Booking options
£595
+ VAT£595
+ VATDelivered Online
All levels
Duration
1 Days
6 CPD hours
This course is intended for
The audience for this course is individuals who want to learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build their foundational knowledge of cloud data services within Microsoft Azure.
Overview
Describe core data concepts Identify considerations for relational data on Azure Describe considerations for working with non-relational data on Azure Describe an analytics workload on Azure
In this course, students will gain foundational knowledge of core data concepts and related Microsoft Azure data services. Students will learn about core data concepts such as relational, non-relational, big data, and analytics, and build their foundational knowledge of cloud data services within Microsoft Azure. Students will explore fundamental relational data concepts and relational database services in Azure. They will explore Azure storage for non-relational data and the fundamentals of Azure Cosmos DB. Students will learn about large-scale data warehousing, real-time analytics, and data visualization.
Identify data formats
Explore file storage
Explore databases
Explore transactional data processing
Explore analytical data processing
Explore job roles in the world of data
Identify data services
Understand relational data
Understand normalization
Explore SQL
Describe database objects
Describe Azure SQL services and capabilities
Describe Azure services for open-source databases
Explore Azure blob storage
Explore Azure DataLake Storage Gen2
Explore Azure Files
Explore Azure Tables
Describe Azure Cosmos DB
Identify Azure Cosmos DB APIs
Describe data warehousing architecture
Explore data ingestion pipelines
Explore analytical data stores
Understand batch and stream processing
Explore common elements of stream processing architecture
Explore Azure Stream Analytics
Explore Apache Spark on Microsoft Azure
Describe Power BI tools and workflow
Describe core concepts of data modeling
Describe considerations for data visualization
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