Microsoft DP-203 Dumps
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Data Engineering on Microsoft Azure (DP-203 Exam)
The Data Engineering on Microsoft Azure (DP-203 Exam) is another exam that tests the candidate’s skills and knowledge regarding Microsoft Azure. The candidates appearing in this exam are expected to have hands-on experience and expertise in integrating, transforming, and consolidating data from numerous structured and unstructured data systems into an analytics solutions-friendly structure. The Azure Data Engineers are responsible for helping stakeholders understanding the data via exploration. They also build and maintain secure data processing pipelines by using various tools and techniques. The Azure Data professionals use numerous Azure data services for storing and producing enhanced datasets for analysis. The candidate for this exam is also expected to have strong knowledge of SQL, Python, etc.
Data Engineering on Microsoft Azure Practice Questions
The most impressive hallmark of Dumpspedia’s DP-203 dumps practice exam questions answers is that they have been prepared by the Microsoft industry experts who have deep exposure of the actual Microsoft Certified: Azure Data Engineer Associate exam requirements. Our experts are also familiar with the Data Engineering on Microsoft Azure exam takers’ requirements.
DP-203 Microsoft Exam Dumps
Once you complete the basic preparation for Data Engineering on Microsoft Azure exam, you need to revise the Microsoft syllabus and make sure that you are able to answer real DP-203 exam questions. For that purpose, We offers you a series of Microsoft Certified: Azure Data Engineer Associate practice tests that are devised on the pattern of the real exam.
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DP-203 PDF vs Testing Engine
Data Engineering on Microsoft Azure Questions and Answers
You have an Azure Databricks workspace and an Azure Data Lake Storage Gen2 account named storage!
New files are uploaded daily to storage1.
• Incrementally process new files as they are upkorage1 as a structured streaming source. The solution must meet the following requirements:
• Minimize implementation and maintenance effort.
• Minimize the cost of processing millions of files.
• Support schema inference and schema drift.
Which should you include in the recommendation?
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 section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are designing an Azure Stream Analytics solution that will analyze Twitter data.
You need to count the tweets in each 10-second window. The solution must ensure that each tweet is counted only once.
Solution: You use a hopping window that uses a hop size of 10 seconds and a window size of 10 seconds.
Does this meet the goal?
You are designing database for an Azure Synapse Analytics dedicated SQL pool to support workloads for detecting ecommerce transaction fraud.
Data will be combined from multiple ecommerce sites and can include sensitive financial information such as credit card numbers.
You need to recommend a solution that meets the following requirements:
- Users must be able to identify potentially fraudulent transactions.
- Users must be able to use credit cards as a potential feature in models.
- Users must NOT be able to access the actual credit card numbers.
What should you include in the recommendation?
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