Cognine

Menu

Category: Retail

Categories
Retail

E-commerce platform development

Client focus

Client wanted to develop a new e-commerce platform to sell agricultural goods to farmers and purchase the farm produce.

0 M+
SKU on the platform
0 +
customer monthly customer visits
0 M+
Orders fulfilled
0 way
Sell goods and buy produce

Challenges

  • Help client enable e-commerce with the farming community to sell and maintain an online catalog of products.
  • Enable fulfillment of customer orders and an end to end solution with API enablement to integrate with others partners in the supply chain
  • Build data analytics and visualization for reports on inventory, sales and financial management.

Solutions

  • Worked with the client to define the functional solution and technical architecture of the e-commerce platform
  • A web front end and native mobile builds were generated for an omni channel experience
  • Developed secure payment gateways and seamless integration with fulfillment partners for hassle free experience

Key Benefits

  • Rapid development and deployment of platform enabled faster time to market with a unified experience
  • A fully scalable micro-services platform that fulfilled over 4 million order in the initial year of operations
Categories
Retail

Data led digital transformation

Client focus

The client is a leading retailer that operates over 1500 stores across Europe under multiple brands.

 
0 +
Retail Outlets
0 +
Data Sources
0 +
Reduction in load times

Challenges

  • The client faced challenges with disparate on-premise data systems and did not have a consolidated view of their products performance.
  • The data warehouse currently runs reports in batch mode and takes up to 20 hours for report generation.
  • Needed a technology partner who can enable near real time reporting over a cloud based data lake.
  • Implement a phased data migration approach without impacting the existing data warehouse model.

Solutions

  • Cognine worked with the client team to migrate the legacy data warehouse to Azure cloud to ensure agility and scalability of reporting architectures.
  • Data handling: Designed the cloud migration strategy by performing data profiling of all the major on-premise data sources and data warehouse systems.
  • A comprehensive data architecture was defined to enable accelerated ingestion and reduce latencies across the value chain
  • Technologies: Snowflake was chosen for hosting the data warehouse and data mart. Attunity, a cloud based replication tool was leveraged to accelerate the migration of the on-premise data to Snowflake. Power BI was chosen for visualization, dash-boarding and self service analytics.

Key Benefits

  • The new data architectures reduced the processing times from 12 hours to minutes. Usage of Attunity brought down the batch load times considerably.
  • Data science teams were provided with flexibility to access data from the analytics work-spaces.