● Describe the relationship between the data lakehouse and the data warehouse.
● Identify the improvement in data quality in the data lakehouse over the data lake.
● Compare and contrast silver and gold tables, which workloads will use a bronze table as a
source, which workloads will use a gold table as a source.
● Identify elements of the Databricks Platform Architecture, such as what is located in the
data plane versus the control plane and what resides in the customer’s cloud account
● Differentiate between all-purpose clusters and jobs clusters.
● Identify how cluster software is versioned using the Databricks Runtime.
● Identify how clusters can be filtered to view those that are accessible by the user.
● Describe how clusters are terminated and the impact of terminating a cluster.
● Identify a scenario in which restarting the cluster will be useful.
● Describe how to use multiple languages within the same notebook.
● Identify how to run one notebook from within another notebook.
● Identify how notebooks can be shared with others.
● Describe how Databricks Repos enables CI/CD workflows in Databricks.
● Identify Git operations available via Databricks Repos.
● Identify limitations in Databricks Notebooks version control functionality relative to Repos.

● Extract data from a single file and from a directory of files
● Identify the prefix included after the FROM keyword as the data type.
● Create a view, a temporary view, and a CTE as a reference to a file
● Identify that tables from external sources are not Delta Lake tables.
● Create a table from a JDBC connection and from an external CSV file
● Identify how the count_if function and the count where x is null can be used
● Identify how the count(row) skips NULL values.
● Deduplicate rows from an existing Delta Lake table.
● Create a new table from an existing table while removing duplicate rows.
● Deduplicate a row based on specific columns.
● Validate that the primary key is unique across all rows.
● Validate that a field is associated with just one unique value in another field.
● Validate that a value is not present in a specific field.
● Cast a column to a timestamp.
● Extract calendar data from a timestamp.
● Extract a specific pattern from an existing string column.
● Utilize the dot syntax to extract nested data fields.
● Identify the benefits of using array functions.
● Parse JSON strings into structs.
● Identify which result will be returned based on a join query.
● Identify a scenario to use the explode function versus the flatten function
● Identify the PIVOT clause as a way to convert data from a long format to a wide format.
● Define a SQL UDF.
● Identify the location of a function.
● Describe the security model for sharing SQL UDFs.
● Use CASE/WHEN in SQL code.
● Leverage CASE/WHEN for custom control flow.

● Identify where Delta Lake provides ACID transactions
● Identify the benefits of ACID transactions.
● Identify whether a transaction is ACID-compliant.
● Compare and contrast data and metadata.
● Compare and contrast managed and external tables.
● Identify a scenario to use an external table.
● Create a managed table.
● Identify the location of a table.
● Inspect the directory structure of Delta Lake files.
● Identify who has written previous versions of a table.
● Review a history of table transactions.
● Roll back a table to a previous version.
● Identify that a table can be rolled back to a previous version.
● Query a specific version of a table.
● Identify why Zordering is beneficial to Delta Lake tables.
● Identify how vacuum commits deletes.
● Identify the kind of files Optimize compacts.
● Identify CTAS as a solution.
● Create a generated column.
● Add a table comment.
● Use CREATE OR REPLACE TABLE and INSERT OVERWRITE
● Compare and contrast CREATE OR REPLACE TABLE and INSERT OVERWRITE
● Identify a scenario in which MERGE should be used.
● Identify MERGE as a command to deduplicate data upon writing.
● Describe the benefits of the MERGE command.
● Identify why a COPY INTO statement is not duplicating data in the target table.
● Identify a scenario in which COPY INTO should be used.
● Use COPY INTO to insert data.
● Identify the components necessary to create a new DLT pipeline.
● Identify the purpose of the target and of the notebook libraries in creating a pipeline.
● Compare and contrast triggered and continuous pipelines in terms of cost and latency
● Identify which source location is utilizing Auto Loader.
● Identify a scenario in which Auto Loader is beneficial.
● Identify why Auto Loader has inferred all data to be STRING from a JSON source
● Identify the default behavior of a constraint violation
● Identify the impact of ON VIOLATION DROP ROW and ON VIOLATION FAIL UPDATEfor a
constraint violation
● Explain change data capture and the behavior of APPLY CHANGES INTO
● Query the events log to get metrics, perform audit loggin, examine lineage.
● Troubleshoot DLT syntax: Identify which notebook in a DLT pipeline produced an error,
identify the need for LIVE in create statement, identify the need for STREAM in from clause.

● Identify the benefits of using multiple tasks in Jobs.
● Set up a predecessor task in Jobs.
● Identify a scenario in which a predecessor task should be set up.
● Review a task’s execution history.
● Identify CRON as a scheduling opportunity.
● Debug a failed task.
● Set up a retry policy in case of failure.
● Create an alert in the case of a failed task.
● Identify that an alert can be sent via email.

● Identify one of the four areas of data governance.
● Compare and contrast metastores and catalogs.
● Identify Unity Catalog securables.
● Define a service principal.
● Identify the cluster security modes compatible with Unity Catalog.
● Create a UC-enabled all-purpose cluster.
● Create a DBSQL warehouse.
● Identify how to query a three-layer namespace.
● Implement data object access control
● Identify colocating metastores with a workspace as best practice.
● Identify using service principals for connections as best practice.
● Identify the segregation of business units across catalog as best practice.