Which masking functions should you implement for each column to meet the data masking requirements? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

You are a data engineer implementing a lambda architecture on Microsoft Azure. You use an open-source big data solution to collect, process, and maintain data. The analytical data store performs poorly.
You must implement a solution that meets the following requirements:
* Provide data warehousing
* Reduce ongoing management activities
* Deliver SQL query responses in less than one second
You need to create an HDInsight cluster to meet the requirements.
Which type of cluster should you create?

You are a data engineer. You are designing a Hadoop Distributed File System (HDFS) architecture. You plan to use Microsoft Azure Data Lake as a data storage repository.
You must provision the repository with a resilient data schema. You need to ensure the resiliency of the Azure Data Lake Storage. What should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

You have an Azure data factory that has two pipelines named PipelineA and PipelineB.
PipelineA has four activities as shown in the following exhibit.

PipelineB has two activities as shown in the following exhibit.

You create an alert for the data factory that uses Failed pipeline runs metrics for both pipelines and all failure types. The metric has the following settings:
Operator: Greater than
Aggregation type: Total
Threshold value: 2
Aggregation granularity (Period): 5 minutes
Frequency of evaluation: Every 5 minutes
Data Factory monitoring records the failures shown in the following table.

For each of the following statements, select yes if the statement is true. Otherwise, select no.
NOTE: Each correct answer selection is worth one point.

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this scenario, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You plan to create an Azure Databricks workspace that has a tiered structure. The workspace will contain the following three workloads:
A workload for data engineers who will use Python and SQL
A workload for jobs that will run notebooks that use Python, Spark, Scala, and SQL A workload that data scientists will use to perform ad hoc analysis in Scala and R The enterprise architecture team at your company identifies the following standards for Databricks environments:
The data engineers must share a cluster.
The job cluster will be managed by using a request process whereby data scientists and data engineers provide packaged notebooks for deployment to the cluster.
All the data scientists must be assigned their own cluster that terminates automatically after 120 minutes of inactivity. Currently, there are three data scientists.
You need to create the Databrick clusters for the workloads.
Solution: You create a Standard cluster for each data scientist, a Standard cluster for the data engineers, and a High Concurrency cluster for the jobs.
Does this meet the goal?