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Wide World Importers (WWI) has hundreds of brick and mortar stores and an online store where they sell a variety of products. They would like to gain business insights using historical, real-time, and predictive analytics using structured and unstructured data sources. In doing so, they want to enable their IT team of data engineers and data scientists to bring in and run complex queries over petabytes of structured data with billions of rows and unstructured enterprise operational data. At the same time, they want to enable business analysts and their IT team to share a single source of truth and have a single workspace to collaborate and work with enterprise data and enriched customer data. They want to accomplish this minimizing the number of disparate services they use across ingest, transformation, querying and storage, so that their team of data engineers, data scientists and database administrators can master one tool, and can build shared best practices for development, management and monitoring.

October 2020

• Data engineer
• Data scientist
• Machine Learning engineer

In this workshop, you will look at the process of creating an end-to-end solution using Azure Synapse Analytics. The workshop will cover data loading, data preparation, data transformation and data serving, along with performing machine learning and handling of both batch and real-time data.

At the end of this whiteboard design session, you will be better able to design and build a complete end-to-end advanced analytics solution using Azure Synapse Analytics.

In this whiteboard design session, you will work in a group to look at the process of designing an end-to-end solution using Azure Synapse Analytics. The design session will cover data loading, data preparation, data transformation and data serving, along with performing machine learning and handling of both batch and real-time data.

At the end of this whiteboard design session, you will be better able to design and build a complete end-to-end advanced analytics solution using Azure Synapse Analytics.

In this hands-on-lab, you will build an end-to-end data analytics with machine learning solution using Azure Synapse Analytics. The information will be presented in the context of a retail scenario. We will be heavily leveraging Azure Synapse Studio, a tool that conveniently unifies the most common data operations from ingestion, transformation, querying, and visualization.

• Azure Synapse Analytics
• Azure Storage and Azure Data Lake gen 2
• Azure Stream Analytics
• Azure Machine Learning
• Azure App Service
• Event Hubs
• IoT Hub
• Power BI

• MCW

We welcome feedback and comments from Microsoft SMEs & learning partners who deliver MCWs.

Having trouble?

• First, verify you have followed all written lab instructions (including the Before the Hands-on lab document).
• Next, submit an issue with a detailed description of the problem.
• Do not submit pull requests. Our content authors will make all changes and submit pull requests for approval.

If you are planning to present a workshop, review and test the materials early! We recommend at least two weeks prior.