Data Analytics

• Discovery & Planning:
  • ✓ Understand your business KPIs and define measurable objectives.
  • ✓ Assess available data sources and formats, including Parquet, CSV, and SQL.
• Data Engineering & Modeling:
  • ✓ Preprocess large datasets using Pandas and Numpy.
  • ✓ Utilize Parquet for efficient storage and DuckDB for fast querying of local or cloud-stored analytics data.
  • ✓ Build predictive and classification models using Scikit-learn.
  • ✓ Automate tasks using Airflow for seamless, repeatable data workflows.
• AI-Driven Insights & Visualizations:
  • ✓ Generate saved queries for ongoing analysis.
  • ✓ Use animated charts and drill-down tables for clearer interpretation.
  • ✓ Build modern dashboards using React.js, Plotly, and D3.js.
• Validation & Testing:
  • ✓ Test models using industry-standard metrics.
  • ✓ Validate data consistency using DuckDB and workflow logs via Airflow.
• Deployment & Support:
  • ✓ Deploy solutions across cloud, local, or integrated CRMs.
  • ✓ Optimize query performance with DuckDB, ideal for in-memory analytics.
  • ✓ Provide ongoing monitoring and scaling with Airflow + Parquet pipelines.

Technologies Behind Our Data Analytics Solutions

We use a cutting-edge stack designed for performance, scalability, and insight delivery:

• Languages & Libraries: Python, Numpy, Pandas, Scikit-learn
• Data Formats & Engines: Parquet, DuckDB, CSV, Excel
• Workflow Orchestration: Airflow for automation and scheduling
• Visualizations: Plotly, D3.js, React.js-based custom dashboards
• AI/NLP: Sentiment analysis, NER, keyword extraction, and summarization
• Storage & Querying: Supabase, local files, and high-performance in-memory engines like DuckDB

Ongoing Support & Scaling

We ensure your analytics infrastructure evolves with your business:

• Real-time Monitoring: Via Airflow dashboards
• Query Optimization: Using DuckDB for blazing-fast results
• Parquet Conversion Pipelines: To improve storage and I/O efficiency
• Dashboard Enhancements: Based on user feedback and changing KPIs
• Model Retraining: To reflect new business patterns