the Power BI and Synapse workspace integration
- Understand Power BI data sources
- Describe optimization options
- Visualize data with serverless SQL pools
Prerequisites:
- It is recommended that students understand how Azure Synapse Analytics and Power BI works.
This module is part of these learning paths:
- Implement and manage an analytics environment
- Integrate Azure Synapse Analytics with Azure Data and AI services
Quiz 1: Knowledge check
Q1. What data source connection method loads all of the data into the Power BI cache, and runs queries against the ingested data?
- DirectQuery
- Import Connection
- Hybrid Connection
Q2. What can be considered a benefit of materialized views?
- A different data distribution compared to the base tables.
- Decreased query performance for complex queries with JOINs and aggregate functions, but increased performance for simple queries.
- Instant query response times for repetitive query patterns.
Q3. What is a limitation of result-set caching?
- The maximum size of the result set cache is 1 TB per database.
- Users cant manually empty the result set cache.
- Pausing the database will clean the cache
Module 2: Integrate machine learning within Azure Synapse Analytics
In this module, you will learn how you can build machine learning modules from within Azure Synapse Analytics.
Learning objectives:
In this module, you will:
- Describe Azure Machine Learning and how it integrates with an Azure Synapse Analytics workspace
- Describe Azure Machine Learning AutoML
- Understand how to score machine learning models with PREDICT
Prerequisites:
- It is recommended that students understand how Azure Synapse Analytics and Azure Machine Learning Services works
This module is part of these learning paths:
Quiz 1: Knowledge check
Q1. What compute target is used when AutoML runs through the Spark pool inside Synapse Analytics?
- Local Compute.
- Remote compute
- Cloud Compute
Q2. What can help to make sure AutoML Models support ONNX format?
- Define
enable_onnx_compatible_modelsasFalseinAutoMLConfig. - Enable ONNX model compatibility on the portal during enrichment model configuration.
- Using Azure Machine Learning workspace instead of the Azure Synapse Workspace.
Q3. What is correct about T-SQL PREDICT command?
- Generates a predicted value or scores based on a stored model within the confines of the data warehouse.
- It does not support ONNX format for models in Azure SQL Managed Instance, Azure SQL Edge, and Azure Synapse Analytics.
- Special permissions are required to use the PREDICT command
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