Client Background
Client: A leading IT & tech firm in the USA
Industry Type: IT
Products & Services: IT Consulting, IT Support, SaaS
Organization Size: 200+
The Problem
In today’s fast-paced digital environment, automotive brands and dealerships demand personalized and dynamic online experiences that reflect their unique identities. Static web pages or dashboards that cannot be customized limit engagement, fail to showcase specific brand elements, and lead to lost opportunities. A dynamic system that can adjust each page’s look and feel based on the dealership or brand’s unique requirements is essential for maintaining consistency and increasing customer engagement.
Our Solution
PDF to Dashboard: Streamlining Financial Statements is a comprehensive solution designed to create a fully dynamic and customizable online experience. Key features include:
Dynamic Customization:
Each page or section of the dashboard can be personalized according to the brand’s identity and the dealership’s preferences. Logos, color schemes, and layout adapt dynamically to reflect specific branding guidelines.
Flask and React-based System:
Our dashboard employs a robust architecture using Flask for the backend and React with ApexCharts for the frontend. This combination ensures a seamless data flow, efficient processing, and a responsive user interface.
Financial Statement Integration:
With over 40 financial formulas, the system provides insights into key metrics like gross profit and fixed operations. The metrics are dynamically generated based on the dealership’s financial data extracted from PDFs via PDF Plumber and Optical Character Recognition (OCR) technology.
Pickle Object Storage:
Calculated variables are stored as pickle objects in a MongoDB database, ensuring efficient retrieval and manipulation of data.
Cloud Hosting on AWS:
The solution is securely hosted on an AWS instance, providing scalability and availability for multiple dealerships and brands.
Backend (Flask):
Endpoints: Provide RESTful APIs for data extraction, processing, and storage.
Data Extraction Module: Uses PDF Plumber and OCR for extracting data from PDF statements.
Data Calculation Module: Calculates financial metrics using over 40 built-in formulas.
Data Storage: Stores processed data as pickle objects in MongoDB.
Frontend (React and ApexCharts):
User Interface: React-based UI provides a dynamic and responsive user experience.
Dashboard Personalization: Allows users to personalize dashboards by changing logos, colors, and layouts dynamically.
Visualizations: ApexCharts generates dynamic graphs and charts based on financial data.
Cloud Infrastructure (AWS):
Hosting: The entire application is hosted on an AWS EC2 instance.
Database: MongoDB database hosted on an AWS DocumentDB instance for scalable storage.
Security: AWS security protocols ensure secure data transfer and storage.
Deliverables
Dynamic Dashboard:
A fully customizable dashboard that allows brands and dealerships to personalize each page according to their unique requirements.
Real-time financial metrics visualized through dynamic graphs and charts.
Data Extraction Module:
An automated system that extracts financial data from PDF statements using PDF Plumber and OCR technology.
Financial Metrics Calculation Module:
A library of over 40 formulas for calculating gross profit, fixed operations, and other key financial metrics.
Backend and API Documentation:
Detailed API documentation for seamless integration and data management.
Training and Support:
Training sessions for dealership staff to use the system effectively.
Ongoing technical support and updates.
Tech Stack
Tools used
REACT
PYTHON
FLASK
MONGODB
VUEXY TEMPLATE
REACTSTRAP
Language/techniques used
PYTHON
Models used
Optical Character Recognition (OCR) Model:
Utilized to extract text from PDF files, the OCR model is integral to converting scanned documents into machine-readable data. We use pre-trained OCR models optimized for financial statements to ensure accurate and efficient data extraction.
Custom Financial Calculation Models:
These models contain a collection of formulas specifically tailored for analyzing automotive financial statements. They are used to compute metrics like gross profit, fixed operations, and other key financial indicators. These models adapt dynamically to each dealership’s data structure.
Skills used
Backend Development:
The backend is built using Flask, which handles data processing, API management, and ensures secure data storage. Knowledge of Python, Flask, and RESTful API design was essential for developing robust data processing and serving endpoints.
Frontend Development:
The frontend is built using React and ApexCharts, providing a dynamic and user-friendly interface. Skills in JavaScript, React, and data visualization tools were necessary for creating a customizable dashboard with rich data visualizations.
Data Extraction and Processing:
Expertise in PDF Plumber and OCR technologies was leveraged to extract accurate data from various PDF formats. Advanced data manipulation and cleaning were required to ensure data consistency across different dealership documents.
Database Management:
Storing financial metrics in MongoDB as pickle objects required skills in data modeling and optimization. Understanding of document-based storage and efficient querying techniques was crucial.
Cloud Infrastructure:
Setting up and managing the AWS instance required knowledge of cloud computing, security protocols, and scalable hosting solutions.
Databases used
MONGODB
Web Cloud Servers used
AWS
What are the technical Challenges Faced during Project Execution
Data Inconsistency Across PDFs:
Financial statements from different brands and dealerships varied significantly in layout and data structure, making it difficult to standardize data extraction.
Text Recognition Errors in OCR:
The Optical Character Recognition (OCR) process sometimes struggled to accurately interpret certain scanned documents, leading to errors in data extraction.
Real-Time Data Processing:
The need for real-time data processing to generate up-to-date financial metrics placed considerable pressure on system architecture, impacting performance.
Dynamic Frontend Personalization:
Adapting the dashboard dynamically to each dealership’s branding required a highly modular frontend design.
Scalability and Security:
Ensuring the system was secure and scalable on AWS while managing sensitive financial data was a significant challenge.
How the Technical Challenges were Solved
Data Inconsistency Across PDFs:
We implemented flexible parsing rules and custom extraction logic using PDF Plumber. By mapping key data points dynamically based on keywords and positions, we could reliably extract relevant information.
Text Recognition Errors in OCR:
We enhanced OCR performance by training the model specifically on sample financial documents, improving recognition accuracy. We also incorporated post-processing validation checks to identify and correct common errors.
Real-Time Data Processing:
We optimized the backend by implementing asynchronous data processing using Flask and Python’s concurrency features. This enabled real-time data calculations without blocking the primary data extraction process.
Dynamic Frontend Personalization:
We modularized the frontend using React components, allowing each dealership to customize their branding independently. Components like logos, colors, and layouts were made configurable through a simple dashboard.
Scalability and Security:
The AWS instance was secured using VPC, IAM, and other standard protocols. We utilized DocumentDB for MongoDB compatibility and implemented automated backups to ensure data integrity and scalable storage.
Business Impact
Increased Efficiency:
Dealerships can now analyze financial performance more efficiently, reducing manual work and errors by automating the data extraction and reporting process.
Enhanced Customization:
The dynamic dashboards provide a personalized user experience, allowing dealerships to reflect their unique branding and business priorities.
Data-Driven Decision-Making:
Real-time financial insights enable dealerships to make strategic decisions quickly, improving profitability and operational efficiency.
Compliance and Transparency:
With accurate data extraction and visualization, dealerships can ensure compliance with financial regulations while providing transparent reports for stakeholders.
Scalable Solution:
Hosted on AWS, the system can easily handle an increasing number of dealerships, adapting to the growing demand for dynamic dashboards.
Project Snapshots
Project website url
https://my.dealerdash.ai/login
Summarize
Summarized: https://blackcoffer.com/
This project was done by the Blackcoffer Team, a Global IT Consulting firm.
Contact Details
This solution was designed and developed by Blackcoffer Team
Here are my contact details:
Firm Name: Blackcoffer Pvt. Ltd.
Firm Website: www.blackcoffer.com
Firm Address: 4/2, E-Extension, Shaym Vihar Phase 1, New Delhi 110043
Email: ajay@blackcoffer.com
Skype: asbidyarthy
WhatsApp: +91 9717367468
Telegram: @asbidyarthy
