45% Faster Reporting, 60% Lower Cost
Posh Peanut runs a global children’s and family apparel business across marketplaces, storefronts, and point-of-sale. Rudder Analytics unified 17+ data sources into one governed warehouse and gave every department reporting it can trust.
One Version of the Numbers
Posh Peanut sells children’s clothing, matching family apparel, and accessories worldwide, across a network of physical and virtual locations.
Seven functions needed the same precise, current analytics: Finance, Marketing, Sales, Inventory, Operations, Distribution, and Merchandising. Each consumed it differently — through Tableau, scheduled exports, or maintained Google Sheets.
Rudder Analytics built the data foundation. An automated ETL/ELT framework feeds a secure BigQuery warehouse, dimensional models make queries fast, and blended dashboards serve every team from one governed layer.
Precision Across Every Function
The business needed accuracy across supply chain, commerce, and finance, delivered to seven departments. Each worked in its own tools, and the numbers needed one shared definition.
Supply-Chain Blind Spots
Cycle counts, bin transfers, inventory movements, and AP/AR lacked the precision analytics that supply-chain management needs.
Distributed Inventory
Sales orders, purchase orders, and customer and supplier shipments spanned a global network of physical and virtual locations.
A Fragmented Marketplace View
Listings, sales, and revenue sat across many marketplaces and point-of-sale channels, with no consolidated report.
Seven Teams, One Truth
Finance, Marketing, Sales, Inventory, Operations, Distribution, and Merchandising each needed reports built for their own decisions.
Three Ways to Consume Data
Stakeholders needed Tableau views, scheduled and on-demand exports, and maintained Google Sheets, all reconciled to one source.
Sources Out of Sync
Operational, commerce, advertising, and analytics data arrived in different shapes and cadences, so figures rarely lined up.
One Governed Warehouse
An automated ETL/ELT framework on Talend Enterprise feeds a secure BigQuery warehouse. Dimensional models make reporting fast, and blended dashboards reach each team in the tool it already uses.
17+ Systems
- Fulfil ERP (operations)
- Shopify & commerce apps
- Meta, Google, Amazon, TikTok ads
- GA4 & Segment analytics
BigQuery Warehouse
- Talend ETL/ELT pipelines
- Batch, parallel, snapshot, incremental
- Dimensional hybrid schema
- Dataform SQLX · managed SCD
Every Team
- Tableau executive dashboards
- Automated Google Sheets
- Scheduled & on-demand exports
- One reconciled set of numbers
Automated ETL/ELT Framework
A production-grade ETL/ELT architecture on Talend Enterprise ingests ERP, commerce, advertising, and analytics sources through their APIs on automated pipelines.
Load Strategy by Volume
Batch loads handle on-demand data, parallel multi-thread execution moves high-volume synchronous data, daily snapshots hold consistency, and incremental loads keep the warehouse fresh at low cost.
Warehouse on GCP VPC
ETL runs on Google Cloud Compute inside a GCP Virtual Private Cloud, with subnet, IP, routing, and firewall controls. BigQuery handles structured and unstructured data at scale.
Fast, Accurate Queries
A hybrid dimensional schema with fact and dimension tables, Dataform SQLX transforms with indexing and partitioning, and managed Slowly Changing Dimensions preserve history.
Complete Data Capture
Python web-automation extraction covers sources without APIs, so no commerce or marketing data goes uncaptured.
A View for Every Team
App Script automates Google Sheets dashboards for Sheets-only teams. Tableau dashboards blend inventory, sales, revenue, marketing, and demand-planning insight for leadership.
Faster, Cheaper, Consistent
Unifying every source in a governed BigQuery warehouse lifted data quality and consistency. Raw-data-to-report time fell 45%, and analytics and reporting spend dropped 60%.
| Metric | Before | After | Impact |
|---|---|---|---|
| Raw-data-to-report time | Manual assembly | 45% faster | −45% |
| Analytics & reporting cost | Baseline | 60% lower | −60% |
| Data sources | Fragmented, siloed | 17+ unified | one warehouse |
| Reporting effort | Heavy manual work | Automated pipelines | much reduced |
| Inventory decisions | Limited visibility | Actionable supply-chain insight | optimized levels |
| Distribution-center ops | Manual, time-intensive | Automated reporting | faster turnaround |
Posh Peanut now runs on one governed source of truth. Supply chain, commerce, and finance reporting reconcile automatically, and each department gets it in the format it works in.
Data and AI for Brands Outgrowing Their Stack
Rudder Analytics builds that platform — from the first pipeline to reporting a board can act on.
