Valuable Databricks Certified Data Engineer Professional Exam Dumps Are Available For Your Preparation

Valuable Databricks Certified Data Engineer Professional Exam Dumps Are Available For Your Preparation

The Databricks Certified Data Engineer Professional certification holders can demonstrate an ability to perform advanced data engineering tasks using Databricks and its capabilities. If you are one who is eager to pass the Databricks Certified Data Engineer Professional exam successfully for the certification, you can choose the valuable exam dumps to prepare for your Databricks Certified Data Engineer Professional exam well. We have collected the Databricks Certified Data Engineer Professional exam dumps questions and answers based on the exam objectives to ensure that you can pass the exam without any difficulties.

Read Databricks Certified Data Engineer Professional Free Dumps Demo Questions Below

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1. There are 5000 different color balls, out of which 1200 are pink color .

What is the maximum likelihood estimate for the proportion of "pink" items in the test set of color balls?

2. )

3. Which of the following data workloads will utilize a Bronze table as its source?

4. Which of the following describes a benefit of a data lakehouse that is unavailable in a traditional data warehouse?

5. Two junior data engineers are authoring separate parts of a single data pipeline notebook. They are working on separate Git branches so they can pair program on the same notebook simultaneously. A senior data engineer experienced in Databricks suggests there is a better alternative for this type of collaboration .

Which of the following supports the senior data engineer's claim?

6. Projecting a multi-dimensional dataset onto which vector has the greatest variance?

7. A data engineer has three notebooks in an ELT pipeline. The notebooks need to be executed in a specific order for the pipeline to complete successfully. The data engineer would like to use Delta Live Tables to manage this process.

Which of the following steps must the data engineer take as part of implementing this pipeline using Delta Live Tables?

8. A data engineering team has created a series of tables using Parquet data stored in an external sys-tem. The team is noticing that after appending new rows to the data in the external system, their queries within Databricks are not returning the new rows. They identify the caching of the previous data as the cause of this issue.

Which of the following approaches will ensure that the data returned by queries is always up-to-date?

9. Question-3: In machine learning, feature hashing, also known as the hashing trick (by analogy to the kernel trick), is a fast and space-efficient way of vectorizing features (such as the words in a language), i.e., turning arbitrary features into indices in a vector or matrix. It works by applying a hash function to the features and using their hash values modulo the number of features as indices directly, rather than looking the indices up in an associative array.

So what is the primary reason of the hashing trick for building classifiers?

10. Which of the following locations hosts the driver and worker nodes of a Databricks-managed clus-ter?


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