Your team member is trying to set up a delta pipeline and build a second gold table to the same pipeline with aggregated metrics based on an existing Delta Live table called sales_orders_cleaned but he is facing a problem in starting the pipeline, the pipeline is failing to state it cannot find the table sales_orders_cleaned, you are asked to identify and fix the problem.
1.CREATE LIVE TABLE sales_order_in_chicago
2.AS
3.SELECT order_date, city, sum(price) as sales,
4.FROM sales_orders_cleaned
5.WHERE city = 'Chicago')
6.GROUP BY order_date, city

• A.Use STREAMING LIVE instead of LIVE table
• B.Delta live table can be used in a group by clause
• C.Delta live tables pipeline can only have one table
• D.Sales_orders_cleaned table is missing schema name LIVE
• E.The pipeline needs to be deployed so the first table is created before we add a second table

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Drop the customers database and associated tables and data, all of the tables inside the database are managed tables. Which of the following SQL commands will help you accomplish this?

• A.DROP DATABASE customers FORCE
• B.DROP DATABASE customers CASCADE
• C.DROP DATABASE customers INCLUDE
• D.All the tables must be dropped first before dropping database
• E.DROP DELTA DATABSE customers

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Which of the following describes a scenario in which a data engineer will want to use a Job cluster instead of
an all-purpose cluster?

• A.An ad-hoc analytics report needs to be developed while minimizing compute costs
• B.A Databricks SQL query needs to be scheduled for upward reporting
• C.An automated workflow needs to be run every 30 minutes
• D.A data engineer needs to manually investigate a production error
• E.A data team needs to collaborate on the development of a machine learning model

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Which of the following are stored in the control pane of Databricks Architecture?

• A.Job Clusters
• B.All Purpose Clusters
• C.Databricks Filesystem
• D.Databricks Web Application
• E.Delta tables

Correct Answer: D

Explanation
The answer is Databricks Web Application
Azure Databricks architecture overview - Azure Databricks | Microsoft Docs Databricks operates most of its services out of a control plane and a data plane, please note serverless features like SQL Endpoint and DLT compute use shared compute in Control pane.
Control Plane: Stored in Databricks Cloud Account
* The control plane includes the backend services that Databricks manages in its own Azure account.
Notebook commands and many other workspace configurations are stored in the control plane and encrypted at rest.
Data Plane: Stored in Customer Cloud Account
* The data plane is managed by your Azure account and is where your data resides. This is also where data is processed. You can use Azure Databricks connectors so that your clusters can connect to external data sources outside of your Azure account to ingest data or for storage.
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The team has decided to take advantage of table properties to identify a business owner for each table, which of the following table DDL syntax allows you to populate a table property identifying the business owner of a table CREATE TABLE inventory (id INT, units FLOAT)

• A.SET TBLPROPERTIES business_owner = 'supply chain'
  CREATE TABLE inventory (id INT, units FLOAT)
• B.TBLPROPERTIES (business_owner = 'supply chain')
• C.CREATE TABLE inventory (id INT, units FLOAT)
  SET (business_owner = 'supply chain')
• D.CREATE TABLE inventory (id INT, units FLOAT)
  SET PROPERTY (business_owner = 'supply chain')
• E.CREATE TABLE inventory (id INT, units FLOAT)
  SET TAG (business_owner = 'supply chain')

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