Descriptive, Diagnostic, Predictive & Prescriptive Analytics
We deliver analytics solutions across the full maturity curve:
Descriptive Analytics
What happened?
→ Explore historical data trends and summaries to uncover business patterns and performance insights.
Diagnostic Analytics
Why did it happen?
→ Identify root causes using drill-downs, correlations, and segment analysis to support accurate problem solving.
Predictive Analytics
What is likely to happen?
→ Forecast outcomes using ML models, enabling proactive business planning.
Prescriptive Analytics
What should we do?
→ Recommend optimal actions through simulation models and AI-powered decision support systems.
ETL & Data Orchestration
Build resilient, scalable data pipelines that automate data ingestion, transformation, and delivery across hybrid environments — on schedule and on demand.
End-to-End ETL Pipelines
Design and implement robust data pipelines using tools like Pentaho Data Integration (PDI), enabling batch and micro-batch ingestion across diverse source systems (databases, APIs, flat files, etc.).
Workflow Automation & Scheduling
Coordinate multi-step data processes with orchestration platforms such as Apache Airflow, ensuring timely execution, dependency resolution, and dynamic reprocessing.
Hybrid Architecture Support
Integrate on-premise systems with cloud-native platforms seamlessly, supporting real-time, near-real-time, and scheduled data flows.
Monitoring & Alerting Frameworks
Embed logging, retry mechanisms, failure handling, and notification systems to proactively manage ETL health and ensure data delivery SLAs are met.
Data Modeling & Warehouse Architecture
Transform raw data into structured, business-aligned models using industry-proven methodologies — enabling scalable, governed, and analytics-ready data environments.
Conceptual, Logical & Physical Modeling
Design data models at every abstraction level — from business-oriented conceptual diagrams to normalized logical schemas and performance-tuned physical structures.
Dimensional & Vault Architectures
Implement star, snowflake, or hybrid (Data Vault + Kimball) architectures tailored to reporting, auditability, and historical traceability requirements.
Layered Data Warehouse Design
Establish a multi-zone architecture (Staging, Integration, Semantic Layer) that decouples transformation logic, increases reusability, and aligns with data governance practices.
Tool-Agnostic Modeling Expertise
Deliver modeling standards that integrate with a wide range of platforms — including SAP, Oracle, SQL Server, PostgreSQL, and cloud-native DWHs like Snowflake or Redshift.
Business-Aligned Data Structures
Collaborate with business stakeholders to define subject-area driven models that map to real-world processes, KPIs, and decision needs.
Data Visualization & Storytelling for Insight-Driven Action
Empower decision-makers with intuitive, interactive visuals that reveal trends, surface anomalies, and support scenario-based planning.
Interactive Dashboards
Dynamic and responsive dashboards built with Power BI, Tableau, and Vispeahen — enabling real-time monitoring, KPI tracking, and executive reporting.
Geospatial Analytics
Unlock location-based insights with shapefiles, satellite data, and IoT signals to improve operations, logistics, and infrastructure planning.
Scenario Modeling & Simulation Interfaces
Build visual “what-if” models that enable forecasting, resource planning, and contingency testing with maximum clarity and flexibility.
Data Quality & Testing Frameworks
Ensure data reliability and trust with automated validation, anomaly detection, and test-driven pipeline development — embedded directly into your data workflows.
Automated Data Quality Rules
Define and enforce rule-based validations (e.g. null checks, domain constraints, threshold rules) across staging and DWH layers — ensuring data accuracy before it reaches BI layers.
Anomaly Detection & Monitoring
Set up automated monitors to detect unusual trends, missing data, or outliers using statistical thresholds, volume tracking, and historical comparisons.
Test Case Management in ETL
Embed testing logic directly within ETL pipelines (e.g. row count matching, reconciliation checks, transformation logic validation) to catch issues during load time.
Data Profiling & Baseline Checks
Utilize profiling tools to capture data distributions, cardinality, and type integrity — helping identify structural changes or schema drift early.
Alerting & Issue Escalation
Integrate alerting systems (email, Slack, dashboards) to notify data owners and trigger escalation protocols when quality issues are detected.
AI & Machine Learning Capabilities for Predictive and Cognitive Insights
We develop intelligent, scalable models that transform raw data into predictive insights, enabling smarter business decisions across industries.
Supervised Learning
Predict customer churn, credit risk, or asset failure → Train models on labeled data to deliver targeted risk scoring, demand forecasting, and proactive customer retention.
Unsupervised Learning
Customer segmentation, anomaly detection → Discover hidden patterns and customer groups to improve personalization, fraud detection, and operational monitoring.
Natural Language Processing (NLP)
Text mining, sentiment analysis, document classification → Extract structured meaning from unstructured text to enhance customer feedback loops, automate documentation, and power conversational AI.
Computer Vision
→ Enable automated understanding of visual content to streamline document workflows, improve safety monitoring, or analyze geospatial data.
Data Governance & Metadata Management
Establish trust and transparency in data with governance frameworks that ensure accountability, quality, and compliance across the data lifecycle.
Metadata Cataloging & Lineage Tracking
Map and trace data flows across systems using OpenMetadata, enabling full visibility of upstream and downstream dependencies.
Data Ownership & Stewardship
Assign clear ownership to data assets, define custodianship roles, and maintain accountability through role-based access control and responsibility matrices.
Policy-Driven Access Control
Enforce access rights based on data sensitivity levels and organizational roles, ensuring both usability and compliance with security regulations.
Business Glossary & Semantic Layer
Unify business terminology with technical metadata to empower users with consistent, trusted understanding of key data concepts.
