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NEW QUESTION: 1
A client is being admitted to the labor and delivery unit. She has had previous admissions for "false labor." Which clinical manifestation would be most indicative of true labor?
A. Uterine contractions
B. Progressive dilatation and effacement of the cervix
C. Increased bloody show
D. Decreased discomfort with ambulation
Answer: B
Explanation:
(A) Bloody show is considered a sign of imminent labor, which usually begins in 24-48 hours. An increase in bloody show is an indication that the cervix is changing. (B) Contractions of true labor produce progressive cervical effacement and dilatation. (C) Contractions of false labor may mimic those of true labor. However, the contractions of false labor do not produce progressive effacement and dilatation of the cervix. (D) In true labor, the discomfort is not relieved by ambulation; walking may intensify the discomfort.
NEW QUESTION: 2
Arrange these steps in the order that they occur during an incident fetch.
Answer:
Explanation:
NEW QUESTION: 3
各アプリケーションに推奨するAzureデータストレージソリューションはどれですか? 回答するには、回答エリアで適切なオプションを選択します。
注:それぞれの正しい選択には1ポイントの価値があります。
Answer:
Explanation:
Explanation
Health Review: Azure SQL Database
Scenario: ADatum identifies the following requirements for the Health Review application:
* Ensure that sensitive health data is encrypted at rest and in transit.
* Tag all the sensitive health data in Health Review. The data will be used for auditing.
Health Interface: Azure Cosmos DB
ADatum identifies the following requirements for the Health Interface application:
* Upgrade to a data storage solution that will provide flexible schemas and increased throughput for writing data. Data must be regionally located close to each hospital, and reads must display be the most recent committed version of an item.
* Reduce the amount of time it takes to add data from new hospitals to Health Interface.
* Support a more scalable batch processing solution in Azure.
* Reduce the amount of development effort to rewrite existing SQL queries.
Health Insights: Azure SQL Data Warehouse
Azure SQL Data Warehouse is a cloud-based enterprise data warehouse that leverages massively parallel processing (MPP) to quickly run complex queries across petabytes of data. Use SQL Data Warehouse as a key component of a big data solution.
You can access Azure SQL Data Warehouse (SQL DW) from Databricks using the SQL Data Warehouse connector (referred to as the SQL DW connector), a data source implementation for Apache Spark that uses Azure Blob Storage, and PolyBase in SQL DW to transfer large volumes of data efficiently between a Databricks cluster and a SQL DW instance.
Scenario: ADatum identifies the following requirements for the Health Insights application:
* The new Health Insights application must be built on a massively parallel processing (MPP) architecture that will support the high performance of joins on large fact tables References:
https://docs.databricks.com/data/data-sources/azure/sql-data-warehouse.html