Recommend an Azure data storage solution based on requirements :

• Choose the correct data storage solution to meet technical & business requirements

• Choose the partition distribution type

Design non-relational cloud data stores :

• Design data distribution and partitions

• Design for scale (including multi-region, latency, and throughput)

• Design a solution that uses cosmos DB, data lake storage gen2, or blob storage

• Select the appropriate cosmos DB API

• Design a disaster recovery strategy

• Design for high availability

Design relational cloud data stores :

• Design data distribution and partitions

• Design for scale (including latency, and throughput)

• Design a solution that uses azure synapse analytics

• Design a disaster recovery strategy

• Design for high availability

Design batch processing solutions :

• Design batch processing solutions that use Data Factory and Azure Databricks

• Identify the optimal data ingestion method for a batch processing solution

• Identify where processing should take place, such as at the source, at the destination, or in transit

Design real-time processing solutions :

• Design for real-time processing by using Stream Analytics and Azure Databricks

• Design and provision compute resources

Design security for source data access :

• Plan for secure endpoints (private/public)

• Choose the appropriate authentication mechanism, such as access keys, shared access signatures (SAS), and azure active directory (azure ad)

Design security for data policies and standards :

• Design data encryption for data at rest and in transit

• Design for data auditing and data masking

• Design for data privacy and data classification

• Design a data retention policy

• Plan an archiving strategy

• Plan to purge data based on business requirements

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