The customer is a wellness company that makes secure cosmetic, skincare, baby care, and cleaning items.

AiRo Helped the Client in Designing a Complete Data Solution for their E-Commerce Platform.

The Client Wanted Assistance in Managing Company Data

Unquestionably, the foundation of any smart business choice is solid data. Making data-informed judgments quickly requires the combining of data from various sources into a unified view. Our team was hired by the client to assist them in managing their company’s data, which included gathering information from online stores for data warehouse and reporting.

AiRo Helped The Client in Designing a Complete Data Solution for their E-Commerce Platform

AiRo specifically took on a series of tasks to design and deploy the Ecommerce data management solution. Our experts utilized ETL operations by combining the company’s data from several sources into a single spot. To create a seamless experience for the internal team our experts had to transform the data along the route into a correct structure to make it more appropriate for reporting needs.

Moreover, the analytics team needed their reports in CSV format for easy accessibility.

AiRo worked closely with the client’s internal teams to determine the optimum reporting format with the product teams and examine new data structures coming-in. Finally, AiRo established data transformation guidelines according to client needs to streamline processes.

● AiRo designed a solution to use a number of ETL scripts to load data into the Apache Hive data warehouse from various data sources like Google BigQuery and Amazon S3.

● Our experts programmed several SQL scripts for Redshift to generate CSV reports with information on online orders, quantities, prices, etc.

The Client Recorded Significant Gains Post Deployment

● When necessary, the analytics teams can use the exported CSV reports to study the audience, their behavior, and their preferences in order to produce insightful analytics results.

● It is a lot simpler to move the data into separate storage, rearrange it for quick analysis and reporting, and export it in a legible format thanks to the ETL and SQL scripts than it would have been if it had been done manually.