Online Access Free 070-775 Exam Questions
| Exam Code: | 070-775 |
| Exam Name: | Perform Data Engineering on Microsoft Azure HDInsight |
| Certification Provider: | Microsoft |
| Free Question Number: | 63 |
| Posted: | Sep 04, 2026 |
DRAG DROP
You have an Apache HBase cluster in Azure HDInsight. The cluster has a table named sales that contains a column family named customerfamily.
You need to add a new column family named customeraddr to the sales table.
How should you complete the command? To answer, drag the appropriate values to the correct targets.
Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
You have several Linux-based and Windows-based Azure HDInsight clusters. The clusters are indifferent Active Directory domains.
You need to consolidate system logging for all of the clusters into a single location. The solution must provide near real-time analytics of the log dat a.
What should you use?
You have an Apache Spark cluster in Azure HDInsight.
Users report that Spark jobs take longer than expected to complete.
You need to reduce the amount of time it takes for the Spark jobs to complete.
What should you do?
DRAG DROP
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You have an initial dataset that contains the crime data from major cities.
You plan to build training models from the training dat
a. You plan to automate the process of adding more data to the training models and to constantly tune the models by using the additional data, including data that is collected in near real-time. The system will be used to analyze event data gathered from many different sources, such as Internet of Things (IoT) devices, live video surveillance, and traffic activities, and to generate predictions of an increased crime risk at a particular time and place.
You have an incoming data stream from Twitter and an incoming data stream from Facebook, which are event-based only, rather than time-based. You also have a time interval stream every 10 seconds.
The data is in a key/value pair format. The value field represents a number that defines how many times a hashtag occurs within a Facebook post, or how many times a Tweet that contains a specific hashtag is retweeted.
You must use the appropriate data storage, stream analytics techniques, and Azure HDInsight cluster types for the various tasks associated to the processing pipeline.
You use Spark Streaming for the real-time ingestion of Twitter feeds.
You need to apply transformation functions to the incoming data.
Which transformation function should you use for each use case? To answer, drag the appropriate functions to the correct cases. Each function may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You have an initial dataset that contains the crime data from major cities.
You plan to build training models from the training dat
a. You plan to automate the process of adding more data to the training models and to constantly tune the models by using the additional data, including data that is collected in near real-time. The system will be used to analyze event data gathered from many different sources, such as Internet of Things (IoT) devices, live video surveillance, and traffic activities, and to generate predictions of an increased crime risk at a particular time and place.
You have an incoming data stream from Twitter and an incoming data stream from Facebook, which are event-based only, rather than time-based. You also have a time interval stream every 10 seconds.
The data is in a key/value pair format. The value field represents a number that defines how many times a hashtag occurs within a Facebook post, or how many times a Tweet that contains a specific hashtag is retweeted.
You must use the appropriate data storage, stream analytics techniques, and Azure HDInsight cluster types for the various tasks associated to the processing pipeline.
You are planning a storage strategy for a large amount of analytic data used for the crime data analytics system. The initial data load involves over 100 billion records, and more than two billion records will be added daily.
You already created an Apache Hadoop cluster in HDInsight premium.
You need to implement the storage strategy to meet the following requirements:
The storage capacity must support 50 TB.
The storage must be optimized for Hadoop.
The data must be stored in its native format.
Enterprise-level security based on Active Directory must be supported.
What should you create?