Microsoft Azure Data Fundamentals - Course DP-900 (beta)

Microsoft Certified: Azure Data Fundamentals

Azure Data Fundamentals can be used to prepare for other Azure role-based certifications like Azure Database Administrator Associate or Azure Data Engineer Associate, but it’s not a prerequisite for any of them.

Exam DP-900: Microsoft Azure Data Fundamentals (beta)

Candidates for this exam should have foundational knowledge of core data concepts and how they are implemented using Microsoft Azure data services.

This exam is intended for candidates beginning to work with data in the cloud.

Candidates should be familiar with the concepts of relational and non-relational data, and different types of data workloads such as transactional or analytical.


The following course prepare the exam DP-900:

DP-900: Microsoft Azure Data Fundamentals

Data Scientist is the central role in developing machine learning models. This role is responsible for solving the business problem that initiated the project. While the Data Engineer will prepare the data to be used for the models, the Data Scientist determines what data is needed for model training, creates model features from the data, determines what machine learning model to use, trains and evaluates the model, and often has involvement in model deployment. Often the data scientist needs to evaluate multiple models to determine which performs the best.



Describe core data concepts

  • Describe types of core data workloads
  • Describe data analytics core concepts

Describe how to work with relational data on Azure

  • Describe relational data workloads
  • Describe relational Azure data services
  • Identify basic management tasks for relational data
  • Describe query techniques for data using SQL language

Describe how to work with non-relational data on Azure

  • Describe non-relational data workloads
  • Describe non-relational data offerings on Azure
  • Identify basic management tasks for non-relational data

Describe an analytics workload on Azure

  • Describe analytics workloads
  • Describe the components of a modern data warehouse
  • Describe data ingestion and processing on Azure
  • Describe data visualization in Microsoft Power BI

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