Batch processing is used in a variety of scenarios, from simple data transformations to a more complete ETL (extract-transform-load) pipeline. In a big data context, batch processing may operate over very large data sets, where the computation takes significant time. (For example, see Lambda architecture.) Batch processing typically leads to further interactive exploration, provides the modeling-ready data for machine learning, or writes the data to a data store that is optimized for analytics and visualization. Refer to Microsoft Doc:

https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/batch-processing

Azure Files offers fully managed file shares in the cloud that are accessible via the industry standard Server Message Block (SMB) protocol or Network File System (NFS) protocol. Azure file shares can be mounted concurrently by cloud or on-premises deployments. Azure Files SMB file shares are accessible from Windows, Linux, and macOS clients. Refer to Microsoft Doc:

https://docs.microsoft.com/en-us/azure/storage/files/storage-files-introduction

You'll generally want to ingest data, do some pre-processing steps on it including possible de-normalization, in order to prepare it for analytics purposes. If the data can change as the analytics is going on, that is a bad environment for that task. Refer to Microsoft Doc:

https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/

You can have a small Azure SQL Database single instance (S0 plan) for only $14.70 per month. This includes 250 GB of storage. If your performance expectations are low (for an infrequently used internal application), this could be a great option. Refer to Microsoft Doc:

https://docs.microsoft.com/en-us/azure/azure-sql/database/cost-management

Data Manipulation Language (DML) affect the information stored in the database. Use these statements to insert, update, and change the rows in the database. These statements include SELECT, INSERT, UPDATE and DELETE. Refer to Microsoft Doc:

https://docs.microsoft.com/en-us/sql/t-sql/statements/statements?view=sql-server-ver15#data-manipulation-language

Azure Blob Storage is the best place to store binary data such as images, videos and other files. If you later need to reference it in a database, you might want to just provide a file name in the data table and leave the data in the storage account. SQL Database, Cosmos DB and Table Storage are not designed for storing large amounts of binary data such as videos. Refer to Microsoft Doc:

https://docs.microsoft.com/en-us/learn/modules/explore-non-relational-data-offerings-azure/3-explore-azure-blob-storage

A pipeline is a series of activities, and is the process by which data travels from its source, gets transformed, into one or more destinations. Refer to Microsoft Doc:

https://docs.microsoft.com/en-us/azure/data-factory/concepts-pipelines-activities

Azure SQL Transparent Data Encryption (TDE) with customer-managed key enables Bring Your Own Key (BYOK) scenario for data protection at rest, and allows organizations to implement separation of duties in the management of keys and data. With customer-managed transparent data encryption, customer is responsible for and in a full control of a key lifecycle management (key creation, upload, rotation, deletion), key usage permissions, and auditing of operations on keys. This key is stored in the Azure Key Vault. Refer to Microsoft Doc:

https://docs.microsoft.com/en-us/sql/relational-databases/security/encryption/extensible-key-management-using-azure-key-vault-sql-server?view=sql-server-ver15

A non-relational database is a database that does not use the tabular schema of rows and columns found in most traditional database systems. Instead, non-relational databases use a storage model that is optimized for the specific requirements of the type of data being stored. For example, data may be stored as simple key/value pairs, as JSON documents, or as a graph consisting of edges and vertices. Refer to Microsoft Doc:

https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/non-relational-data

If you need to white-list (or preapprove) a specific Ip address or range to the entire server, a server-level firewall rule should suffice. You could add individual database-level IP firewall rules, but that is not the optimal solution. An NSG cannot help here, and the Azure Firewall service is more complicated to set up. Refer to Microsoft Doc:

https://docs.microsoft.com/en-us/azure/azure-sql/database/firewall-configure