Maintaining and improving data quality is a major goal of modern data engineering.
Which of the following contributes directly to high levels of data quality within the Databricks Lakehouse Platform? Select two responses. - ACCURATE ANSWERS schema evolution, Data expectations enforcement
Whic...
Maintaining and improving data quality is a major goal of modern data
engineering.
Which of the following contributes directly to high levels of data quality
within the Databricks Lakehouse Platform? Select two responses. -
ACCURATE ANSWERS✔✔ schema evolution, Data expectations
enforcement
Which of the following describes how the Databricks Lakehouse
Platform makes data governance simpler? Select one response -
, ACCURATE ANSWERS✔✔ Unity Catalog provides a single
governance solution across workload types and clouds.
Data organizations need specialized environments designed specifically
for machine learning workloads.
Which of the following is made available by Databricks as part of
Databricks Machine Learning to support machine learning workloads?
Select four responses. - ACCURATE ANSWERS✔✔ Built-in automated
machine learning development, Support for distributed model training
on big data, Optimized and preconfigured machine learning frameworks,
Built-in real-time model serving
Unity Catalog offers improved Lakehouse data object governance and
organization capabilities for data segregation.
Which of the following is a consequence of using Unity Catalog to
manage, organize and segregate data objects? Select one response. -
ACCURATE ANSWERS✔✔ Databricks SQL
Data sharing has traditionally been performed by proprietary vendor
solutions, SSH File Transfer Protocol (SFTP), or cloud-specific
solutions. However, each of these sharing tools and solutions comes with
its own set of limitations. As a result, Databricks helped to develop the
solution, Delta Sharing.
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