DP-900: Microsoft Azure Data Fundamentals.

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.

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. The fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build your foundational knowledge of cloud data services within Microsoft Azure. You will identify and describe core data concepts such as relational, non-relational, big data, and analytics, and explore how this technology is implemented with Microsoft Azure. You will explore the roles, tasks, and responsibilities in the world of data.

Over the last few decades, the amount of data that systems, applications, and devices have generated has increased significantly. Data is everywhere. Data is available in different structures and formats. Understanding data and exploring it reveals interesting facts, and helps you gain meaningful insights.

In this module, you'll learn about how you can organize and process data. You'll learn about relational and non-relational databases, and how data is handled through transactional processing, and through batch and streaming data processing.

To consider how the tools and techniques learnt can be applied in real world scenarios, imagine you're a data analyst for a large consumer organization. The organization wants to understand customer buying patterns from supermarkets. The organization has a number of datasets from different sources, such as till information (point of sale), weather data, and holiday data. The organization would like to use Azure technologies to understand and analyze these datasets. This scenario will be used throughout the module.