Build and Deploy a web application for Spend Optimization Tracker
• The solution drives planning and optimization of various investments (marketing, trade) that brands make to improve outcomes like sales, new customers, leads etc. and visualize on a web application.
• It provides following specific insights/tools for planners:
• ROI on various investments
• Forecast outcomes for future mix of investments
• Optimize the mix to maximize the business outcome
• It leverages outcome data (sales etc.) and spend data by each activity (TV, Print, Digital, Trade) to build machine learning models to quantify the relationship between them. It further uses optimization module to generate an optimal investment plan accounting for all the relevant constraints.
The data engineering services involve the below scope, 1. Design the pipeline flow and development of the ETL Pipeline using Azure Components such as Azure Data Factory, Azure Data Bricks, Azure Logic Apps and Azure Active Directory 3. Build a data ingestion layer using Azure Data Factory to extract data from data sources such as FTP, Rest API etc. into Azure Data Lake Storage 4. Build data transformation logic in Azure Databricks implementing the required Business Rules and store the cleansed data in Sql Server and leverage Azure Logic Apps for email notification on the execution status of the pipeline such as Success, Failure etc.
Von Tiger Analytics
Analytics | AI + Machine Learning | Data Platform