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Data Engineering & Analytics

Build scalable data pipelines, real-time analytics, and business intelligence that turns raw data into competitive advantage.

What We Deliver

Data That Powers Decisions

From ETL pipelines to real-time streaming, from data warehouses to interactive dashboards — we build the data infrastructure that lets you understand your business and predict the future.

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ETL Pipelines

Extract, transform, load. Automate data ingestion from any source. Clean, validate, enrich. Deliver trusted data daily.

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Real-Time Streaming

Kafka, Kinesis, Pub/Sub. Process data as it arrives. Millisecond latency. React to events instantly.

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Data Warehouses

Snowflake, BigQuery, Redshift. Structured, queryable, scalable. Your single source of truth.

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Business Intelligence

Tableau, Looker, Power BI. Interactive dashboards. Real-time KPIs. Self-service analytics for your team.

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Data Governance

Data quality, lineage, metadata. Compliance and discoverability. Know where every number comes from.

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Performance Optimization

Query optimization, indexing, partitioning. Fast queries even on terabytes of data. Save on cloud costs.

Core Capabilities

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Modern Data Stack

dbt for transformations, Apache Airflow for orchestration, modern cloud data warehouses. Best-in-class tooling.

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Data Integration

Fivetran, Stitch, custom connectors. Connect any source to your warehouse. APIs, databases, SaaS, files.

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Stream Processing

Kafka, Spark Streaming, Flink. Real-time aggregations, windowing, event-driven processing.

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Analytics & BI

Dashboard design, data visualization, user training. Make insights accessible to entire organization.

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Data Modeling

Dimensional modeling, star schemas, slowly changing dimensions. Logical, efficient, performant structures.

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Analytics Engineering

dbt models, data tests, documentation. Treat data transformations like code. Version control, CI/CD.

Technologies We Use

BigQuery Snowflake Redshift Apache Spark dbt Apache Airflow Kafka Tableau Looker Python
Our Process

Data Architecture Framework

1

Assessment

Understand current data landscape. Identify sources, pain points, growth opportunities.

2

Design

Architecture modern data warehouse. Plan integrations, transformations, governance model.

3

Implementation

Build pipelines, load data, transform, test. Deploy with zero downtime.

4

Analytics & Training

Create dashboards, enable self-service, train teams. Continuous improvement.

Case Study: Axelion Data Warehouse

Challenge: E-commerce company had data scattered across Salesforce, Shopify, Google Analytics, internal databases. No unified view. Dashboards took weeks to create.

Solution: Built modern data warehouse on BigQuery. Automated ETL pipelines via Airflow. Created dbt transformations. Built Looker dashboards for real-time insights.

Result: 10x faster reporting, 30% faster insights, 95% cost reduction vs. previous solutions. Sales team now self-serves analytics daily.

10x
Faster Reports
95%
Cost Savings
2mo
Time to Live
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Build Your Data Foundation

Data warehouse projects range from $75k (MVP) to $250k+ (enterprise). We charge per milestone with clear deliverables.