Automate data collection for faster business decision-making. Eliminate data discrepancy issues by building an end-to-end data pipeline and data warehouse
The Results
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The Execution
The customer is a leading Direct-To-Consumer (D2C) player that invests in developing e-commerce capabilities for digital-first brands in the beauty, fashion, and personal care sector.
The company was previously collecting data from their managed brands manually which resulted in data inaccuracies and delays in getting business insights for decision making activities. They also had no visibility on data from their managed brands ecommerce platforms and marketplaces.
ADA helped to build and end-to-end data pipeline and data warehouse on Amazon AWS to gather insights from many different data sources for sales, returns, inventories, and finance. ADA also built bespoke API connectors for various eCommerce platforms to enrich collected data.
The new data warehouse helped to provide up to date and accurate data for data analytics and data science team to make business intelligence dashboards and construct ML models.
The Approach
We observed close alignment between the actual sales and predicted values for Y2023, with difference of only 6.8%: