Free Udemy Course: Practice Exams | Azure DP-420 Desgn & Implmt Cloud w/COSMOS

In order to set realistic expectations, please note: These questions are NOT official questions that you will find on the official exam. These questions DO cover all the material outlined in the knowledge sections below. Many of the questions are based on fictitious scenarios which have questions posed within them.The official knowledge requirements for the exam are reviewed routinely to ensure that the content has the latest requirements incorporated in the practice questions. Updates to content are often made without prior notification and are subject to change at any time.Each question has a detailed explanation and links to reference materials to support the answers which ensures accuracy of the problem solutions.The questions will be shuffled each time you repeat the tests so you will need to know why an answer is correct, not just that the correct answer was item "B"  last time you went through the test.NOTE: This course should not be your only study material to prepare for the official exam. These practice tests are meant to supplement topic study material.Should you encounter content which needs attention, please send a message with a screenshot of the content that needs attention and I will be reviewed promptly. Providing the test and question number do not identify questions as the questions rotate each time they are run. The question numbers are different for everyone.As a candidate for this exam, you should have subject matter expertise designing, implementing, and monitoring cloud-native applications that store and manage data.Your responsibilities for this role include:Designing and implementing data models and data distribution.Loading data into an Azure Cosmos DB database.Optimizing and maintaining the solution.As a professional in this role, you integrate the solution with other Azure services. You also design, implement, and monitor solutions that consider security, availability, resilience, and performance requirements.As a candidate for this exam, you must have solid knowledge and experience with:Developing apps for Azure.Working with Azure Cosmos DB database technologies.Creating server-side objects with JavaScript.You should be proficient at developing applications that use the Azure Cosmos DB for NoSQL API. You should be able to:Write efficient SQL queries for the API.Create appropriate indexing policies.Interpret JSON.Read C# or Java code.Use PowerShell.Additionally, you should be familiar with provisioning and managing resources in Azure.Skills at a glanceDesign and implement data models (35–40%)Design and implement data distribution (5–10%)Integrate an Azure Cosmos DB solution (5–10%)Optimize an Azure Cosmos DB solution (15–20%)Maintain an Azure Cosmos DB solution (25–30%)Design and implement data models (35–40%)Design and implement a non-relational data model for Azure Cosmos DB for NoSQLDevelop a design by storing multiple entity types in the same containerDevelop a design by storing multiple related entities in the same documentDevelop a model that denormalizes data across documentsDevelop a design by referencing between documentsIdentify primary and unique keysIdentify data and associated access patternsSpecify a default time to live (TTL) on a container for a transactional storeDesign a data partitioning strategy for Azure Cosmos DB for NoSQLChoose a partitioning strategy based on a specific workloadChoose a partition keyPlan for transactions when choosing a partition keyEvaluate the cost of using a cross-partition queryCalculate and evaluate data distribution based on partition key selectionCalculate and evaluate throughput distribution based on partition key selectionConstruct and implement a synthetic partition keyDesign and implement a hierarchical partition keyDesign partitioning for workloads that require multiple partition keysPlan and implement sizing and scaling for a database created with Azure Cosmos DBEvaluate the throughput and data storage requirements for a specific workloadChoose between serverless and provisioned modelsChoose when to use database-level provisioned throughputDesign for granular scale units and resource governanceEvaluate the cost of the global distribution of dataConfigure throughput for Azure Cosmos DB by using the Azure portalImplement client connectivity options in the Azure Cosmos DB SDKChoose a connectivity mode (gateway versus direct)Implement a connectivity modeCreate a connection to a databaseEnable offline development by using the Azure Cosmos DB emulatorHandle connection errorsImplement a singleton for the clientSpecify a region for global distributionConfigure client-side threading and parallelism optionsEnable SDK loggingImplement data access by using the SQL language for Azure Cosmos DB for NoSQLImplement queries that use arrays, nested objects, aggregation, and orderingImplement a correlated subqueryImplement queries that use array and type-checking functionsImplement queries that use mathematical, string, and date functionsImplement queries based on variable dataImplement data access by using Azure Cosmos DB for NoSQL SDKsChoose when to use a point operation versus a query operationImplement a point operation that creates, updates, and deletes documentsImplement an update by using a patch operationManage multi-document transactions using SDK Transactional BatchPerform a multi-document load using Bulk Support in the SDKImplement optimistic concurrency control using ETagsOverride default consistency by using query request optionsImplement session consistency by using session tokensImplement a query operation that includes paginationImplement a query operation by using a continuation tokenHandle transient errors and 429sSpecify TTL for a documentRetrieve and use query metricsImplement server-side programming in Azure Cosmos DB for NoSQL by using JavaScriptWrite, deploy, and call a stored procedureDesign stored procedures to work with multiple documents transactionallyImplement and call triggersImplement a user-defined functionDesign and implement data distribution (5–10%)Design and implement a replication strategy for Azure Cosmos DBChoose when to distribute dataDefine automatic failover policies for regional failure for Azure Cosmos DB for NoSQLPerform manual failovers to move single master write regionsChoose a consistency modelIdentify use cases for different consistency modelsEvaluate the impact of consistency model choices on availability and associated request unit (RU) costEvaluate the impact of consistency model choices on performance and latencySpecify application connections to replicated dataDesign and implement multi-region writeChoose when to use multi-region writeImplement multi-region writeImplement a custom conflict resolution policy for Azure Cosmos DB for NoSQLIntegrate an Azure Cosmos DB solution (5–10%)Enable Azure Cosmos DB analytical workloadsEnable Azure Synapse LinkChoose between Azure Synapse Link and Spark ConnectorEnable the analytical store on a containerImplement custom partitioning in Azure Synapse LinkEnable a connection to an analytical store and query from Azure Synapse Spark or Azure Synapse SQLPerform a query against the transactional store from SparkWrite data back to the transactional store from SparkImplement solutions across servicesIntegrate events with other applications by using Azure Functions and Azure Event HubsDenormalize data by using Change Feed and Azure FunctionsEnforce referential integrity by using Change Feed and Azure FunctionsAggregate data by using Change Feed and Azure Functions, including reportingArchive data by using Change Feed and Azure FunctionsImplement Azure Cognitive Search for an Azure Cosmos DB solutionOptimize an Azure Cosmos DB solution (15–20%)Optimize query performance when using the API for Azure Cosmos DB for NoSQLAdjust indexes on the databaseCalculate the cost of the queryRetrieve request unit cost of a point operation or queryImplement Azure Cosmos DB integrated cacheDesign and implement change feeds for Azure Cosmos DB for NoSQLDevelop an Azure Functions trigger to process a change feedConsume a change feed from within an application by using the SDKManage the number of change feed instances by using the change feed estimatorImplement denormalization by using a change feedImplement referential enforcement by using a change feedImplement aggregation persistence by using a change feedImplement data archiving by using a change feedDefine and implement an indexing strategy for Azure Cosmos DB for NoSQLChoose when to use a read-heavy versus write-heavy index strategyChoose an appropriate index typeConfigure a custom indexing policy by using the Azure portalImplement a composite indexOptimize index performanceMaintain an Azure Cosmos DB solution (25–30%)Monitor and troubleshoot an Azure Cosmos DB solutionEvaluate response status code and failure metricsMonitor metrics for normalized throughput usage by using Azure MonitorMonitor server-side latency metrics by using Azure MonitorMonitor data replication in relation to latency and availabilityConfigure Azure Monitor alerts for Azure Cosmos DBImplement and query Azure Cosmos DB logsMonitor throughput across partitionsMonitor distribution of data across partitionsMonitor security by using logging and auditingImplement backup and restore for an Azure Cosmos DB solutionChoose between periodic and continuous backupConfigure periodic backupConfigure continuous backup and recoveryLocate a recovery point for a point-in-time recoveryRecover a database or container from a recovery pointImplement security for an Azure Cosmos DB solutionChoose between service-managed and customer-managed encryption keysConfigure network-level access control for Azure Cosmos DBConfigure data encryption for Azure Cosmos DBManage control plane access to Azure Cosmos DB by using Azure role-based access control (RBAC)Manage data plane access to Azure Cosmos DB by using keysManage data plane access to Azure Cosmos DB by using Microsoft Entra IDConfigure cross-origin resource sharing (CORS) settingsManage account keys by using Azure Key VaultImplement customer-managed keys for encryptionImplement Always EncryptedImplement data movement for an Azure Cosmos DB solutionChoose a data movement strategyMove data by using client SDK bulk operationsMove data by using Azure Data Factory and Azure Synapse pipelinesMove data by using a Kafka connectorMove data by using Azure Stream AnalyticsMove data by using the Azure Cosmos DB Spark ConnectorConfigure Azure Cosmos DB as a custom endpoint for an Azure IoT HubImplement a DevOps process for an Azure Cosmos DB solutionChoose when to use declarative versus imperative operationsProvision and manage Azure Cosmos DB resources by using Azure Resource Manager templatesMigrate between standard and autoscale throughput by using PowerShell or Azure CLIInitiate a regional failover by using PowerShell or Azure CLIMaintain indexing policies in production by using Azure Resource Manager templates