Exam Certified Data Engineer Associate topic 1 question 25 discussion

The answer is incorrect. The correct answer is Delta Live Tables or (C) https://docs.databricks.com/delta-live-tables/expectations.html

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. Quality is explicitly mentioned in the definition.

The response is D

Delta Live Tables (DLT) is designed for building and managing data pipelines with built-in support for data quality monitoring and enforcement. It allows data engineers to define expectations (data quality rules) and automatically track if the ingested data meets these expectations. If data fails the specified rules, DLT can log the errors and either reject or quarantine the data, depending on the configured behavior.

D. Delta Live Tables Delta Live Tables provides features for automating data quality monitoring and ensuring that the data in the pipeline meets certain quality standards. It allows you to define expectations and monitor data quality as part of the data pipeline.

delta live table

Correct is D

Correct: D

D is correct

D. Delta Live Tables Delta Live Tables is a tool provided by Databricks that can help data engineers automate the monitoring of data quality. It is designed for managing data pipelines, monitoring data quality, and automating workflows. With Delta Live Tables, you can set up data quality checks and alerts to detect issues and anomalies in your data as it is ingested and processed in real-time. It provides a way to ensure that the data quality meets your desired standards and can trigger actions or notifications when issues are detected. While the other tools mentioned may have their own purposes in a data engineering environment, Delta Live Tables is specifically designed for data quality monitoring and automation within the Databricks ecosystem.

D Delta Live Tables. Delta Live Tables is a tool that can be used to automate the process of monitoring the quality level of data in a data pipeline. Delta Live Tables provides a number of features that can be used to monitor data quality, including: Data lineage: Delta Live Tables tracks the lineage of data as it flows through the data pipeline. This allows the data engineer to see where the data came from and how it has been transformed. Data quality checks: Delta Live Tables allows the data engineer to define data quality checks that can be run on the data as it is ingested. These checks can be used to identify data that is not meeting the expected quality standards. Alerts: Delta Live Tables can be configured to send alerts when data quality checks fail. This allows the data engineer to be notified of potential problems with the data pipeline.

The data engineer can use the Data Explorer tool to monitor the quality level of the ingested data. Data Explorer is a feature of Databricks that provides data profiling and data quality metrics to monitor the health of data pipelines.

B. Data Explorer can be used to monitor the quality level of data. It provides an interactive interface to analyze the data and define quality rules to identify issues. Data Explorer also offers automated validation rules that can be used to monitor data quality over time.