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1. A data engineer has written the following query:

1 SELECT *

2 FROM json.`/path/to/json/file.json`;

The data engineer asks a colleague for help to convert this query for use in a Delta Live Tables (DLT) pipeline. The query should create the first table in the DLT pipeline.

Which of the following describes the change the colleague needs to make to the query?

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

3. Which of the following statements describes Delta Lake?

4. 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?

5. You are working on a email spam filtering assignment, while working on this you find there is new word e.g. HadoopExam comes in email, and in your solutions you never come across this word before, hence probability of this words is coming in either email could be zero.

So which of the following algorithm can help you to avoid zero probability?

6. 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?

7. A data engineer has created a Delta table as part of a data pipeline. Downstream data analysts now need SELECT permission on the Delta table.

Assuming the data engineer is the Delta table owner, which part of the Databricks Lakehouse Plat-form can the data engineer use to grant the data analysts the appropriate access?

8. FROM raw_table;

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

10. 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?


 

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