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Web Platform for Commodity Trading Data Aggregation

Services Covered:

Web Application Development • Data Engineering • Data Integration
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Industry
Industry

Financial Services

Duration
Duration

25 months

Budget
Budget

10K - 49K

Start Date
Start Date

1 January 2021

Team Size
Team Size

Confidential

Engagement Model
Engagement Model

Offshore

Project Capability Score (PCS)

gauge meter
80/100
Strong

Project Capability Score (PCS) estimates how capable August Infotech is of successfully delivering a project like this, based on its past experience, track record, and ability to handle similar work. Learn more about PCS

Client

Confidential

mapNew York City, United States of America

Project Summary

August Infotech is building a web platform for a small commodity trading company that aggregates and processes data from multiple sources and formats for analysis and decision-making. The platform ingests files, emails, web sources and databases and transforms them into usable formats. The client praises August Infotech's metrics tracking, trend analysis and flexible, accommodating team during this ongoing engagement.

Key Challenges

  • Data arriving from various sources and in different formats (Excel, CSV, websites, email, PDF, database, zip)
  • Cumbersome manual manipulation and conversion of disparate data formats
  • Difficulty analyzing data spread across incompatible formats
  • Inability to take the right business decisions due to fragmented data

Project Deliverables

  • Website
  • Django backend
  • Data import and processing pipelines
  • Web scraping modules
  • PostgreSQL database
  • AWS deployment (ECS, EC2, RDS)
  • Docker containers and CI/CD workflow

Project Solution

August Infotech developed a web platform that ingests and normalizes data from multiple sources (Excel, CSV, websites, email, PDF, databases, zip files) and converts them into analysis-ready formats. The backend was implemented in Python (pandas, NumPy) with Django, scheduled jobs via Celery and caching with Redis; web scraping used BeautifulSoup; data storage used PostgreSQL/RDS. The frontend used React.js; deployment utilized Docker and AWS services (ECR, ECS, EC2, RDS) with a Git-based CI/CD workflow.

Project Outcome

  • Able to measure, track, and record various metrics for facilitating enterprise-wide enhanced decisions
  • Able to identify opportunities
  • Smartly reduce the learning curve
  • Directing actions based on trends which in turn help to define goals
  • Flexible, accommodative team with effective daily scrum workflow

Platforms

  • WebWeb
  • CloudCloud

Tech Stack

  • PythonPython
  • DjangoDjango
  • React.jsReact.js
  • PostgreSQLPostgreSQL
  • Amazon Web Services (AWS)Amazon Web Services (AWS)
  • RedisRedis
  • Beautiful SoupBeautiful Soup
  • DockerDocker
  • MatplotlibMatplotlib

Client Endorsement

Overall Review Rating

5star

Timeliness

Cost Rating

Willing to Refer

Quality of Deliverables

“The project is ongoing, but the client commends August Infotech's ability to measure and track metrics to facilitate better decisions. The flexible team remains accommodating of the client's needs. Their ability to analyze trends and identify opportunities for improvement makes them stand out.”

Anonymous

Quantitative Analytics Director

Note: This endorsement is based on publicly available client feedback from external review sources.

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