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A retailer with hundreds of locations providing both prescription and non-prescription eye ware along with optician services.
Customer had a monthly forecasting processes that involved various manual steps using Excel worksheets and models. This process was time consuming and had high rate of deviation from actual targets. Customer kicked off an initiative to build an automated advance analytics solution that would be faster, flexible and have a high rate of accuracy. VNB advance analytics team was chosen by the customer to implement this key predictive analytics solution.
After going through customers current manual process, VNB advance analytics team proposed an architecture with automated data ingestion, data preparation, self-learning predictive models and delivery of predictive outputs via PowerBI share and collaborate features. Following were the important activities performed during the project: - Followed Data Science Process Lifecycle (TDSP) for the end to end implementation - Prepared data sets for Sales, Promotion, Store Remodeling, Workforce(Full Time/Part Time) and Products. - As part of the first data collection process all the raw data were stored in Azure Blog Storage. Data were later feed to Azure Machine Learning flow where they were cleaned and fed to actual model for training and prediction. - Output published through Web Service which later utilized in PowerBI and other application - The implementation of the retail dashboard Power BI solution
VNB’s BI team conducted a thorough review of the customer’s data landscape and proposed a data gateway architecture to handle the multiple data sources such as SAP data sources, Legacy Oracle DW, and SQL server.VIEW DETAILS
VNB provided a comprehensive solution by creating Opex and Capex reports. These reports enabled the customer to gain real-time financial insights, effectively manage expenses, and optimize resource allocation.VIEW DETAILS