Data Intelligence & Advanced Analytics

Data Modeling

Architecture and Strategy of Cognitive Assets

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Overview

The architectural blueprint upon which analytical integrity is built. We standardize data assets so the infrastructure answers the operational and strategic questions of the business, consistently.

What we build

  • Conceptual model

    The "what" of the system: high-level entities (vendors, products, transactions) and their relationships, as the communication tool with stakeholders.

  • Logical model

    Attributes, primary and foreign keys, normalization: integrity rules that prevent redundancy and information anomalies.

  • Physical model

    The technical implementation: data types, partitioning and indexing for RDBMS or NoSQL engines.

  • Design methodologies

    Normalization for transactional systems, star and snowflake schemas for OLAP, Data Vault 2.0 for massive scalable environments.

  • BI optimization

    Indexing and partitioning that cut response times from seconds to milliseconds; structures end users can navigate without engineering help.

  • Consistency of truth

    One definition per metric: "Net Revenue" is calculated the same way across every department.

Part of Data Intelligence & Advanced Analytics: orchestrating mathematical precision for strategic decision-making. Engaged as part of a scoped project after a diagnostic conversation.

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