Data Processing with Azure
- Offered byCoursera
Data Processing with Azure at Coursera Overview
Duration | 13 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course |
Credential | Certificate |
Data Processing with Azure at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Intermediate Level
- Approx. 13 hours to complete
- English Subtitles: French, Portuguese (European), Russian, English, Spanish
Data Processing with Azure at Coursera Course details
- This Azure training course is designed to equip students with the knowledge need to process, store and analyze data for making informed business decisions. Through this Azure course, the student will understand what big data is along with the importance of big data analytics, which will improve the students mathematical and programming skills. Students will learn the most effective method of using essential analytical tools such as Python, R, and Apache Spark.
Data Processing with Azure at Coursera Curriculum
Introduction
Course Introduction
1.1 Batch Processing with Databricks and Data Factory in Azure
1.2 - ELT Processing using Azure
1.3 - Databricks and Azure Spark
1.4 Transform Data using Databricks in ADF
1.5 Use Case: ADF and Spark
Azure Databricks and Apache Spark
Exercise 1 - Use Batch Processing with Databricks and Data Factory on Azure
Exercise 2 - Intro to Databricks and Data Factory Page
Module 1 Quiz
Pipelines and Activities - Introduction
Processing using a Pipeline
Analyzing Logs for an HDInsight Cluster
Using Azure Blob Storage within HDInsight
Using Azure Blob Storage with HDInsight
Exercise 1 - Pipeline Activities & Usage in Azure Data Factory
Exercise 2 - Examine Logs within the HDInsight/Blob Storage
Module 2 Quiz
Section 3 - Link Services and Datasets
Link Services and Datasets - Introduction
Identifying Pipelines for a Data Factory
Data Stores and Azure Blob Storage
Linked Service and Connecting Data Factory to External Resources
Processing Input Blobs with Azure Data Factory
Exercise 1 - Link Data within Datasets in Azure Storage
Module 3 Quiz
Schedules and Triggers - Introduction
Creating a Trigger that Runs a Pipeline on a Schedule
Scheduling a Trigger in Azure Data Factory
Pipeline Execution and Triggers in ADF
Use Case: Azure Schedule, Trigger, and Events
Pipeline Execution and Triggers in ADF
Module 4 Quiz
Selecting Windowing Functions - Introduction
How Stream Analytics Support Native Windowing Functions
Temporal Windows
Using Window Functions in the GROUP BY Clause
Aggregating Events over Multiple Windows using WindowsQ
Understanding Stream Analytics Windowing Functions
Module 5 Quiz
Section 6 - Configuring Input and Output for Streaming Data Solutions
How Stream Analytics Relate to Data Solutions
Generate Sample Call Data and Send it to Event Hubs
Creating a Stream Analytics Job
Configuring Job Input and Output
Define a Query to Filter Fraudulent Calls
Test and Start the Job
Visualize Results in Power BI
Output Real-Time Stream Analytics Data to a Power BI Dashboard
Module 6 Quiz
ELT vs ETL in PolyBase - Introduction
How SQL Data Warehouse in Microsoft Offers ELT Solutions
Loading Methods using Non-PolyBase Options
Use Case: A Deeper Dive into ETL Processing
Video: Ingesting Data using Polybase
Azure SQL Data Warehouse
Module 7 Quiz