01
Cloud Data Platforms
Target architecture, cloud migration, performance and governance for modern analytical platforms across Snowflake, BigQuery and cloud-native services.
Data Consulting · Cloud Engineering · Native Apps
Hello. How can we scale your data today?
Consulting and engineering for modern data platforms, analytics foundations and native data applications across Snowflake, BigQuery and enterprise data environments.
Architecture first · Production-minded · Built for maintainability
DATRELIS Architecture View
From source to data product
Production Mindset
01
Sources
Databases
APIs
Events
02
Ingest
Batch
CDC
Streaming
03
Engineer
SQL & dbt
Python
Airflow
04
Platform
Snowflake
BigQuery
Cloud Storage
05
Deliver
Native Apps
BI & Metrics
Data Products
Designed for: reliability, governance, performance and maintainability.
Cloud-first · Vendor-aware
Consulting focus
Strategy & Architecture
Platform Engineering
Data Integration
Analytics & Native Apps
About DATRELIS
Data. Relations. Intelligence.
Consulting and engineering for cloud data platforms, integration, analytics foundations and native data applications.
Consulting & Engineering
Turning complex data environments into dependable platforms.
DATRELIS works with teams to assess current-state architecture, define target platforms, engineer reliable data flows and improve analytics delivery. Our focus is practical: systems that are clear to operate, easier to govern and ready to evolve with the business.
Data
Reliable foundations, governed models and production-ready engineering.
Relations
Clear relationships across source systems, models, metrics and business context.
Intelligence
Analytics and applications that turn trusted data into decisions, workflows and measurable outcomes.
Capabilities
Consulting and engineering across the data lifecycle.
Each engagement starts with the client context: architecture, workloads, operating model and business priorities. Technology follows the problem, not the other way around.
02
Data Engineering & Integration
Batch, CDC and streaming pipelines; transformation layers; orchestration, testing and observability built for maintainable day-to-day operations.
03
Analytics & Semantic Foundations
Business-ready models, KPI definitions, semantic layers and BI delivery that keep reporting logic consistent and easier to govern.
04
Native Apps & Data Products
Productized workflows that run close to governed data, including Snowflake Native Apps, data utilities and reusable operational accelerators.
05
Enterprise Data Integration
Connecting ERP, SAP and operational systems with cloud data platforms while preserving lineage, controls and dependable downstream delivery.
Products
Native applications built from recurring data challenges.
Alongside consulting engagements, DATRELIS is developing Snowflake-native applications and reusable data products shaped by repeatable engineering and analytics needs.
Data Operations Utilities
Focused tools for recurring platform operations, controls and engineering workflows inside the data cloud.
Governance & Quality
Practical capabilities that make quality, traceability and operational checks easier to run close to governed data.
Analytics Accelerators
Reusable building blocks designed to shorten the path from modeled data to business-ready metrics and analytics.
Product names, availability and marketplace links will be published when releases are ready.
Approach
A clear path from assessment to production.
We combine advisory and hands-on delivery: understand the current state, define the target architecture, implement deliberately, then improve reliability, cost and performance over time.
01
Assess
Understand the current architecture, workloads, data flows, constraints, reliability issues and business priorities.
Current-state viewRisks & gapsPriorities
02
Architect
Define the target design, data contracts, security boundaries, orchestration model and deployment approach before implementation.
Target architectureData modelDelivery plan
03
Build
Implement pipelines, models, tests, analytics or native applications with maintainability and production behavior in mind.
Production codeAutomationTesting
04
Operate & Improve
Measure reliability, cost and performance; refine the operating model and improve the system as workloads and requirements evolve.
ObservabilityOptimizationRunbooks
Technology Ecosystem
Technology selected to fit the architecture.
We work across modern cloud and enterprise data ecosystems. Platform choices are based on workload fit, client standards, integration needs and operating requirements.
Snowflake
BigQuery
Google Cloud
Microsoft Azure
AWS
SAP
dbt
Apache Airflow
Python
Power BI
Looker
SQL
Contact
Start the conversation.
Share the problem, platform or outcome you are working toward. We will use the context to frame the most useful next step.
Prefer email? contact@datrelis.com.tr