Data engineering team has a job currently setup to run a task load data into a reporting table every day at 8: 00 AM takes about 20 mins, Operations teams are planning to use that data to run a second job, so they access latest complete set of data. What is the best to way to orchestrate this job setup?

• A.Add Operation reporting task in the same job and set the Data Engineering task to de-pend on Operations reporting task
• B.Setup a second job to run at 8:20 AM in the same workspace
• C.Add Operation reporting task in the same job and set the operations reporting task to depend on Data Engineering task
• D.Use Auto Loader to run every 20 mins to read the initial table and set the trigger to once and create a second job
• E.Setup a Delta live to table based on the first table, set the job to run in continuous mode

Correct Answer: C

Explanation
The answer is Add Operation reporting task in the same job and set the operations reporting task to depend on Data Engineering task.

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The sales team has asked the Data engineering team to develop a dashboard that shows sales per-formance for all stores, but the sales team would like to use the dashboard but would like to select individual store location, which of the following approaches Data Engineering team can use to build this functionality into the dashboard.

• A.Use query Parameters which then allow user to choose any location
• B.Currently dashboards do not support parameters
• C.Use Databricks REST API to create a dashboard for each location
• D.Use SQL UDF function to filter the data based on the location
• E.Use Dynamic views to filter the data based on the location

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A data engineer wants to create a relational object by pulling data from two tables. The relational object must
be used by other data engineers in other sessions. In order to save on storage costs, the data engineer wants to
avoid copying and storing physical data.
Which of the following relational objects should the data engineer create?

• A.Spark SQL Table
• B.Delta Table
• C.Temporary view
• D.View
• E.Database

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A junior developer complains that the code in their notebook isn't producing the correct results in the development environment. A shared screenshot reveals that while they're using a notebook versioned with Databricks Repos, they're using a personal branch that contains old logic. The desired branch nameddev-2.3.9is not available from the branch selection dropdown.
Which approach will allow this developer to review the current logic for this notebook?

• A.Use Repos to make a pull request use the Databricks REST API to update the current branch to dev-2.3.9
• B.Use Repos to pull changes from the remote Git repository and select the dev-2.3.9 branch.
• C.Use Repos to checkout the dev-2.3.9 branch and auto-resolve conflicts with the current branch
• D.Merge all changes back to the main branch in the remote Git repository and clone the repo again
• E.Use Repos to merge the current branch and the dev-2.3.9 branch, then make a pull request to sync with the remote repository

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Which of the following locations in the Databricks product architecture hosts the notebooks and jobs?

• A.Data plane
• B.Control plane
• C.Databricks Filesystem
• D.JDBC data source
• E.Databricks web application

Correct Answer: B

Explanation
The answer is Control Pane,
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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