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DP-203 · Question #5

Case Study 1 - Contoso, Ltd Overview Contoso, Ltd. is a clothing retailer based in Seattle. The company has 2,000 retail stores across the United States and an emerging online presence. The network co

The correct answer is CREATE EXTERNAL DATA SOURCE; CREATE EXTERNAL FILE FORMAT; CREATE EXTERNAL TABLE AS SELECT; CREATE EXTERNAL TABLE; CREATE DATABASE SCOPED CREDENTIAL. The correct sequence for setting up PolyBase external tables in Azure Synapse Analytics or SQL Server follows a logical dependency chain. You must first create a DATABASE SCOPED CREDENTIAL to securely store authentication details, then CREATE EXTERNAL DATA SOURCE to define where

Submitted by daniela_cl· Mar 30, 2026Design and Implement Data Storage / Configure external data sources and PolyBase in Azure Synapse Analytics or SQL Server (DP-203 / DP-900 / 70-765)

Question

Case Study 1 - Contoso, Ltd Overview Contoso, Ltd. is a clothing retailer based in Seattle. The company has 2,000 retail stores across the United States and an emerging online presence. The network contains an Active Directory forest named contoso.com. The forest it integrated with an Azure Active Directory (Azure AD) tenant named contoso.com. Contoso has an Azure subscription associated to the contoso.com Azure AD tenant. Existing Environment Transactional Data Contoso has three years of customer, transactional, operational, sourcing, and supplier data comprised of 10 billion records stored across multiple on-premises Microsoft SQL Server servers. The SQL Server instances contain data from various operational systems. The data is loaded into the instances by using SQL Server Integration Services (SSIS) packages. You estimate that combining all product sales transactions into a company-wide sales transactions dataset will result in a single table that contains 5 billion rows, with one row per transaction. Most queries targeting the sales transactions data will be used to identify which products were sold in retail stores and which products were sold online during different time periods. Sales transaction data that is older than three years will be removed monthly. You plan to create a retail store table that will contain the address of each retail store. The table will be approximately 2 MB. Queries for retail store sales will include the retail store addresses. You plan to create a promotional table that will contain a promotion ID. The promotion ID will be associated to a specific product. The product will be identified by a product ID. The table will be approximately 5 GB. Streaming Twitter Data The ecommerce department at Contoso develops an Azure logic app that captures trending Twitter feeds referencing the company's products and pushes the products to Azure Event Hubs. Planned Changes and Requirements Planned Changes Contoso plans to implement the following changes: Load the sales transaction dataset to Azure Synapse Analytics. Integrate on-premises data stores with Azure Synapse Analytics by using SSIS packages. Use Azure Synapse Analytics to analyze Twitter feeds to assess customer sentiments about products. Sales Transaction Dataset Requirements Contoso identifies the following requirements for the sales transaction dataset: Partition data that contains sales transaction records. Partitions must be designed to provide efficient loads by month. Boundary values must belong to the partition on the right. Ensure that queries joining and filtering sales transaction records based on product ID complete as quickly as possible. Implement a surrogate key to account for changes to the retail store addresses. Ensure that data storage costs and performance are predictable. Minimize how long it takes to remove old records. Customer Sentiment Analytics Requirements Contoso identifies the following requirements for customer sentiment analytics: Allow Contoso users to use PolyBase in an Azure Synapse Analytics dedicated SQL pool to query the content of the data records that host the Twitter feeds. Data must be protected by using row-level security (RLS). The users must be authenticated by using their own Azure AD credentials. Maximize the throughput of ingesting Twitter feeds from Event Hubs to Azure Storage without purchasing additional throughput or capacity units. Store Twitter feeds in Azure Storage by using Event Hubs Capture. The feeds will be converted into Parquet files. Ensure that the data store supports Azure AD-based access control down to the object level. Minimize administrative effort to maintain the Twitter feed data records. Purge Twitter feed data records that are older than two years. Data Integration Requirements Contoso identifies the following requirements for data integration: Use an Azure service that leverages the existing SSIS packages to ingest on-premises data into datasets stored in a dedicated SQL pool of Azure Synapse Analytics and transform the data. Identify a process to ensure that changes to the ingestion and transformation activities can be version-controlled and developed independently by multiple data engineers Drag and Drop Question You need to ensure that the Twitter feed data can be analyzed in the dedicated SQL pool. The solution must meet the customer sentiment analytic requirements. Which three Transact-SQL DDL commands should you run in sequence? To answer, move the appropriate commands from the list of commands to the answer area and arrange them in the correct order. NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select. Answer:

Exhibit

DP-203 question #5 exhibit

Answer Area

Drag items

CREATE EXTERNAL DATA SOURCECREATE EXTERNAL FILE FORMATCREATE EXTERNAL TABLECREATE EXTERNAL TABLE AS SELECTCREATE DATABASE SCOPED CREDENTIAL

Correct arrangement

  • CREATE EXTERNAL DATA SOURCE
  • CREATE EXTERNAL FILE FORMAT
  • CREATE EXTERNAL TABLE AS SELECT
  • CREATE EXTERNAL TABLE
  • CREATE DATABASE SCOPED CREDENTIAL

Explanation

The correct sequence for setting up PolyBase external tables in Azure Synapse Analytics or SQL Server follows a logical dependency chain. You must first create a DATABASE SCOPED CREDENTIAL to securely store authentication details, then CREATE EXTERNAL DATA SOURCE to define where the data lives (referencing the credential), then CREATE EXTERNAL FILE FORMAT to define how the data is structured (e.g., delimited text, Parquet), and finally CREATE EXTERNAL TABLE to define the schema mapping to the external data. CREATE EXTERNAL TABLE AS SELECT (CETAS) is used to export/transform data into external storage and would come before CREATE EXTERNAL TABLE in workflows where you are materializing data first before defining a reusable external table over it.

Topics

#PolyBase#Azure Synapse Analytics#External Tables#T-SQL DDL

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