Reading the documentation of Azure and the training seems to me that Azure Data Lake Analytics is equal to Azure Data Lake storage. Is it correct?
I saw also that Data Lake Storage Gen2 is based on Blob storage capabilities but this is not mentioned in the lesson. Is it correct?
In the documentation Azure is also dividing into 4 stages the process of Big data with the different technology, for example:
- Ingestion: Azure Data Factory, Apache Kafka for HDInsight, Stream Analytics
- Store: Azure Data Lake Storage Gen2
- Prep and train: Azure Databricks, Azure HDInsight, Azure Machine Learning Services
- Model and serve: Azure Synapse Analytics, Azure Cosmos DB, Azure SQL Database, Azure Analysis Services
In the lesson seems to me that they are all equivalent, (Azure Data Lake Analytics vs Azure Databricks vs HDInsights etc…)
Naturally, I’m not an expert in Big Data Technology can someone explain also this part?
How awesome that you are on top of the details like that! The aim of the Big Data lecture is to give a very basic introduction to the concepts and some of the Azure services that is used in the space.
Having said that, you are right in the 4 steps of Big Data in conjunction with Machine Learning services.
If you want to learn more about Azure ML and Big data, I’d suggest starting here: https://acloud.guru/overview/azure-ml-studio