Exam DP-900 topic 1 question 12 discussion

All 3 are Yes. This is not just a big data question.

YES, YES, YES Batch processing can have output to SQL Database, Hive, HBase, Spark SQL. Look at the link and the diagram there https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/batch-processing

✅ Yes ✅ Yes ✅ Yes

a. Yes Batch processing can output data to a file store, such as a data lake or blob storage, commonly used for storing large volumes of processed data. b. Yes Batch processing can load processed data into relational databases, often for reporting, analytics, or further processing. c. Yes Batch processing can also output data to NoSQL databases, especially for use cases where the data needs to be accessed in a flexible, schema-less format.

Batch processing can output data to a file store: Correct Answer: Yes Explanation: Batch processing can indeed output data to a file store. This is commonly used for storing large volumes of data in files, such as logs, reports, or backups. Batch processing can output data to a relational database: Correct Answer: Yes Explanation: Batch processing can also output data to a relational database. This is useful for scenarios where structured data needs to be stored and queried efficiently. Batch processing can output data to a NoSQL database: Correct Answer: Yes Explanation: Yes, batch processing can also output data to a NoSQL database. NoSQL databases are designed to handle unstructured or semi-structured data, making them suitable for various use cases.

YES YES YES

I was thinking that all 3 are yes. Based on Microsoft documentation there are 4 Sinks for stream processing namely Azure Event Hubs, Azure Data Lake Store Gen 2 or Azure blob storage, Azure SQL Database or Azure Synapse Analytics, or Azure Databricks, and Microsoft Power BI. Which I think that Azure SQL Database is a relational. Maybe the answer to this question is outdated based on the old technology.

Statement 1: Batch processing can output data to a file store. Yes. Batch processing can indeed output data to a file store. This is a common use case where processed data is stored in file systems like Azure Blob Storage or other similar cloud-based or on-premises file storage systems. Statement 2: Batch processing can output data to a relational database. Yes. Batch processing can output data to relational databases. After processing, the data can be structured and stored in relational database systems like Azure SQL Database, MySQL, PostgreSQL, or other relational databases. Statement 3: Batch processing can output data to a NoSQL database. Yes. Batch processing can also output data to NoSQL databases. This is particularly useful for unstructured or semi-structured data. NoSQL databases like Azure Cosmos DB, MongoDB, or others can be used for storing the results of batch processing tasks.

YNN "Big data solutions often use long-running batch jobs to filter, aggregate and otherwise prepare the data for analysis. Usually, these jobs involve reading source files from scalable storage (like HDFS, Azure Data Lake Store, and Azure Storage), processing them, and writing the output to new files in scalable storage." https://learn.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing

I have no experience with Azure batch, but seems it do not natively writes into sql, you need to add script and external libraries to run ETL operation within the batch job. Question is not clear at this point.

yes no no

Frankly Speaking, In real work, we always have Batch Processing using Spark to write into Postgres...Perhaps it is not the 100% perfect architecture but it is used in many projets...And Theorically, it is possible although it is not really ETL (Data should be all transformed before loading )

Should be Y Y Y

YYY!!!

Why the answer is not being fixed here?

YES YES YES

YES YES YES