Download Microsoft Azure Data Fundamentals.CertDumps.DP-900.2022-07-04.1e.95q.vcex

https://docs.microsoft.com/en-us/azure/azure-sql/database/authentication-mfa-ssms-overview

Power BI dashboard, also known as Canvas, is a single page that tells a story with the help of visualizations.
The visualizations that are present on the Power BI Dashboard are known as Tiles. Once you select a tile, you will move to the report page where that visualization was created.
Option A is incorrect. Not visualizations but the Power BI dashboard is known as Canvas.
Option B is incorrect. There is nothing like Elements on the Power BI dashboard.
Option C is correct. The visualizations that are present on the Power BI Dashboard are known as Tiles.
Option D is incorrect. The visualizations come from the reports, these are not the reports.
Reference: To know more about the Visualization in Microsoft Power BI, refer to the documentation below from Azure:
https://docs.microsoft.com/en-us/power-bi/consumer/end-user-dashboards

A relational database stores data and provides access to data points that are related to each other. A relational database follows the basic relational model that is a simple and straightforward method of storing data in tables. Each row of the table in a relational database represents a record with a unique id i.e. key.
Each column of the table holds an attribute of the data, and each record represents the value for each attribute.
For example, a table STUDENT_RECORD represents the record of students in a class and the attributes of columns are - Student_Id, Student_Name, Student_Branch, and Student_Marks. We need to define the data type of each attribute in the beginning at the time of the creation of the table. Here, if we set Student_Id as a number, all the values in the column Student_Id will contain numbers only. And if we set it as alphanumeric, all the values in the column Student_Id will contain both alphabets and numbers.

     

So, Option A is correct.
Reference: To know more about the characteristics of Relational Databases, click the Lin below:
https://docs.rackspace.com/support/how-to/properties-of-rdbmss-and-nosql-databases/

Let's understand the different types of data analytics to find how Diagnostic analytics is the correct option here.
Descriptive Analytics explains what happened in the past. It provides context to the businesses and helps to understand how it is performing. It can be represented as data visualizations such as charts, graphs, dashboards, and reports.
Diagnostic Analytics explains why something has happened in the past. It takes the descriptive data to the next level and provides a deeper analysis of why something happened. It is also known as root cause analysis and includes data discovery, data mining, drill down, and drill through.
Predictive Analytics predicts what's most likely to happen in the future. It takes historical data and uses a machine learning model to predict what will happen next.
Prescriptive Analytics explains the actions to take to affect the upcoming results. It takes predictive data to the next level and suggests actions to be performed along with the outline of potential implications.
Option A is Correct. The descriptive analytics uses charts, graphs, dashboards, and reports to present what happened in the past and how it is performing. Here, the aim of creating bar chart is to track the year-wise sale.
Option B is incorrect. Diagnostic analytics explains why something happened in the past to find the root cause.
Here, the organization is using a bar chart just to track the sales, not the cause of increase or decrease. 
Option C is incorrect. Predictive analytics is done to predict what will happen in the future while here, the bar chart is presenting the past data of sales of the organization.
Option D is incorrect. Prescriptive analytics explains the set of actions to be performed as per the predictive analytics while here, the bar chart is presenting the past data of sales of the organization.
Reference: To know more about the different types of data analytics, refer to the link below:
https://www.logianalytics.com/predictive-analytics/comparing-descriptive-predictive-prescriptive-and-diagnostic-analytics/

SQL Server for Virtual Machines Azure database is responsible to migrate the SQL workloads on Azure while maintaining the operating system-level access and SQL Server compatibility. So, in the given scenario, SQL Server on Virtual Machines will be the right choice.
Option A is incorrect. Azure SQL Database is an up-to-date relational database service with hyper scale storage, serverless compute, automated, and AI-powered features for the optimization of durability and performance.
Option B is incorrect. Azure SQL Managed Instance enables the migration of SQL workloads to Azure and maintains SQL Server Compatibility with the benefits of an evergreen, fully managed Paas.
Option C is incorrect. Azure Cosmos DB enables building applications with high availability and low latency, at any scale, and anywhere. It also enables the migration of MongoDB, Cassandra, and other NoSQL workloads to the cloud.
Option D is correct. SQL Server for Virtual Machines Azure database is responsible to migrate the SQL workloads on Azure while maintaining the operating system-level access and SQL Server compatibility.
Reference: To know more about the Azure database products, refer to the link below:
https://azure.microsoft.com/en-in/product-categories/databases/

https://docs.microsoft.com/en-us/sql/ssdt/project-oriented-offline-database-development?view=sql-server-ver15

https://docs.microsoft.com/en-us/azure/cosmos-db/set-throughput

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

https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-access-control