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Microsoft DP-900 Exam Syllabus Topics:
| Topic | Details |
|---|---|
Describe core data concepts (15-20%) | |
| Describe types of core data workloads | - describe batch data - describe streaming data - describe the difference between batch and streaming data - describe the characteristics of relational data |
| Describe data analytics core concepts | - describe data visualization (e.g., visualization, reporting, business intelligence (BI)) - describe basic chart types such as bar charts and pie charts - describe analytics techniques (e.g., descriptive, diagnostic, predictive, prescriptive, cognitive) - describe ELT and ETL processing - describe the concepts of data processing |
Describe how to work with relational data on Azure (25-30%) | |
| Describe relational data workloads | - identify the right data offering for a relational workload - describe relational data structures (e.g., tables, index, views) |
| Describe relational Azure data services | - describe and compare PaaS, IaaS, and SaaS solutions - describe Azure SQL family of products including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machines - describe Azure Synapse Analytics - describe Azure Database for PostgreSQL, Azure Database for MariaDB, and Azure Database for MySQL |
| Identify basic management tasks for relational data | - describe provisioning and deployment of relational data services - describe method for deployment including the Azure portal, Azure Resource Manager templates, Azure PowerShell, and the Azure command-line interface (CLI) - identify data security components (e.g., firewall, authentication) - identify basic connectivity issues (e.g., accessing from on-premises, access with Azure VNets, access from Internet, authentication, firewalls) - identify query tools (e.g., Azure Data Studio, SQL Server Management Studio, sqlcmd utility, etc.) |
| Describe query techniques for data using SQL language | - compare Data Definition Language (DDL) versus Data Manipulation Language (DML) - query relational data in Azure SQL Database, Azure Database for PostgreSQL, and Azure Database for MySQL |
Describe how to work with non-relational data on Azure (25-30%) | |
| Describe non-relational data workloads | - describe the characteristics of non-relational data - describe the types of non-relational and NoSQL data - recommend the correct data store - determine when to use non-relational data |
| Describe non-relational data offerings on Azure | - identify Azure data services for non-relational workloads - describe Azure Cosmos DB APIs - describe Azure Table storage - describe Azure Blob storage - describe Azure File storage |
| Identify basic management tasks for non-relational data | - describe provisioning and deployment of non-relational data services - describe method for deployment including the Azure portal, Azure Resource Manager templates, Azure PowerShell, and the Azure command-line interface (CLI) - identify data security components (e.g., firewall, authentication, encryption) - identify basic connectivity issues (e.g., accessing from on-premises, access with Azure VNets, access from Internet, authentication, firewalls) - identify management tools for non-relational data |
Describe an analytics workload on Azure (25-30%) | |
| Describe analytics workloads | - describe transactional workloads - describe the difference between a transactional and an analytics workload - describe the difference between batch and real time - describe data warehousing workloads - determine when a data warehouse solution is needed |
| Describe the components of a modern data warehouse | - describe Azure data services for modern data warehousing such as Azure Data Lake Storage Gen2, Azure Synapse Analytics, Azure Databricks, and Azure HDInsight - describe modern data warehousing architecture and workload |
| Describe data ingestion and processing on Azure | - describe common practices for data loading - describe the components of Azure Data Factory (e.g., pipeline, activities, etc.) - describe data processing options (e.g., Azure HDInsight, Azure Databricks, Azure Synapse Analytics, Azure Data Factory) |
| Describe data visualization in Microsoft Power BI | - describe the role of paginated reporting - describe the role of interactive reports - describe the role of dashboards - describe the workflow in Power BI |
Microsoft DP-900: Microsoft Azure Data Fundamentals Exam Certified Professional salary
The average salary of a Microsoft DP-900: Microsoft Azure Data Fundamentals Exam Certified Expert in
- India - 12,10,327 INR
- England - 60,532 POUNDS
- Europe - 60,547 EURO
- United States - 80,000 USD
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-900
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Languages: English, Japanese, Chinese (Simplified), Korean, French, German, Spanish, Portuguese (Brazil), Russian, Indonesian (Indonesia), Arabic (Saudi Arabia), Chinese (Traditional), Italian
Retirement date: none
Prove that you can describe the following: core data concepts; how to work with relational data on Azure; how to work with non-relational data on Azure; and an analytics workload on Azure.
Microsoft DP-900 Practice Test Questions, Microsoft DP-900 Exam Practice Test Questions
The Microsoft DP-900 exam is a qualifying test for obtaining the Microsoft Certified: Azure Data Fundamentals certification. This exam is intended for the entry-level professionals looking to take up a career path in the IT field. Although it is not a requirement for any advanced-level certificate, the DP-900: Microsoft Azure Data Fundamentals test is a great foundation to prepare the individuals for other Azure role-based options. Thus, the certified candidates can pursue two certifications: Azure Data Engineer Associate or Azure Database Administrator Associate.
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Microsoft Azure Data Fundamentals (DP-900 Deutsch Version) Sample Questions:
Ihr Unternehmen plant, Daten aus einem Customer-Relationship-Management-System (CRM) mithilfe eines ELT-Prozesses (Extract Load and Transform) in ein Data Warehouse zu laden.
Wo findet die Datenverarbeitung in den einzelnen Phasen des ELT-Prozesses statt? Ziehen Sie zur Beantwortung die entsprechenden Stellen an die richtige Stelle. Jede Stelle kann einmal oder gar nicht verwendet werden. Möglicherweise müssen Sie die Trennleiste zwischen den Bereichen ziehen oder scrollen, um den Inhalt anzuzeigen.
HINWEIS: Jede richtige Auswahl ist einen Punkt wert.
Correct Answer:

Explanation:
Box 1: The CRM system
Data is extracted from the CRM system.
Box 2: The data warehouse
Data is loaded to the data warehouse.
Box 3: An in-memory data integration tool
The data transformation that takes place usually involves various operations, such as filtering, sorting, aggregating, joining data, cleaning data, deduplicating, and validating data.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/etl
Auf welchen zwei Ebenen können Sie den Durchsatz für ein Azure Cosmos DB-Konto festlegen? Jede richtige Antwort stellt eine vollständige Lösung dar.
HINWEIS: Jede richtige Auswahl ist einen Punkt wert.
- A. Artikel
- B. Datenbank
- C. Behälter
- D. Partition
Correct Answer: B,C 🗳️
Explanation: Only visible for PassLeader members. You can sign-up / login (it's free).
Sie planen die Bereitstellung einer App. Die App benötigt einen nicht-relationalen Datendienst, der eine garantierte Latenz von weniger als 10 ms für Lese- und Schreibvorgänge bietet. Was sollte die Lösung beinhalten?
- A. Azure-Dateien
- B. Azure Blob-Speicher
- C. Azure-Tabellenspeicher
- D. Azure Cosmos
Correct Answer: D 🗳️
Ein Balkendiagramm mit den Verkäufen seit Jahresbeginn nach Regionen ist ein Beispiel für welche Art von Analyse?
- A. vorausschauend
- B. beschreibend
- C. vorgeschrieben
- D. Diagnose
Correct Answer: D 🗳️
Ihr Unternehmen entwirft einen Datenspeicher, der Schülerdaten enthält. Die Daten haben das folgende Format.
Welche Art von Datenspeicher sollten Sie verwenden?
- A. Grafik
- B. Schlüssel / Wert
- C. Objekt
- D. säulenförmig
Correct Answer: D 🗳️
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