Digital Data Processing & Prediction
Tech Stack
D2P2 (Digital Data Processing & Prediction) is a real- time social media tracing and sentiment analysis system, designed to help enterprises, both private & public. Built to monitor and interpret digital engagement, sentiment, public opinion, and online narratives across platforms like Facebook, Instagram, Twitter (X), YouTube, & Google News and other platforms.
The Business Challenge
Organizations, and many heavy asset industries often operate in silos – old, outdated IT infrastructure that is siloed or isolated from one another and lacks any data-sharing or communication between systems. This meant the teams struggled with:
- Manual monitoring and collection of large quantities of content across multiple platforms.
- Delayed insights into emerging trends and sentiment leading to fragmented workflows and reactive decision-making.
- No centralized audit trail, hindering decision making and misinformation containment.
- Lack of automation, relying on third-party tools and static reports for sentiment & trend analysis.
Our Approach
We mapped end to end use cases and structured the system into use-case-driven modules with specific goals to align with roles such as analysts, decision-makers, and IT administrators.
D2P2 emphasizes automation, intuitive visualization, and proactive alerts with integrated sentiment analysis and Power BI reporting underpinnings.
D2P2 Features and Capabilities
D2P2 consists of 12 modules with the following key capabilities:
- Dashboard: Interactive visual summaries showing real-time trends, keyword spikes, profile activity, and regional insights.
- Profile Management: Tracks 1,000+ social handles, engagement metrics, sentiment, and influence over time.
- Keyword & Hashtag Tracking: Extracts public posts using pre-set terms like #Election2024, with historical sentiment comparison.
- District Mapping: Heatmaps and sentiment overlays allow users to correlate public opinion with geography.
- Google Search & Website Monitoring: Captures articles, search queries, and trending narratives from indexed websites.
- Image Search & OCR Engine: Identifies image reuse, extracts embedded text, and maps visual misinformation.
- Mobile Number Insights: Connects profiles to mobile numbers using connected apps like Truecaller, enriching person-level intelligence.
- Sentiment Engine: Uses NLP to classify public sentiment across languages as Positive, Negative, or Neutral.
- Power BI Integration: Presents district-wise KPIs, keyword reach, media impact, and influencer summaries.
- Report Analytics & Automation: Generates scheduled reports (daily/weekly/ monthly) and alerts based on spike thresholds.
- Alerts & Notification System: Flags emerging narratives, harmful content, or reputation threats in real time.
System Architecture / Tech Stack / Development Tools
- Frontend: HTML, CSS, JavaScript
- Backend: Java
- Database: MySQL
- Analytics: Power BI, AI/ML
- Cloud Infrastructure: AWS
- Security: SSL, Cloudflare/CloudFront
- Backup: Weekly/monthly with full recovery options
- APIs: RESTful services for integrations, automated fetches, and external dashboard syncs
Workflow Automation
- Data Collection: API and scraping from social platforms, Google, websites, and OCR image uploads.
- Processing Layer: NLP-driven sentiment scoring, keyword tagging, district classification, and trend detection.
- Storage & Access: Indexed datasets, structured APIs, and historical data retention for future modeling.
- Visualization: Live dashboards and scheduled reports tailored to user role and region.
- Alert Engine: User-defined thresholds trigger push/email/SMS alerts for critical changes.
Impact
- 500K+ posts processed weekly across platforms with over 85% automation.
- +30% faster misinformation containment, with visual and text-based media tracked simultaneously.
- Unified and Real-Time dashboard used across 5 departments, reducing duplication and fragmentation.
- Power BI Visual Reports increased adoption across the board
- Data-informed decision-making for PR, field response, and media engagement.
Roles Benefited
- Analysts: Transitioned from manual reports to AI-powered dashboards and alerts.
- Marketing Teams: Gained early visibility into narrative swings and influencer activity.
- Policy Planners: Used district-level insights for targeted public messaging.
- IT/Dev Teams: Benefited from robust, API-driven architecture with secure access and integrations.
- Field Units: Acted faster on media-triggered disruptions thanks to mobile- accessible alerts and sentiment trends.
What It Means for Other Organizations
D2P2 demonstrates how structured automation can replace fragmented media monitoring. With real-time data collection, AI-powered insights, and secure cloud-based architecture, organizations can:
- Detect sentiment shifts and misinformation early.
- Reduce reporting delays and improve stakeholder visibility.
- Align responses across regions and channels using live insight