Free Access to Microsoft.DP-203.v2023-08-29.q209 with Valid Practice Test (Page 37)

Question 176

You need to design an analytical storage solution for the transactional data. The solution must meet the sales transaction dataset requirements.
What should you include in the solution? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Question 177

You have an Azure Synapse Analytics dedicated SQL pool named pool1.
You plan to implement a star schema in pool1 and create a new table named DimCustomer by using the following code.

You need to ensure that DimCustomer has the necessary columns to support a Type 2 slowly changing dimension (SCD). Which two columns should you add? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

A.[HistoricalSalesPerson] [nvarchar] (256) NOT NULL
B.[EffectiveEndDate] [datetime] NOT NULL
C.[PreviousModifiedDate] [datetime] NOT NULL
D.[RowID] [bigint] NOT NULL
E.[EffectiveStartDate] [datetime] NOT NULL

Correct Answer: A,B

Topic 1, Litware, inc.
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Overview
Litware, Inc. owns and operates 300 convenience stores across the US. The company sells a variety of packaged foods and drinks, as well as a variety of prepared foods, such as sandwiches and pizzas.
Litware has a loyalty club whereby members can get daily discounts on specific items by providing their membership number at checkout.
Litware employs business analysts who prefer to analyze data by using Microsoft Power BI, and data scientists who prefer analyzing data in Azure Databricks notebooks.
Requirements
Business Goals
Litware wants to create a new analytics environment in Azure to meet the following requirements:
See inventory levels across the stores. Data must be updated as close to real time as possible.
Execute ad hoc analytical queries on historical data to identify whether the loyalty club discounts increase sales of the discounted products.
Every four hours, notify store employees about how many prepared food items to produce based on historical demand from the sales data.
Technical Requirements
Litware identifies the following technical requirements:
Minimize the number of different Azure services needed to achieve the business goals.
Use platform as a service (PaaS) offerings whenever possible and avoid having to provision virtual machines that must be managed by Litware.
Ensure that the analytical data store is accessible only to the company's on-premises network and Azure services.
Use Azure Active Directory (Azure AD) authentication whenever possible.
Use the principle of least privilege when designing security.
Stage Inventory data in Azure Data Lake Storage Gen2 before loading the data into the analytical data store. Litware wants to remove transient data from Data Lake Storage once the data is no longer in use. Files that have a modified date that is older than 14 days must be removed.
Limit the business analysts' access to customer contact information, such as phone numbers, because this type of data is not analytically relevant.
Ensure that you can quickly restore a copy of the analytical data store within one hour in the event of corruption or accidental deletion.
Planned Environment
Litware plans to implement the following environment:
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.
Customer data, including name, contact information, and loyalty number, comes from Salesforce, a SaaS application, 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.
Daily inventory data comes from a Microsoft SQL server located on a private network.
Litware currently has 5 TB of historical sales data and 100 GB of customer data. The company expects approximately 100 GB of new data per month for the next year.
Litware will build a custom application named FoodPrep to provide store employees with the calculation results of how many prepared food items to produce every four hours.
Litware does not plan to implement Azure ExpressRoute or a VPN between the on-premises network and Azure.

Question 178

You are designing a data mart for the human resources (MR) department at your company. The data mart will contain information and employee transactions. From a source system you have a flat extract that has the following fields:
* EmployeeID
* FirstName
* LastName
* Recipient
* GrossArnount
* TransactionID
* GovernmentID
* NetAmountPaid
* TransactionDate
You need to design a start schema data model in an Azure Synapse analytics dedicated SQL pool for the data mart.
Which two tables should you create? Each Correct answer present part of the solution.

A.a dimension table for employee
B.a fabric for Employee
C.a dimension table far EmployeeTransaction
D.a dimension table for Transaction
E.a fact table for Transaction

Question 179

You are building a database in an Azure Synapse Analytics serverless SQL pool.
You have data stored in Parquet files in an Azure Data Lake Storege Gen2 container.
Records are structured as shown in the following sample.
{
"id": 123,
"address_housenumber": "19c",
"address_line": "Memory Lane",
"applicant1_name": "Jane",
"applicant2_name": "Dev"
}
The records contain two applicants at most.
You need to build a table that includes only the address fields.
How should you complete the Transact-SQL statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Question 180

You use Azure Data Factory to prepare data to be queried by Azure Synapse Analytics serverless SQL pools.
Files are initially ingested into an Azure Data Lake Storage Gen2 account as 10 small JSON files. Each file contains the same data attributes and data from a subsidiary of your company.
You need to move the files to a different folder and transform the data to meet the following requirements:
Provide the fastest possible query times.
Automatically infer the schema from the underlying files.
How should you configure the Data Factory copy activity? To answer, select the appropriate options in the answer are a.
NOTE: Each correct selection is worth one point.

Question 176

Question 177

Question 178

Question 179

Question 180

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