A junior member of the data engineering team is exploring the language interoperability of Databricks notebooks. The intended outcome of the below code is to register a view of all sales that occurred in countries on the continent of Africa that appear in the geo_lookup table.
Before executing the code, running SHOW TABLES on the current database indicates the database contains only two tables: geo_lookup and sales.

Which statement correctly describes the outcome of executing these command cells in order in an interactive notebook?

• A.Both commands will succeed. Executing show tables will show that countries at and sales at have been registered as views.
• B.Cmd 1 will succeed. Cmd 2 will search all accessible databases for a table or view named countries af: if this entity exists, Cmd 2 will succeed.
• C.Cmd 1 will succeed and Cmd 2 will fail, countries at will be a Python variable representing a PySpark DataFrame.
• D.Both commands will fail. No new variables, tables, or views will be created.
• E.Cmd 1 will succeed and Cmd 2 will fail, countries at will be a Python variable containing a list of strings.

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A table in the Lakehouse namedcustomer_churn_paramsis used in churn prediction by the machine learning team. The table contains information about customers derived from a number of upstream sources. Currently, the data engineering team populates this table nightly by overwriting the table with the current valid values derived from upstream data sources.
The churn prediction model used by the ML team is fairly stable in production. The team is only interested in making predictions on records that have changed in the past 24 hours.
Which approach would simplify the identification of these changed records?

• A.Apply the churn model to all rows in the customer_churn_params table, but implement logic to perform an upsert into the predictions table that ignores rows where predictions have not changed.
• B.Convert the batch job to a Structured Streaming job using the complete output mode; configure a Structured Streaming job to read from the customer_churn_params table and incrementally predict against the churn model.
• C.Calculate the difference between the previous model predictions and the current customer_churn_params on a key identifying unique customers before making new predictions; only make predictions on those customers not in the previous predictions.
• D.Modify the overwrite logic to include a field populated by calling
  spark.sql.functions.current_timestamp() as data are being written; use this field to identify records written on a particular date.
• E.Replace the current overwrite logic with a merge statement to modify only those records that have changed; write logic to make predictions on the changed records identified by the change data feed.

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What is the main difference between the silver layer and gold layer in medallion architecture?

• A.Silver optimized to perform ETL, Gold is optimized query performance
• B.Gold is optimized go perform ETL, Silver is optimized for query performance
• C.Silver is copy of Bronze, Gold is a copy of Silver
• D.Silver is stored in Delta Lake, Gold is stored in memory
• E.Silver may contain aggregated data, gold may preserve the granularity of original data

Correct Answer: A

Explanation
Medallion Architecture - Databricks
Gold Layer:
1. Powers Ml applications, reporting, dashboards, ad hoc analytics
2. Refined views of data, typically with aggregations
3. Reduces strain on production systems
4. Optimizes query performance for business-critical data
Exam focus: Please review the below image and understand the role of each layer(bronze, silver, gold) in medallion architecture, you will see varying questions targeting each layer and its purpose.
Sorry I had to add the watermark some people in Udemy are copying my content.
A diagram of a house Description automatically generated with low confidence

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The data architect has mandated that all tables in the Lakehouse should be configured as external Delta Lake tables.
Which approach will ensure that this requirement is met?

• A.Whenever a database is being created, make sure that the location keyword is used
• B.When configuring an external data warehouse for all table storage. leverage Databricks for all ELT.
• C.Whenever a table is being created, make sure that the location keyword is used.
• D.When tables are created, make sure that the external keyword is used in the create table statement.
• E.When the workspace is being configured, make sure that external cloud object storage has been mounted.

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Kevin is the owner of the schema sales, Steve wanted to create new table in sales schema called regional_sales so Kevin grants the create table permissions to Steve. Steve creates the new table called regional_sales in sales schema, who is the owner of the table regional_sales

• A.Kevin is the owner of sales schema, all the tables in the schema will be owned by Kevin
• B.Steve is the owner of the table
• C.By default ownership is assigned DBO
• D.By default ownership is assigned to DEFAULT_OWNER
• E.Kevin and Smith both are owners of table

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