Data Platform ModernizationTransform raw data into strategic advantage
- Modern data platform design with lakehouse architectures combining the best of data lakes and data warehouses
- Real-time and batch pipeline engineering with Spark, Kafka, and Airflow for reliable data at any scale
- Self-service analytics and BI enablement turning every team into a data-driven decision maker
- Data governance frameworks ensuring quality, lineage, and compliance across the entire data estate
The work, in detail.
We design and implement modern data platforms that unify data engineering, analytics, and governance into a single, scalable architecture. From real-time streaming pipelines to petabyte-scale data lakes, we help organizations harness the full value of their data with platforms built for reliability, performance, and compliance.
- Data lake and lakehouse architecture
- Real-time and batch ETL pipelines
- Business intelligence and analytics
- Data governance and quality frameworks
- Streaming data processing with Kafka
- Cost-optimized storage and compute
The data platform modernization stack.
- 01
Data Engineering & Pipelines
Build the foundation for data-driven decisionsWe design and build robust data pipelines that ingest, transform, and deliver data reliably at scale. From real-time streaming to complex batch orchestration, our pipelines are the backbone of modern data platforms.
- Real-time and batch ETL pipeline development
- Data lake and lakehouse architecture (Delta Lake, Iceberg)
- Streaming data processing with Kafka and Kinesis
- Data quality frameworks with automated validation
- Schema evolution and backward-compatible data contracts
- 02
Analytics & Business Intelligence
From raw data to actionable insightsWe build analytics platforms that make data accessible to every stakeholder, from executive dashboards to self-service exploration tools, ensuring the right insights reach the right people at the right time.
- Executive dashboard design and development
- Self-service analytics platform configuration
- Embedded analytics for customer-facing products
- KPI framework design and metric layer implementation
- Predictive reporting and trend analysis
- 03
Data Governance & Quality
Trust your data completelyWe implement comprehensive data governance frameworks that ensure data quality, enforce access policies, track lineage, and maintain compliance, giving organizations complete confidence in their data.
- Data cataloging and discovery (DataHub, Atlan, Alation)
- End-to-end data lineage tracking and visualization
- Automated data quality monitoring and alerting
- Compliance frameworks for GDPR, CCPA, and industry regulations
- Master data management and golden record strategies
- 04
Mission Data Platforms
Enterprise-grade platforms for critical workloadsWe build and operate data platforms designed for the most demanding workloads, with multi-tenant isolation, petabyte-scale processing, real-time analytics, and production disaster recovery.
- Multi-tenant data platform architectures with isolation guarantees
- Petabyte-scale data processing and storage optimization
- Real-time analytics with sub-second query performance
- Cost-optimized storage tiering and lifecycle management
- Cross-region disaster recovery and data replication
What clients have actually shipped.
- 01Scandinavian Federal Data Authority
Federal Data Lake Consolidation
Consolidated 47 disparate data sources into a unified data lakehouse on Databricks and AWS, serving 1,200+ analysts across 12 federal agencies with governed, self-service access to 3.2 petabytes of data.
- 99.9%
- Platform Uptime
- 3.2 PB
- Data Under Management
- 60%
- Infrastructure Cost Reduction
- 85% faster
- Query Performance Improvement
- 02ShopStream Europe
Real-Time Analytics for E-Commerce
Built a real-time analytics platform processing 2M+ events per minute from 50+ European e-commerce sites, enabling personalized recommendations, fraud detection, and live inventory optimization.
- 2M+
- Events Processed per Minute
- 18%
- Recommendation Revenue Lift
- 99.7%
- Fraud Detection Accuracy
Who we work with.
- Databricks
- Snowflake
- AWS
- Google Cloud
- Confluent
"CreativeMinds transformed our data capabilities from a fragmented mess of 47 disconnected systems into a unified platform that 1,200 analysts rely on daily. The 60% cost reduction was impressive, but the real win is that our agencies can now share data securely and make decisions based on a single source of truth."
How we run an engagement.
- 01
Discovery
We learn the business, the constraints, and the real technical problem — workshops, stakeholder interviews, and competitive review. Most ambiguity gets resolved here.
- 02
Planning
A scoped roadmap with milestones, deliverables, architecture decisions, and the trade-offs we made and rejected. You get the document, not a slide.
- 03
Development
Senior-only delivery. Sprint cadence, transparent progress, continuous integration. No mid-project surprise about who is actually writing the code.
- 04
Delivery
Deploy, validate, hand off. Full documentation, monitoring in place, and a defined window of post-launch support to catch what only production reveals.
Start this engagement.
Tell us what you are trying to ship. We'll come back with whether we are the right team, what scope looks like, and what a 8-16 weeks engagement would cover.
What pairs with this work.
- 01cloud
Cloud Computing & Architecture
Multi-cloud certified solutions (AWS, GCP, Azure) with well-architected framework implementation
- 02ai
AI & Machine Learning
Enterprise AI solutions from intelligent copilots and RAG systems to predictive analytics and production-grade MLOps
- 03cloud
Cloud Migration
Seamless migration from on-premises to multi-cloud infrastructure (AWS, GCP, Azure)