Getting Started with Cosmos DB NoSQL Development
This course teaches developers to utilize Azure Cosmos DB for NoSQL API and SDK. Students will learn query execution, resource configuration, SDK operations, and design strategies for non-relational data modeling and data partitioning.
This learning path prepares you for the task of developing data-driven applications by using Microsoft Azure SQL Database.
You’ll learn how to create and configure an Azure SQL Database, build and deploy database projects using GitHub Actions and Azure Pipelines, and automate the publishing process. Additionally, you’ll explore how to use Data API builder for Azure SQL Database and develop a data API with Azure Web Apps and Static Web App.
Furthermore, you’ll gain skills in importing data via an external REST endpoint, exporting data using an Azure Function, and securing an Azure SQL Database. These essential skills will empower you to effectively develop and manage applications using Azure SQL Database.
Azure Database for PostgreSQL is a Platform as a Service database service in the Microsoft cloud. It bases itself on the PostgreSQL open-source relational database and includes built-in high availability, automatic backup and restore, as well as comprehensive security features. The pay-as-you-go pricing model provides predictable performance and near-instant scaling.
In this learning path, you learn the main features of PostgreSQL and how they work in Azure Database for PostgreSQL. You learn about the different Azure Database for PostgreSQL implementation options, and how to configure a server for your needs.
Unlock opportunities with Azure Cosmos DB.
This DP-420T00: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB course teaches developers how to create application using the SQL API and SDK for Azure Cosmos DB. Students will learn how to write efficient queries, create indexing policies, manage and provisioned resources, and perform common operations with the SDK.
Microsoft Fabric Analytics Engineer.
This Microsoft course covers methods and practices for implementing and managing enterprise-scale data analytics solutions using Microsoft Fabric. Students will build on existing analytics experience and will learn how to use Microsoft Fabric components, including lakehouses, data warehouses, notebooks, dataflows, data pipelines, and semantic models, to create and deploy analytics assets.
Reshape how your entire team uses data.
Manage your data in a single, AI-powered analytics platform that helps teams turn data into a competitive advantage.
This DP-601T00: Implementing a Lakehouse with Microsoft Fabric course is designed to build your foundational skills in data engineering on Microsoft Fabric, focusing on the Lakehouse concept.
This official Microsoft course will explore the powerful capabilities of Apache Spark for distributed data processing and the essential techniques for efficient data management, versioning, and reliability by working with Delta Lake tables. This course will also explore data ingestion and orchestration using Dataflows Gen2 and Data Factory pipelines.
This course includes a combination of lectures and hands-on exercises that will prepare you to work with lakehouses in Microsoft Fabric.
Explore the data warehousing process and learn how to load, monitor, secure, and query a warehouse in Microsoft Fabric.
In this learning path, the student is exposed to various ways to:
Explore the data science process and learn how to train machine learning models to accomplish artificial intelligence in Microsoft Fabric.
Develop dynamic reports with Microsoft Power BI
Transform and load data, define semantic model relationships and calculations, create interactive visuals, and distribute reports using Power BI.
This course covers methods and practices to implement data engineering solutions by using Microsoft Fabric. Students will learn how to design and develop effective data loading patterns, data architectures, and orchestration processes.
Objectives for this course include ingesting and transforming data and securing, managing, and monitoring data engineering solutions.
This course is designed for experienced data professionals skilled at data integration and orchestration, such as those with the DP-203: Azure Data Engineer certification.
Unlock the potential of your data with Azure Data Fundamentals credential.
In this DP-900T00: Microsoft Azure Data Fundamentals course, students will 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. Students 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. They will explore the roles, tasks, and responsibilities in the world of data.
The students will explore relational data offerings, provisioning and deploying relational databases, and querying relational data through cloud data solutions with Microsoft Azure. They will explore non-relational data offerings, provisioning and deploying non-relational databases, and non-relational data stores with Microsoft Azure. Students will explore the processing options available for building data analytics solutions in Azure. They will explore Azure Synapse Analytics, Azure Databricks, and Azure HDInsight. Students will learn what Power BI is, including its building blocks and how they work together.
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With over 30 years of experience, Trainocate has been empowering individuals and businesses to build the essential skills that drive growth and success. Whether it’s professionals advancing in their careers or organizations transforming their workforce, our training programmes deliver results.
Specializing in cloud computing, data & AI, cybersecurity, and digital leadership, our training is powered by industry-leading technology partners like AWS, Alibaba Cloud, Cisco, EC-Council, Fortinet, Google Cloud, IBM, ISACA, ISC2, Microsoft, NetApp, Nutanix, Oracle, Palo Alto, Splunk, Red Hat, Rocheston, Trend Micro, and VMware.
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