We helped a leading ecommerce retailer trial a centralised data operations team to improve efficiencies and reduce incident rates
A leading Indian e-commerce platform in fashion, beauty, and lifestyle operated with fragmented data ownership across departments such as marketing, finance, and insights. Each team requested different datasets, commercial metrics, clickstream data, storefront analytics, creating a constant stream of ad hoc data pipeline requests.
Engineering teams were overwhelmed with building, maintaining, and troubleshooting these pipelines, leading to long turnaround times for resolving data issues and a high volume of recurring incidents. The lack of centralized triage and standardized processes created inefficiencies, duplicated effort, and inconsistent data quality across teams.
The client needed a more structured data operations model to reduce incident volume, speed up response times, and free engineering resources to focus on improving core data integrations and platform reliability.
ADA helped define and trial a centralized data operations team that would triage and manage all departmental data issues, perform initial assessment and route analysis findings to the relevant engineering teams.
ADA also improved the data process and minimized incident rates by building self-healing data pipelines and reporting on data accuracy. ADA also put in place data pipelines and business logic for derived and aggregated datasets orchestrated using Azkaban; a batch workflow job scheduler that allows for tracking and monitoring of the data workflows.
