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The GAQM Databricks-Certified-Data-Engineer-Associate (Databricks Certified Data Engineer Associate) Certification Exam is a comprehensive examination that tests the skills of professionals who work with data on the Databricks platform. Databricks Certified Data Engineer Associate Exam certification is designed to help professionals stay up-to-date with the latest data engineering trends and technologies, and it can help professionals advance their career in the field of data engineering. By earning this certification, professionals can demonstrate their commitment to professional development and their dedication to staying current in their field.
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The GAQM Databricks-Certified-Data-Engineer-Associate (Databricks Certified Data Engineer Associate) Certification Exam is designed to validate the skills and knowledge of data engineers who work with the Databricks Unified Analytics Platform. Databricks Certified Data Engineer Associate Exam certification is ideal for professionals who want to demonstrate their expertise in building and optimizing data pipelines, data transformation, and data storage using Databricks.
NEW QUESTION # 268
A data engineer and data analyst are working together on a data pipeline. The data engineer is working on the raw, bronze, and silver layers of the pipeline using Python, and the data analyst is working on the gold layer of the pipeline using SQL. The raw source of the pipeline is a streaming input. They now want to migrate their pipeline to use Delta Live Tables.
Which of the following changes will need to be made to the pipeline when migrating to Delta Live Tables?
Answer: E
Explanation:
Delta Live Tables is a declarative framework for building reliable, maintainable, and testable data processing pipelines. You define the transformations to perform on your data and Delta Live Tables manages task orchestration, cluster management, monitoring, data quality, and error handling. Delta Live Tables supports both SQL and Python as the languages for defining your datasets and expectations. Delta Live Tables also supports both streaming and batch sources, and can handle both append-only and upsert data patterns. Delta Live Tables follows the medallion lakehouse architecture, which consists of three layers of data: bronze, silver, and gold. Therefore, migrating to Delta Live Tables does not require any of the changes listed in the options B, C, D, or E. The data engineer and data analyst can use the same languages, sources, and architecture as before, and simply declare their datasets and expectations using Delta Live Tables syntax. References:
* What is Delta Live Tables?
* Transform data with Delta Live Tables
* What is the medallion lakehouse architecture?
NEW QUESTION # 269
A data engineer has configured a Structured Streaming job to read from a table, manipulate the data, and then perform a streaming write into a new table.
The code block used by the data engineer is below:
If the data engineer only wants the query to process all of the available data in as many batches as required, which of the following lines of code should the data engineer use to fill in the blank?
Answer: A
Explanation:
https://spark.apache.org/docs/latest/api/python/reference/pyspark.ss/api/pyspark.sql.streaming.DataStreamWriter
NEW QUESTION # 270
Which of the following SQL keywords can be used to convert a table from a long format to a wide format?
Answer: B
Explanation:
The SQL keyword that can be used to convert a table from a long format to a wide format is PIVOT. The PIVOT clause is used to rotate the rows of a table into columns of a new table1. The PIVOT clause can aggregate the values of a column based on the distinct values of another column, and use those values as the column names of the new table1. The PIVOT clause can be useful for transforming data from a long format, where each row represents an observation with multiple attributes, to a wide format, where each row represents an observation with a single attribute and multiple values2. For example, the PIVOT clause can be used to convert a table that contains the sales of different products by different regions into a table that contains the sales of each product by each region as separate columns1.
The other options are not suitable for converting a table from a long format to a wide format. CONVERT is a function that can be used to change the data type of an expression3. WHERE is a clause that can be used to filter the rows of a table based on a condition4. TRANSFORM is a keyword that can be used to apply a user- defined function to a group of rows in a table5. SUM is a function that can be used to calculate the total of a numeric column.
:
1: PIVOT | Databricks on AWS
2: Reshaping Data - Long vs Wide Format | Databricks on AWS
3: CONVERT | Databricks on AWS
4: WHERE | Databricks on AWS
5: TRANSFORM | Databricks on AWS
6: [SUM | Databricks on AWS]
NEW QUESTION # 271
A data engineering team is building a new data-transformation notebook. During development, the engineers need fast testing, quick code changes, and easy debugging. Later, the notebook will run nightly as a scheduled job without human intervention. The team wants to optimize for development speed.
Which compute should the team use during development?
Answer: C
NEW QUESTION # 272
Which of the following describes the relationship between Gold tables and Silver tables?
Answer: D
Explanation:
According to the medallion lakehouse architecture, gold tables are the final layer of data that powers analytics, machine learning, and production applications. They are often highly refined and aggregated, containing data that has been transformed into knowledge, rather than just information. Silver tables, on the other hand, are the intermediate layer of data that represents a validated, enriched version of the raw data from the bronze layer.
They provide an enterprise view of all its key business entities, concepts and transactions, but they may not have all the aggregations and calculations that are required for specific use cases. Therefore, gold tables are more likely to contain aggregations than silver tables. References:
* What is the medallion lakehouse architecture?
* What is a Medallion Architecture?
NEW QUESTION # 273
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