Modern Data
& Analytical
Platform

for a B2C Retail Company

#Data Management
#Data
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Duration

The project spanned over
4
months
from initial assessment to full implementation and optimization.

client

Our client is a
B2C
retail
company based in San Francisco, California, operating multiple stores across the United States.

Tools and Technologies

tools
tools
tools
tools

Project Overview

This rapidly growing business required efficient data management and analytical solutions to unlock growth, drive strategic decision-making, and increase operational efficiency. The goal was to establish a robust data framework supporting descriptive and predictive analytics, actionable reports and dashboards, and scalable data processing capabilities.

Challenge

Current data platform has become outdated and unable to support client’s growing needs and was in need of a redesign. Operational Postgres DB was supporting analytical needs, no CDC tool was in place leading to lots of unnecessary and often manual work by Data Engineers and Analysts, as well as limited ability perform deep dive research and modeling.

Solution

After conducting a POC, we decided to implement a modern data platform with a warehouse, CDC tool, and a transformation layer as core components. Proposed architecture was designed to be flexible and scalable while supporting both current and future business objectives.

Implementation

01

Data Repository:

  • Evaluated various options with the client and collaboratively decided on Snowflake as the most suitable solution.
  • Selected Snowflake for its «set and forget» administration, support for semi-structured data, and secure data-sharing features.
02

Data Ingestion:

  • Implemented Fivetran for seamless data synchronization from multiple databases, including ERP systems, Salesforce, Google, Facebook, and more.
  • Integrated records from various microservices and external sources into Snowflake.
03

Transformations:

  • Took advantage of Fivetran’s built in dbt capability for advanced data transformations, creating data marts and summaries for business-critical data.
  • Provided ready access to ERP data, enabling the development of sophisticated applications and models for marketing, product, and logistics teams.
04

Metrics, Semantics, and BI:

  • Created a single semantic layer to unify and enable common understanding of metrics and KPIs.
  • Quickly built user friendly reports and dashboards for multiple teams and stakeholders.
  • By having the right solution in place, introduced self-serve BI as an option for power users

Architecture

Architecture
Results

Operational
Efficiency

Empower decision-makers to work more effectively and efficiently by delivering clear, actionable business insights. Achieve immediate ROI by concentrating efforts on areas with the greatest potential.

Collaboration and Decision-Making

Significant reduction in performance bottlenecks and improved scalability.

Predictive Analytics

Development of sophisticated models for predicting customer lifetime value (LTV) and generating personalized recommendations.

Data Utilization

Enhanced ability to ingest and transform large volumes of data to support all product, marketing, and other company initiatives.

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