Microsoft DP-203 Practice Test - Questions Answers, Page 17

Box 1: @trigger().startTime

startTime: A date-time value. For basic schedules, the value of the startTime property applies to the first occurrence. For complex schedules, the trigger starts no sooner than the specified startTime value.

Box 2: /{YYYY}/{MM}/{DD}/{HH}_{deviceType}.json

One dataset per hour per deviceType.

Box 3: Flatten hierarchy

- FlattenHierarchy: All files from the source folder are in the first level of the target folder. The target files have autogenerated names.

Reference:

https://docs.microsoft.com/en-us/azure/data-factory/concepts-pipeline-execution-triggers

https://docs.microsoft.com/en-us/azure/data-factory/connector-file-system

Box 1: {YYYY}/{MM}/{DD}/{HH}

Date Format [optional]: if the date token is used in the prefix path, you can select the date format in which your files are organized. Example: YYYY/MM/DD Time Format [optional]: if the time token is used in the prefix path, specify the time format in which your files are organized. Currently the only supported value is HH.

Box 2: {regionID}/raw

Data engineers from each region must be able to build their own pipelines for the data of their respective region only.

Box 3: {deviceID}

Reference:

https://github.com/paolosalvatori/StreamAnalyticsAzureDataLakeStore/blob/master/README.md

Box 1: WHERE EventType='HeartBeat'

Box 2: ,TumblingWindow(Second, 5)

Tumbling windows are a series of fixed-sized, non-overlapping and contiguous time intervals.

The following diagram illustrates a stream with a series of events and how they are mapped into 10-second tumbling windows.

Incorrect Answers:

,SessionWindow.. : Session windows group events that arrive at similar times, filtering out periods of time where there is no data.

Reference:

https://docs.microsoft.com/en-us/stream-analytics-query/session-window-azure-stream-analytics

https://docs.microsoft.com/en-us/stream-analytics-query/tumbling-window-azure-stream-analytics

Explanation:

Box 1: Self-hosted integration runtime

A self-hosted IR is capable of running copy activity between a cloud data stores and a data store in private network.

Box 2: Schedule trigger

Schedule every 8 hours

Box 3: Copy activity

Scenario:

Customer data, including name, contact information, and loyalty number, comes from Salesforce and can be imported into Azure once every eight hours. Row modified dates are not trusted in the source table.

Product data, including product ID, name, and category, comes from Salesforce and can be imported into Azure once every eight hours. Row modified dates are not trusted in the source table.

Guarantee Stream Analytics job reliability during service updates

Part of being a fully managed service is the capability to introduce new service functionality and improvements at a rapid pace. As a result, Stream Analytics can have a service update deploy on a weekly (or more frequent) basis. No matter how much testing is done there is still a risk that an existing, running job may break due to the introduction of a bug. If you are running mission critical jobs, these risks need to be avoided. You can reduce this risk by following Azure's paired region model.

Scenario: The application development team will create an Azure event hub to receive real-time sales data, including store number, date, time, product ID, customer loyalty number, price, and discount amount, from the point of sale (POS) system and output the data to data storage in Azure

Reference:

https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-job-reliability

Virtual network rules are one firewall security feature that controls whether the database server for your single databases and elastic pool in Azure SQL Database or for your databases in SQL Data Warehouse accepts communications that are sent from particular subnets in virtual networks.Server-level, not database-level: Each virtual network rule applies to your whole Azure SQL Database server, not just to one particular database on the server. In other words, virtual network rule applies at the serverlevel, not at the database-level.Reference:https://docs.microsoft.com/en-us/azure/sql-database/sql-database-vnet-service-endpoint-rule- overview

Always Encrypted is a feature designed to protect sensitive data stored in specific database columns from access (for example, credit card numbers, national identification numbers, or data on a need to know basis). This includes database administrators or other privileged users who are authorized to access the database to perform management tasks, but have no business need to access the particular data in the encrypted columns. The data is always encrypted, which means the encrypted data is decrypted only for processing by client applications with access to the encryption key.Reference:https://docs.microsoft.com/en-us/azure/sql-database/sql-database-security-overview

Scenario: Implement a surrogate key to account for changes to the retail store addresses. A surrogate key on a table is a column with a unique identifier for each row. The key is not generated from the table data. Data modelers like to create surrogate keys on their tables when they design data warehouse models. You can use the IDENTITY property to achieve this goal simply and effectively without affecting load performance.

Reference: https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-identity