Explanation

Box 1: Interactive Query
Choose Interactive Query cluster type to optimize for ad hoc, interactive queries.
Box 2: Hadoop
Choose Apache Hadoop cluster type to optimize for Hive queries used as a batch process.
Note: In Azure HDInsight, there are several cluster types and technologies that can run Apache Hive queries.
When you create your HDInsight cluster, choose the appropriate cluster type to help optimize performance for your workload needs.
For example, choose Interactive Query cluster type to optimize for ad hoc, interactive queries. Choose Apache Hadoop cluster type to optimize for Hive queries used as a batch process. Spark and HBase cluster types can also run Hive queries.
References:
https://docs.microsoft.com/bs-latn-ba/azure/hdinsight/hdinsight-hadoop-optimize-hive-query?toc=%2Fko-kr%2F

To set up the database as a subscriber we need to configure database replication. You can use SQL Server Management Studio to configure replication. Use the latest versions of SQL Server Management Studio in order to be able to use all the features of Azure SQL Database.
References:
https://www.sqlshack.com/sql-server-database-migration-to-azure-sql-database-using-sql-server-transactionalreplication/

DirectQuery mode is required for automatic page refresh.
Reference:
https://docs.microsoft.com/en-us/power-bi/service-real-time-streaming
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-twitter-sentiment-analysis-trends

In Azure, all of the following data stores will meet the core requirements supporting real-time processing:
* Apache Spark in Azure Databricks
* Azure Stream Analytics
* HDInsight with Spark Streaming
* HDInsight with Storm
* Azure Functions
* Azure App Service WebJobs
Note: Lambda architectures use batch-processing, stream-processing, and a serving layer to minimize the latency involved in querying big data.

Reference:
https://azure.microsoft.com/en-us/blog/lambda-architecture-using-azure-cosmosdb-faster-performance-low- tco-low-devops/
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/stream-processing
https://docs.microsoft.com/en-us/azure/cosmos-db/lambda-architecture
Design for data security and compliance
Testlet 1
Case study
This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
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.
Requirements. 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.
Requirements. 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 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.

Scenario: Limit the business analysts' access to customer contact information, such as phone numbers, because this type of data is not analytically relevant.
Labeling: You can apply sensitivity-classification labels persistently to columns by using new metadata attributes that have been added to the SQL Server database engine. This metadata can then be used for advanced, sensitivity-based auditing and protection scenarios.
Incorrect Answers:
D: Transparent Data Encryption (TDE) encrypts SQL Server, Azure SQL Database, and Azure Synapse Analytics data files, known as encrypting data at rest. TDE does not provide encryption across communication channels.
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/data-discovery-and-classification-overview
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-security-overview Design for data security and compliance Testlet 2 Case study This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
Overview
General Overview
ADatum Corporation is a medical company that has 5,000 physicians located in more than 300 hospitals across the US. The company has a medical department, a sales department, a marketing department, a medical research department, and a human resources department.
You are redesigning the application environment of ADatum.
Physical Locations
ADatum has three main offices in New York, Dallas, and Los Angeles. The offices connect to each other by using a WAN link. Each office connects directly to the Internet. The Los Angeles office also has a datacenter that hosts all the company's applications.
Existing Environment
Health Review
ADatum has a critical OLTP web application named Health Review that physicians use to track billing, patient care, and overall physician best practices.
Health Interface
ADatum has a critical application named Health Interface that receives hospital messages related to patient care and status updates. The messages are sent in batches by each hospital's enterprise relationship management (ERM) system by using a VPN. The data sent from each hospital can have varying columns and formats.
Currently, a custom C# application is used to send the data to Health Interface. The application uses deprecated libraries and a new solution must be designed for this functionality.
Health Insights
ADatum has a web-based reporting system named Health Insights that shows hospital and patient insights to physicians and business users. The data is created from the data in Health Review and Health Interface, as well as manual entries.
Database Platform
Currently, the databases for all three applications are hosted on an out-of-date VMware cluster that has a single instance of Microsoft SQL Server 2012.
Problem Statements
ADatum identifies the following issues in its current environment:
* Over time, the data received by Health Interface from the hospitals has slowed, and the number of messages has increased.
* When a new hospital joins ADatum, Health Interface requires a schema modification due to the lack of data standardization.
* The speed of batch data processing is inconsistent.
Business Requirements
Business Goals
ADatum identifies the following business goals:
* Migrate the applications to Azure whenever possible.
* Minimize the development effort required to perform data movement.
* Provide continuous integration and deployment for development, test, and production environments.
* Provide faster access to the applications and the data and provide more consistent application performance.
* Minimize the number of services required to perform data processing, development, scheduling, monitoring, and the operationalizing of pipelines.
Health Review Requirements
ADatum identifies the following requirements for the Health Review application:
* Ensure that sensitive health data is encrypted at rest and in transit.
* Tag all the sensitive health data in Health Review. The data will be used for auditing.
Health Interface Requirements
ADatum identifies the following requirements for the Health Interface application:
* Upgrade to a data storage solution that will provide flexible schemas and increased throughput for writing data. Data must be regionally located close to each hospital, and reads must display be the most recent committed version of an item.
* Reduce the amount of time it takes to add data from new hospitals to Health Interface.
* Support a more scalable batch processing solution in Azure.
* Reduce the amount of development effort to rewrite existing SQL queries.
Health Insights Requirements
ADatum identifies the following requirements for the Health Insights application:
* The analysis of events must be performed over time by using an organizational date dimension table.
* The data from Health Interface and Health Review must be available in Health Insights within 15 minutes of being committed.
* The new Health Insights application must be built on a massively parallel processing (MPP) architecture that will support the high performance of joins on large fact tables.