Project Description

Project Description

Customer:
US based Analytics company partnered with Stanra for Architecture, Design, Development, and implementation of a subscription based Data analytics platform, catering to a sunrise industry for all US states

Challenge:
Business model is to gather high volumes of data across various verticals, multiple states, from private and public data sources, in various data formats and data covering weather data, lifecycle related data and enterprise performance data for the industry. Further the data needs to be stored, cleansed, curated and enriched for further analysis and transformation. The data is to be visualised through the front end web application using maps, charts, graphs and tables. The portal is for B2B and B2C customers ranging from basic user to premium subscription users. The application is eventually planned to be on web and mobile devices.

Accomplishments:

  • First phase was to build the end to end engine on AWS platform using native tools. Selected one state, few data sets and sample charts, maps, graphs and tables for visualisation. Currently in full-fledged development phase of the product
  • Front End
    • Development of UI and application comprising of screens, maps, charts across several menu options using various charting tools, maps. AWS QuickSight implementation on the anvil.
    • Access control and user management using Cognito
    • Comprehensive subscription model starting with free user to premium subscriber
    • Payment gateways
    • Plans to implement mobile applications as well.
  • All data to be provided on demand using APIs
  • Backend Data Engine
    • Huge volumes and types of data:
      • Data gathered from various sources, private/public sources, Paid/free sources, various formats and frequencies of publication
      • Data from various verticals like growers, pharma companies, dispensaries, laboratories, transporters etc
      • Covers comprehensive weather data from growers, product lifecycle data and enterprise data on companies related to the industry, and data from various equipment used in the industry.
      • Lot of data gathered using sophisticated Web scraping methods
    • Data Processing
      • Layers of data curation, enrichment, transformation and analytics
      • Development of Analytics Module for continuous aggregation, summarization, correlation and regression
      • Architecture and design of Server on microservice and AWS Lambda Architecture

Technology – AWS Glue, S3, AWS RDS, Athena, Arora, QuickSight, Microservices, AWS Lambda, React Native, React JS, Java 8 Python, Cognito,