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This accelerator was built to provide developers with all of the resources needed to build a solution to identify the top factors for revenue growth from an e-commerce platform using Azure Synapse Analytics and Azure Machine Learning.

License: MIT License

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azure-synapse-solution-accelerator-financial-analytics-customer-revenue-growth-factor's Introduction

page_type languages products
sample
python
azure-synapse-analytics
azure-machine-learning
power-bi

Customer Revenue Growth Factor Solution Accelerator

Customer Revenue Growth Factor Soltion Accelerator

This accelerator was built to provide developers with all of the resources needed to build a solution to identify the top factors for revenue growth from an e-commerce platform using Azure Synapse Analytics and Azure Machine Learning.

Getting Started

Start by deploying the resources needed for this solution:

Deploy to Azure

  1. Clone this repository and navigate to the root of the directory
  2. Go to Deployment guide for the steps you need to take to deploy this solution

Prerequisites

In order to successfully complete your solution, you will need to have access to and or provisioned the following:

  1. Access to an Azure subscription
  2. A Power BI Pro License (or free trial)

Optional

  1. Azure Storage Explorer

Azure and Analytics Platform

The directions provided for this repository assume fundemental working knowledge of Azure, Azure Synapse Analytics, Azure Machine Learning Services, and Power BI.

For additional training and support, please see:

  1. Azure Synapse Analytics
  2. Azure Machine Learning Services
  3. Power BI

Process Overview

The architecture diagram below details what you will be building for this Solution Accelerator:

Azure Synapse AI Architecture Azure Synapse AI + AutoML Architecture

Resource Deployment

The resources in this folder can be used to deploy the required resources into your Azure Subscription. You can do this in the Azure Portal

Analytics Deployment

This folder contains the Notebooks needed to complete this solution accelerator. Once you have deployed all the required resources from ResourceDeploymnet.md, run through the Notebooks following the instructions in Resource Deployment.

License

Copyright (c) Microsoft Corporation

All rights reserved.

MIT License

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the ""Software""), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED AS IS, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.

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azure-synapse-solution-accelerator-financial-analytics-customer-revenue-growth-factor's Issues

Deployment Guide in Incomplete

I was trying to spin this up in my environment and found that the instructions provided are incomplete and/or unclear in some areas.

Fpor instance in step 2 Storage Account permissions, I found I needed to also import the 6 - PBI Data Model notebook as it is needed for Step 5.

And there is instruction to skip to step 8, but there is no step 8 in the documentation.

Notebook 4 Needs to Be Updated

In notebook 4, right at the bottom, the model metrics and important features are being saved to the ADLS:

important_features.write.format("delta").mode("overwrite").option("overwriteSchema", "true").save(f"abfss://{file_system_name}" + "@"+ f"{data_lake_account_name}.dfs.core.windows.net/important_features/important_features")
model_metrics.write.format("delta").mode("overwrite").option("overwriteSchema", "true").save(f"abfss://{file_system_name}" + "@"+ f"{data_lake_account_name}.dfs.core.windows.net/model_metrics/model_metrics")

However in the PBI report, the datasource is looking to the /source/reporting/important_features and /source/reporting/model_metrics folders.

So when changing the datasource to point to our ADLS, the report still doesn't work unless we either point the datasource to the folders indicated by the code, or the notebook code is updated to write the files out to the reporting subfolder...

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