Introduction to Data Engineering with Microsoft Azure 1
- Offered byFutureLearn
Introduction to Data Engineering with Microsoft Azure 1 at FutureLearn Overview
Duration | 6 weeks |
Total fee | ₹2,763 |
Mode of learning | Online |
Credential | Certificate |
Introduction to Data Engineering with Microsoft Azure 1 at FutureLearn Highlights
- Earn a certificate upon completion
Introduction to Data Engineering with Microsoft Azure 1 at FutureLearn Course details
- On this course, you’ll explore the generation, storage, and management of data using various technologies and platforms and prepare to take the DP-203 exam
- You’ll investigate data platforms, including cloud technologies, and examine a data engineer’s role in helping organizations benefit from technological advances
- Using Azure Data Factory and Azure Synapse Pipeline, you’ll learn to manage data pipelines and build analytical solutions that align with business requirements
- Using tools such as Apache Spark, you’ll be able to boost the performance of big-data analytic applications, taking your data visualization and analysis skills to the next level
- By continuing your learning with Introduction to Data Engineering with Microsoft Azure 2, you’ll equip yourself with all the necessary knowledge to pass the exam and progress your career in data engineering
Introduction to Data Engineering with Microsoft Azure 1 at FutureLearn Curriculum
Azure for the Data Engineer
Understand the evolving world of data
Survey the services on the Azure Data platform
Identify the tasks of a data engineer in a cloud-hosted architecture
Store data in Azure
Choose a data storage approach in Azure
Create an Azure Storage account
Connect an app to Azure Storage
Secure your Azure Storage account
Store application data with Azure Blob storage
Data integration at scale with Azure Data Factory or Azure Synapse Pipeline
Integrate data with Azure Data Factory or Azure Synapse Pipeline
Petabyte-scale ingestion with Azure Data Factory or Azure Synapse Pipeline
Perform code-free transformation at scale with Azure Data Factory or Azure Synapse Pipeline
Populate slowly changing dimensions in Azure Synapse Analytics pipelines
Orchestrate data movement and transformation in Azure Data Factory or Azure Synapse Pipeline
Execute existing SSIS packages in Azure Data Factory or Azure Synapse Pipeline
Operationalize your Azure Data Factory or Azure Synapse Pipeline
Realize Integrated Analytical Solutions with Azure Synapse Analytics
Introduction to Azure Synapse Analytics
Survey the Components of Azure Synapse Analytics
Explore Azure Synapse Studio
Design a Modern Data Warehouse using Azure Synapse Analytics
Work with Data Warehouses using Azure Synapse Analytics
Design a multidimensional schema to optimize analytical workloads
Use data loading best practices in Azure Synapse Analytics
Optimize data warehouse query performance in Azure Synapse Analytics
Integrate SQL and Apache Spark pools in Azure Synapse Analytics
Understand data warehouse developer features of Azure Synapse Analytics
Manage and monitor data warehouse activities in Azure Synapse Analytics
Analyze and optimize data warehouse storage in Azure Synapse Analytics
Secure a data warehouse in Azure Synapse Analytics
Perform data engineering with Azure Synapse Apache Spark Pools
Analyze data with Apache Spark in Azure Synapse Analytics
Ingest data with Apache Spark notebooks in Azure Synapse Analytics
Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics
Integrate SQL and Apache Spark pools in Azure Synapse Analytics
Monitor and manage data engineering workloads with Apache Spark in Azure Synapse Analytics
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