Microsoft Designing an Azure Data Solution Set 2

You are designing a big data storage solution. The solution must meet the following requirements: Provide unlimited account sizes. Support a hierarchical file system. Be optimized for parallel analytics workloads. Which storage solution should you use?

You plan to store 100 GB of data used by a line-of-business (LOB) app. You need to recommend a data storage solution for the data. The solution must meet the following requirements: Minimize storage costs. Natively support relational queries. Provide a recovery time objective (RTO) of less than one minute. What should you include in the recommendation?

You are designing a data storage solution for a database that is expected to grow to 50 TB. The usage pattern is singleton inserts, singleton updates, and reporting. Which storage solution should you use?

You need to design the runtime environment for the Real Time Response system. What should you recommend?

You need to optimize storage for CONT_SQL3. What should you recommend?

What should you recommend as a batch processing solution for Health Interface?

Inventory levels must be calculated by subtracting the current day's sales from the previous day's final inventory. Which two options provide Litware with the ability to quickly calculate the current inventory levels by store and product? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.

You are designing an enterprise data warehouse in Azure Synapse Analytics. You plan to load millions of rows of data into the data warehouse each day. You must ensure that staging tables are optimized for data loading. You need to design the staging tables. What type of tables should you recommend?

A company has an application that uses Azure SQL Database as the data store. The application experiences a large increase in activity during the last month of each year. You need to manually scale the Azure SQL Database instance to account for the increase in data write operations. Which scaling method should you recommend?

You are designing an Azure Data Factory pipeline for processing data. The pipeline will process data that is stored in general-purpose standard Azure storage. You need to ensure that the compute environment is created on-demand and removed when the process is completed. Which type of activity should you recommend?