You are planning a streaming data solution that will use Azure Databricks. The solution will stream sales transaction data from an online store. The solution has the following specifications:-The output data will contain items purchased, quantity, line total sales amount, and line total tax amount. -Line total sales amount and line total tax amount will be aggregated in Databricks.-Sales transactions will never be updated. Instead, new rows will be added to adjust a sale.You need to recommend an output mode for the dataset that will be processed by using Structured Streaming. The solution must minimize duplicate data.What should you recommend?
Answer(s): C
You have an enterprise data warehouse in Azure Synapse Analytics named DW1 on a server named Server1. You need to determine the size of the transaction log file for each distribution of DW1.What should you do?
Answer(s): D
You are designing an anomaly detection solution for streaming data from an Azure IoT hub. The solution must meet the following requirements:Send the output to Azure Synapse.Identify spikes and dips in time series data. Minimize development and configuration effort. Which should you include in the solution?
Answer(s): B
You can identify anomalies by routing data via IoT Hub to a built-in ML model in Azure Stream Analytics.
https://docs.microsoft.com/en-us/learn/modules/data-anomaly-detection-using-azure-iot-hub/
A company uses Azure Stream Analytics to monitor devices.The company plans to double the number of devices that are monitored.You need to monitor a Stream Analytics job to ensure that there are enough processing resources to handle the additional load.Which metric should you monitor?
There are a number of resource constraints that can cause the streaming pipeline to slow down. The watermark delay metric can rise due to:Not enough processing resources in Stream Analytics to handle the volume of input events. Not enough throughput within the input event brokers, so they are throttled.Output sinks are not provisioned with enough capacity, so they are throttled. The possible solutions vary widely based on the flavor of output service being used.Incorrect Answers:A: Deserialization issues are caused when the input stream of your Stream Analytics job contains malformed messages.
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-time-handling
HOTSPOT (Drag and Drop is not supported)You are designing an enterprise data warehouse in Azure Synapse Analytics that will store website traffic analytics in a star schema.You plan to have a fact table for website visits. The table will be approximately 5 GB.You need to recommend which distribution type and index type to use for the table. The solution must provide the fastest query performance.What should you recommend? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.Hot Area:
Answer(s): A
Box 1: HashConsider using a hash-distributed table when:The table size on disk is more than 2 GB.The table has frequent insert, update, and delete operations. Box 2: Clustered columnstoreClustered columnstore tables offer both the highest level of data compression and the best overall query performance.
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tablesdistributehttps://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tablesindex
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