Exam AZ-305 topic 4 question 63 discussion

The correct answer should be C and E ADF moves data from on-prem Oracle to Data Lake storage, which makes data ready for DataBrick https://docs.microsoft.com/en-us/azure/data-factory/load-azure-data-lake-storage-gen2 DataBricks "ETL" data to Synapse: https://docs.microsoft.com/en-us/azure/databricks/scenarios/databricks-extract-load-sql-data-warehouse

Two Services not storage

C & E are correct

This question appeared in the exam, August 2024. I gave this same answers listed here. I scored 870

To ensure that the data from App1 is available to Azure Databricks, you should include the following Azure services in your solution: 1. Azure Data Factory (E): Azure Data Factory can be used to create a data pipeline for ETL (Extract, Transform, Load) processes, which can move your data from the on-premises Oracle database to Azure¹⁴. 2. Azure Data Lake Storage (C): Azure Data Lake Storage can act as the intermediary storage area where the transformed data can be placed. Azure Databricks is tightly integrated with Azure Data Lake Storage, making it an ideal choice for storing your data. Please note that while Azure Data Box Gateway and Azure Data Box Edge are used for offline transfer of large amounts of data, and Azure Import/Export service is used for importing large amounts of data into Azure, they might not be necessary if your data can be transferred online or isn't extremely large.

From this link it looks like you can directly link to an Oracle DB from ADF, doesn't look like import/export would be required. I'm going with CE https://learn.microsoft.com/en-us/azure/data-factory/connector-oracle?tabs=data-factory

ADF - to extract and load data to Data Lake Data Lake - as it's the only storage generally supported by Databricks

C. Azure Data Lake Storage E. Azure Data Factory Azure Data Lake Storage is a secure, scalable and reliable data lake that allows you to perform analytics on large amounts of data. It's a great choice for storing large volumes of data, like what App1 might produce. Azure Data Factory is a cloud-based data integration service that allows you to create data-driven workflows for moving and transforming data at scale. In this case, it can be used to create a pipeline to move the data from your on-premises Oracle database to Azure Data Lake Storage, making it available for further processing with Azure Databricks. Azure Data Factory has built-in support for a wide range of data sources, including Oracle. After the data is stored in Azure Data Lake Storage, you can use Azure Databricks to transform the data and load it into the Azure Synapse Analytics instance.

B and E, teacher correct in question in Azure Course

Azure Data Lake Storage (Option C): Azure Data Lake Storage provides a scalable and secure repository for storing large amounts of data. You can ingest data from App1 into Azure Data Lake Storage, and then make it available for processing in Azure Databricks. Azure Data Factory (Option E): Azure Data Factory is a fully managed data integration service that allows you to orchestrate and automate data movement and data transformation workflows. You can use Azure Data Factory to extract data from App1, transform it using Azure Databricks, and then load it into Azure Synapse Analytics.

In AZ-304 it was ADL and ADF meaning CE https://www.examtopics.com/discussions/microsoft/view/51579-exam-az-304-topic-3-question-20-discussion/

This scenario should be consistent with using C and E. Azure Data Factory is a recommended solution for migrating Oracle data. Azure Data Lake storage can then hold the data in a useable format for the chosen solution: Azure Databricks. Azure Data Box Gateway does not natively support Oracle. Azure Data Box Edge is an appliance not a service. And the azure import/export service is for one-shot migrations not really suitable for this scenario.

CE should be the answer, why somone want to use Azure Import/Export service!

CE is the answer. https://learn.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-introduction#designed-for-enterprise-big-data-analytics Data Lake Storage Gen2 makes Azure Storage the foundation for building enterprise data lakes on Azure. Designed from the start to service multiple petabytes of information while sustaining hundreds of gigabits of throughput, Data Lake Storage Gen2 allows you to easily manage massive amounts of data. https://learn.microsoft.com/en-us/azure/data-factory/introduction Big data requires a service that can orchestrate and operationalize processes to refine these enormous stores of raw data into actionable business insights. Azure Data Factory is a managed cloud service that's built for these complex hybrid extract-transform-load (ETL), extract-load-transform (ELT), and data integration projects.

I remember answering another question Topic 1 Q26 https://www.examtopics.com/exams/microsoft/az-305/view/6/ The solution suggests import/export might be good option to ingest on-premise data continuously upstream to processing the data with ADF pipeline.

on-premise data => Azure Synapse Link for dataverse (import/export) => Data Factory (data pipeline) => data bricks

Is Correct C. Azure Data Lake Storage E. Azure Data Factory