Free DP-900 Exam Dumps Preview

With ELT, the data store used to perform the transformation is the same data store where the data is ultimately consumed.

References:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/etl

A graph database is a collection of nodes (or vertices) and edges (or relationships). Therefore, the correct answer is Vertexes.

References:
https://docs.microsoft.com/en-us/power-bi/consumer/end-user-dashboards
https://docs.microsoft.com/en-us/power-bi/create-reports/service-dashboard-add-widget

References:
https://docs.microsoft.com/en-us/sql/big-data-cluster/connect-to-big-data-cluster?view=sql-server-ver15
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-query-ssms
https://docs.microsoft.com/en-us/azure/mariadb/connect-workbench

Azure SQL Database is relational database and a managed service.

Incorrect Answers:
A, B: Cosmos DB, HDInsight are non-relational databases.
D: Azure Synapse Analytics is for data warehousing, not for Online Transaction Processing

References:
https://cloud.netapp.com/blog/azure-cvo-blg-azure-database-review-your-guide-for-database-assessment

SQL Server on Azure VM SQL Server on Azure VM falls into the industry category Infrastructure-as-a-Service (IaaS) and allows you to run SQL Server inside a fully managed virtual machine (VM) in Azure.
The most significant difference from SQL Database and SQL Managed Instance is that SQL Server on Azure Virtual Machines allows full control over the database engine. You can choose when to start maintenance/patching, change the recovery model to simple or bulk-logged, pause or start the service when needed, and you can fully customize the SQL Server database engine. With this additional control comes the added responsibility to manage the virtual machine.
References:
https://docs.microsoft.com/en-us/azure/azure-sql/azure-sql-iaas-vs-paas-what-is-overview?view=azuresql

Box 1: Azure Data Factory

Box 2: Azure Data Lake Storage
Azure Data Lake Storage (ADLA) now natively supports Parquet files. ADLA adds a public preview of the native extractor and outputter for the popular Parquet file format

Box 3: Azure Synapse Analytics
Use Azure Synapse Analytics Workspaces.

References:
https://docs.microsoft.com/en-us/azure/data-factory/supported-file-formats-and-compression-codecs

References:
https://docs.microsoft.com/en-us/azure/azure-sql/database/sql-database-paas-overview

Real time processing deals with streams of data that are captured in real-time and processed with minimal latency to generate real-time (or near-real-time) reports or automated responses.

References:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/real-time-processing

References:
https://docs.databricks.com/data/data-sources/azure/synapse-analytics.html

References:
https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-get-started-portal
https://docs.microsoft.com/en-us/azure/storage/common/storage-account-overview
https://azure.microsoft.com/en-us/pricing/details/bandwidth/

The ans should be A.
In the textbook DP-900T00-A-Microsoft Azure Data Fundamentals Module 4 Describe modern data warehousing: ''A data warehouse gathers data from many different sources within an organization...The focus of a data warehouse is to provide answers to complex queries...''

References:
https://docs.microsoft.com/en-us/sql/relational-databases/views/views

Data Manipulation Language (DML) statements:
DELETE
INSERT
References:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-reference-tsql-statements

References:
https://docs.microsoft.com/en-us/power-bi/consumer/end-user-dashboards
https://docs.microsoft.com/en-us/power-bi/visuals/power-bi-visualization-kpi
https://docs.microsoft.com/en-us/power-bi/consumer/end-user-drill

Y - Azure Data Lake Storage can be used as a staging area for ingested data before the data is converted into a format suitable for performing analytics. It allows you to store and analyze large amounts of data, and it is optimized for big data analytics workloads.
N - Azure Data Factory is a cloud-based data integration service that allows you to create, schedule, and manage data pipelines. It does not use a massively parallel processing architecture by default, but allows you to perform complex data integration and transformation tasks by integrating with other Azure services.
N - Azure HDInsight is designed for big data analytics workloads and does not enable you to build tabular models from multiple data sources to support OLAP queries. Azure Analysis Services is a service that you can use to create and manage tabular models for OLAP.

A key/value store associates each data value with a unique key.
Key/value stores are highly optimized for applications performing simple lookups, but are less suitable if you need to query data across different key/value stores.
Key/value stores are also not optimized for querying by value.
A single key/value store can be extremely scalable, as the data store can easily distribute data across multiple nodes on separate machines.
References:
https://docs.microsoft.com/en-us/azure/architecture/guide/technology-choices/data-store-overview

Azure Storage offers two options for copying your data to a secondary region:

Geo-redundant storage (GRS)
Geo-zone-redundant storage (GZRS)
With GRS or GZRS, the data in the secondary region isn't available for read or write access unless there is a failover to the secondary region.

For read access to the secondary region, configure your storage account to use read-access geo-redundant storage (RA-GRS) or read-access geo-zone-redundant storage (RA-GZRS).

References:
https://docs.microsoft.com/en-us/azure/storage/common/storage-redundancy#redundancy-in-a-secondary-region

Serverless is a compute tier for single databases in Azure SQL Database that automatically scales compute based on workload demand and bills for the amount of compute used per second. The serverless compute tier also automatically pauses databases during inactive periods when only storage is billed and automatically resumes databases when activity returns.

A graph database stores two types of information, nodes and edges. Edges specify relationships between nodes. Nodes and edges can have properties that provide information about that node or edge, similar to columns in a table. Edges can also have a direction indicating the nature of the relationship.
References:
https://docs.microsoft.com/en-us/azure/architecture/guide/technology-choices/data-store-overview

References:
https://www.sqlshack.com/start-your-journey-with-azure-cosmos-db/

The Azure SQL Database firewall lets you decide which IP addresses may or may not have access to either your Azure SQL Server or your Azure SQL database. When creating an Azure SQL Database, the firewall needs to be configured before anyone will be able to access the database. By default, no external access to your SQL Database will be allowed until you explicitly assign permission by creating a firewall rule.

References:
https://www.sqlshack.com/configuring-the-azure-sql-database-firewall/

Note: Azure Media Indexer enables you to make content of your media files searchable and to generate a full-text transcript for closed captioning and keywords. You can process one media file or multiple media files in a batch.

Azure Private Link enables you to access Azure PaaS Services (for example, Azure Storage and SQL Database) and Azure hosted customer-owned/partner services over a private endpoint in your virtual network.

Traffic between your virtual network and the service travels the Microsoft backbone network. Exposing your service to the public internet is no longer necessary

References:
https://techcommunity.microsoft.com/t5/azure-database-support-blog/azure-sql-db-private-link-private-endpoint-connectivity/ba-p/1235573

Box 1: Azure Data factory
Relevant Azure service for the three ETL phases are Azure Data Factory and SQL Server Integration Services (SSIS).

Box 2: Azure Synapse Analytics
You can copy and transform data in Azure Synapse Analytics by using Azure Data Factory

Note: Azure Synapse Analytics connector is supported for the following activities: Copy activity with supported source/sink matrix table Mapping data flow Lookup activity GetMetadata activity

References:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/etl
https://docs.microsoft.com/en-us/azure/data-factory/connector-azure-sql-data-warehouse

References:
https://docs.microsoft.com/en-us/azure/postgresql/overview-postgres-choose-server-options

Data as it appears in the real world is naturally connected. Traditional data modeling focuses on defining entities separately and computing their relationships at runtime. While this model has its advantages, highly connected data can be challenging to manage under its constraints.

A graph database approach relies on persisting relationships in the storage layer instead, which leads to highly efficient graph retrieval operations. Azure Cosmos DB's Gremlin API supports the property graph model.

References:
https://docs.microsoft.com/en-us/azure/cosmos-db/graph-introduction#introduction-to-graph-databases

A: Azure SQL Database is a fully managed platform as a service (PaaS) database engine that handles most of the database management functions such as upgrading, patching, backups, and monitoring without user involvement.

D: SQL Database delivers predictable performance with multiple resource types, service tiers, and compute sizes. It provides dynamic scalability with no downtime, built-in intelligent optimization, global scalability and availability, and advanced security options. These capabilities allow you to focus on rapid app development and accelerating your time-to-market, rather than on managing virtual machines and infrastructure.

References:
https://docs.microsoft.com/en-us/azure/azure-sql/database/sql-database-paas-overview