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Big Data & Decision SciencesReal-Time Streaming

Real-Time Streaming ETL & Lakehouse Modernization with Apache Flink & dbt

Retire fragile nightly batch scripts with sub-second streaming pipelines that deliver real-time data to operational dashboards.

VB
Architected by Vaibhav Bhosale
10 min read
Updated 2025-11-28
Verified Architecture
Sub-Second
Data Freshness Latency
99.99%
Pipeline Reliability
65%
ETL Compute Cost Reduction
8 Silos
Unified into Lakehouse

Executive Architecture Summary

Nightly batch ETL scripts running for 6 hours are prone to silent failures and leave business stakeholders looking at stale yesterday-data. i26 replaces legacy scripts with modern stream processing architectures built on Apache Kafka, Apache Flink, and dbt.

The Enterprise Challenge & Cost Liabilities

Organizations rely on brittle Cron jobs running custom Python scripts and SQL views that break whenever source schemas change. Executive reporting is delayed until late morning, while downstream machine learning models operate on stale inputs.

The i26 Engineering Solution & Blueprint

- Continuous change capture into Kafka with schema registry enforcement. - Stateful real-time stream aggregation and event enrichment using Apache Flink. - Automated data quality testing, lineage graphs, and semantic documentation via dbt core.

Technologies & Architecture Components

Apache FlinkApache Kafkadbt CoreBigQuery / SnowflakeTerraformAirflow / Dagster
VB
Vaibhav Bhosale
Founding Partner & Chief Systems Architect · i26 AI & Software Solutions

Specializing in zero-downtime database cutovers, cloud FinOps rightsizing, and sovereign private VPC AI architectures. Oversees all enterprise implementations at i26.

Related Enterprise Blueprints

Ready to Implement This Solution in Your Environment?

Schedule a direct technical scoping call with Vaibhav Bhosale. We will evaluate your current infrastructure, SLAs, and data volumes under mutual NDA.

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