Empirical Intelligence & BI Cockpits

Data Management & Business Intelligence

Transform fragmented, siloid enterprise records into an infallible single source of executive truth. Modern cloud lakehouses, sub-second BI cockpits, real-time CDC streams, and predictive machine learning models.

Contact UsAll Services

Data Management

Bring scattered data into a single source of truth

Most enterprises do not suffer from a lack of data — they drown in it. Financial transactions in one core ledger, operational volumes in isolated spreadsheets, customer journeys locked inside SaaS tools, and logistics logs in legacy servers. When executive leadership demands consolidated EBITDA, cash runway, or cohort margins, manual reporting takes weeks of spreadsheet triage. WAGONN permanently eliminates reporting blindness.

We architect unified enterprise lakehouses, stream live transaction mutations via Change Data Capture (CDC), and deliver sub-second executive BI cockpits. From inventory turnover and supplier payment aging to customer lifetime value and predictive demand forecasting; our decision support systems provide leadership with complete empirical clarity to navigate market volatility.

Areas of expertise

Our Data Management and BI Practices

From petabyte-scale lakehouses to real-time CDC streams, sub-second OLAP cockpits, sovereign data governance, and predictive MLOps: empirical certainty without compromise.

  • Modern Data Lakehouse & Warehousing

    Architecting unified modern lakehouses on Snowflake, Databricks, or ClickHouse using open Iceberg formats to permanently eliminate contradictory metrics across departments.

    • Petabyte-Scale Columnar Compression and Storage Optimization
    • Version-Controlled, Modular, and Test-Driven Modeling via dbt
    • Open Table Formats (Apache Iceberg) Guaranteeing Zero Vendor Lock-in
    100+ TBConsolidated Storage

  • Real-Time Streaming & Change Data Capture (CDC)

    Non-intrusive stream pipelines reading transaction logs (WAL/Binlog) asynchronously via Debezium and Kafka, replicating state to data lakehouses in sub-500ms with zero DB locking.

    • Sub-500ms End-to-End Event Replication Latency to Storage
    • Zero Transactional Lock Overhead on Production Core Databases
    • Schema Registry Contracts and DLQs Guaranteeing Zero Data Loss
    < 500msPipeline Latency

  • Sub-Second BI & Executive Cockpits

    Columnar OLAP engines and pre-aggregated data marts rendering cash runways, gross margins, and inventory turnover in under 120ms with dynamic drill-down.

    • Pre-Aggregated ClickHouse Materialized Views with Sub-Second Queries
    • Power BI, Apache Superset, or Custom Headless Executive React Interfaces
    • Automated Outlier & Threshold Alerts Dispatched Directly to Leadership
    < 120msDashboard Query Latency

  • Data Governance, Lineage & Statutory Compliance

    Tracking data lineage from source to executive report with OpenLineage, enforcing granular cell-level RBAC and automated PII anonymization for full statutory audit readiness.

    • Automated Data Quality Contracts via Great Expectations & dbt
    • Complete End-to-End Data Lineage Tracking via OpenLineage
    • Strict Statutory Compliance for GDPR, KVKK, and Financial Audits
    %100Audited Data Integrity

  • Predictive AI, Demand Forecasting & Feature Stores

    Turning historical archives into predictive foresight; 90-day cash and stock forecasting, churn propensity, and dynamic pricing models backed by centralized Feature Stores.

    • Centralized Feast Feature Store Eliminating Training-Serving Skew
    • Dynamic Demand & Revenue Forecasting with >94% Accuracy Scores
    • Operational Risk & Outlier Early-Warning Neural Algorithms
    >%94Predictive Accuracy (F1)

  • Operational Reverse ETL & Automated Activation

    Pushing refined analytical scores and anomaly triggers back into frontline CRM, sales, procurement, and messaging backbones to automate executive actions.

    • Customer Propensity Scores Pushed Back into Frontline CRM Systems
    • Supplier Disruption Risks Triggering Automated Procurement Adjustments
    • Real-Time Automated Webhooks and Incident Notifications Across Teams
    0 SaatManual Report Prep Time

Industry approach

Domain-Specific Data Architectures

From modern dbt-managed lakehouses to real-time Debezium CDC streaming, sub-second ClickHouse marts, and centralized Feast feature stores; inspect our production-ready data pipelines.

Modern Lakehouse (dbt / Iceberg)

Consolidated Lakehouse & Modular dbt Transformations

Consolidating relational databases, SaaS platforms, and raw files into open Apache Iceberg formats, transformed by modular version-controlled dbt models with continuous testing.

100+ TB
Consolidated Storage
< 250ms
Columnar Query Time
-%50
Storage & Cost Savings
  • Version-Controlled, Modular, and Test-Driven Modeling via dbt Suites
  • Open Table Format (Apache Iceberg) Guaranteeing Total Vendor Neutrality
  • Granular Row & Column-Level Security (RLS) with Real-Time PII Masking

Real-Time CDC & Streams (Kafka)

Log-Based Change Data Capture (CDC) & Distributed Event Streaming

Asynchronously streaming row-level mutations straight from transaction logs (WAL/Binlog) via Debezium and Apache Kafka with zero production lock overhead.

< 500ms
Pipeline Latency
150K+
Events Processed / Sec
0 ms
Production DB Lock Overhead
  • WAL / Binlog Non-Intrusive Capture Eliminating Production SQL Overhead
  • Schema Registry & Avro Contracts Preventing Downstream Schema Breakages
  • Event Sourcing & Dead-Letter-Queues for Automatic Fault Isolation

Executive BI Cockpit (ClickHouse)

Columnar ClickHouse Engine & Executive Decision Support Cockpits

Pre-aggregating multi-million row event streams on write via ClickHouse SummingMergeTree materialized views, powering C-level cockpits in under 120 milliseconds.

< 120ms
Dashboard Query Latency
100+
Concurrent Executives
0 Saat
Manual Excel Prep Time
  • Columnar ClickHouse Materialized Views for Sub-Second Aggregations
  • Multi-Tenant Role-Based Cockpit Matrix with Granular Row-Level Security
  • Automated Outlier & Threshold Alerts Dispatched Directly to Leadership

Predictive ML & Feature Stores

Centralized Feature Stores (Feast) & Predictive MLOps Pipelines

Connecting live enterprise streams directly to machine learning inference via Feast Feature Stores, eliminating train-serve skew for demand forecasting and churn detection.

>%94
Predictive Accuracy (F1)
30-90 Gün
Forecasting Horizon
Anlık
Automated Anomaly Detection
  • Centralized Feast Feature Store Unifying Online Serving with Offline Training
  • Seasonal and Inflation Modeling for Dynamic Working Capital Allocation
  • Operational Reverse ETL Dispatching ML Scores Directly to Frontline Reps

Our method

Reliable Data for Enterprise Decisions

High-integrity data engineering eliminating guesswork, emotional forecasting, and fragmented spreadsheets across all operational tiers.

  • Single Source of Truth & Lakehouse Core

    Consolidating core ledgers, transactional databases, and SaaS tools into an infallible lakehouse core to permanently eliminate conflicting numbers.

  • Zero-Latency Decision Making (CDC & Sub-Second BI)

    No waiting for month-end reconciliation. Real-time CDC streams every transaction into board dashboards in under 500 milliseconds.

  • Sovereign Governance, Lineage & Compliance

    Full compliance with GDPR, KVKK, and sovereign banking audits with automated lineage tracking, cell-level RLS, and dynamic PII tokenization.

Working model

A Four-Stage Data and Analytics Model

From initial data catalog audit to real-time CDC deployment, sub-second ClickHouse marts, and automated MLOps governance: our disciplined 4-stage data engineering methodology.

  1. 01DISCOVERY SPEC

    01 / DATA INVENTORY & BLUEPRINT

    Data Cataloging, Quality Audit & Lakehouse Blueprint

    Cataloging all databases, SaaS endpoints, and flat files, auditing schema drift, and formalizing the modern sovereign Lakehouse architecture blueprint.

    • Comprehensive discovery of all relational DBs and SaaS APIs
    • Automated schema profiling detecting duplicate and corrupt metrics
    • Formal sign-off on sovereign Apache Iceberg + ClickHouse blueprint
    1 - 2 WeeksAudit Phase
  2. 02STREAMING PIPELINE

    02 / REAL-TIME CDC & STREAMING

    Non-Intrusive CDC Deployment & Kafka Streams

    Deploying Debezium non-intrusive CDC over database WAL logs, orchestrating Kafka streaming backbones, and authoring modular dbt transformation models.

    • Log-based replication imposing zero locks on core databases
    • Sub-500ms end-to-end event streaming into partitioned Kafka topics
    • Version-controlled dbt models with automated schema regression tests
    < 500msPipeline Latency
  3. 03SUB-SECOND BI

    03 / EXECUTIVE BI COCKPITS & OLAP

    Columnar ClickHouse Marts & Sub-Second Dashboards

    Engineering ClickHouse SummingMergeTree materialized views; deploying sub-second executive cockpits for consolidated EBITDA and cash runway tracking.

    • ClickHouse SummingMergeTree pre-aggregating live transaction streams
    • Power BI, Apache Superset, or custom React headless dashboard delivery
    • Row-Level Security (RLS) isolating holding-wide vs branch-level metrics
    < 120msQuery Latency
  4. 04GOVERNED MLOPS

    04 / GOVERNANCE, MLOPS & 24/7 SLA

    OpenLineage Tracking, Feast Feature Stores & Reverse ETL

    Automated data quality contracts, GDPR-compliant dynamic tokenization, predictive ML forecasting engines, and 24/7 mission-critical pipeline SLA monitoring.

    • Great Expectations automated data contracts preventing metric drift
    • Feast Feature Store powering demand forecasting and churn detection
    • Reverse ETL operationalizing analytical scores into frontline workflows
    100%Audited Integrity

FAQ

Data Management and Business Intelligence: Frequently Asked Questions

Key inquiries regarding modern lakehouse architectures, non-intrusive CDC streaming, sub-second executive cockpits, and data governance. For custom consultations, you can contact us.We are delighted to assist your enterprise.

  • We consolidate all disparate enterprise assets—relational databases (PostgreSQL, MySQL, Oracle), NoSQL data, SaaS APIs (CRM, billing, marketing), logistics telematics, and IoT streams—into a high-performance modern Lakehouse architecture (Snowflake, Databricks, ClickHouse, Apache Iceberg). Utilizing dbt for modular transformation, automated schema evolution, and deduplication, we establish an infallible enterprise Single Source of Truth that eliminates conflicting numbers across departments.

  • Rather than bogging down production databases with invasive batch SQL queries, we deploy non-intrusive Change Data Capture (CDC via Debezium) engines that read transaction logs (WAL/Binlog) asynchronously, coupled with Apache Kafka / Redpanda event backbones. Every transaction, order, payment, or inventory change replicates to analytical storage in under 500 milliseconds with zero transactional overhead on source systems.

  • To end slow, spinning reports across millions of transaction rows, we deploy columnar OLAP engines (ClickHouse, BigQuery) and materialized analytical data marts. Powering dashboards via Power BI, Apache Superset, or custom headless React/Next.js interfaces, our executive cockpits render consolidated EBITDA, cash runway, inventory turnover, and cohort LTV in under 250 milliseconds with dynamic drill-down capabilities.

  • We map every field from raw ingestion to the final executive dashboard using automated lineage tooling (OpenLineage). Automated data quality contracts via Great Expectations and dbt prevent corrupted metrics from polluting reports. Granular Row-Level Security (RLS) and Role-Based Access Control (RBAC) ensure strict boundary isolation, while sensitive customer PII is dynamically masked and tokenized to meet stringent GDPR, KVKK, and sovereign banking audits.

  • We transform static historical archives into predictive enterprise intelligence. By engineering centralized Feature Stores and automated MLOps pipelines, we deploy real-time demand forecasting, dynamic pricing, churn prediction, and financial anomaly detection models directly over live data streams, feeding automated actionable alerts straight to department leadership.

  • Rather than letting high-value analytics sit idle inside dashboards, we operationalize warehouse data. Through automated Reverse ETL pipelines, refined customer propensity scores push back into CRM tools, supplier risk indicators flow into procurement portals, and anomaly alerts dispatch immediately to operational teams via Webhooks, Slack, or ticketing engines for instant remediation.

Our other services

Our service portfolio

Six complementary practices, engaged individually or together depending on your needs.

Let's work together

Let's plan your project together

Let us listen to your needs and define the right scope, timeline and roadmap together.

Contact Us
Chat with us on WhatsApp