Data Services
End-to-end data infrastructure
Warehouses, lakehouses, pipelines, and transformation layers built to last
Your Data Partner — decisions backed by data, not gut feeling.
End-to-end data platforms
built to ship and operate.
RALA Data Solutions helps teams deliver reliable data infrastructure and practical automation — from warehouses and pipelines to business logic and AI-enabled workflows. Built to be operated, not just deployed.
BuildClear systems, reviewable progress
RunMonitoring, runbooks, predictable ops
ImprovePractical automation with guardrails
Reports & Analytics
BI-ready outputs
Power BI, reporting marts, KPI frameworks, and decision-ready dashboards
Automation & AI
Smarter operations
Operational automation first — AI workflows where they genuinely add value
Consulting
Architecture & advisory
Multi-cloud strategy, IaC, and hands-on delivery guidance
Platform experience
Azure
AWS
GCP
MS Fabric
Databricks
dbt
Terraform
Power BI
Selected feedback
How a modern data stack is built
From raw sources to business decisions — the architecture we design, build, and operate.
Source Systems
CRM • ERP • APIs • Files
Data Lake
Raw / Bronze layer
Data Warehouse
Silver → Gold layers
dbt Models
Business logic • tested
BI & Reporting
Power BI • Fabric • Looker • custom
Decisions
Data-driven • not gut feel
What we do
Four areas where we deliver value — from raw data to decisions.
Data Services
Data infrastructure, end to end
We build the foundation — from raw ingestion to clean, modeled data your teams can actually use.
- Data warehouse & lakehouse design (Azure, AWS, GCP, Fabric, Databricks)
- ELT/ETL pipelines with orchestration, monitoring, and runbooks
- Transformation layers in SQL and dbt — readable, tested, documented
- Data quality checks, lineage, and observability
- Environments, access controls, governance basics
Reports & Analytics
From data to decisions
Reporting layers, BI dashboards, and KPI frameworks that give teams a clear, consistent view of what matters.
- Power BI — reports, dashboards, and semantic models
- Reporting-ready marts and metrics layer foundations
- KPI design, metric consistency, and governance
- Client-facing and internal analytics — both covered
- Performance tuning for large-scale report delivery
Automation & AI
Less manual work, more reliable ops
We automate the routine first — then bring in AI where it has clear, measurable value and proper guardrails.
- Workflow automation — scheduling, alerts, operational tooling
- Python-based automation and cloud-native workflow orchestration
- AI-enabled workflows with human-in-the-loop where it counts
- Evaluation, monitoring, and audit trails for AI outputs
Consulting
Architecture & strategic advisory
Hands-on guidance for teams building or scaling their data stack — from tool selection to multi-cloud architecture.
- Multi-cloud architecture & stack selection (Azure, AWS, GCP, Fabric)
- Infrastructure as Code — Terraform, CI/CD, multi-tenancy
- Architecture reviews and hands-on delivery support
- Platform strategy aligned to business goals and team maturity
Approach
Startup speed. Production discipline.
01
Align
Define outcomes, constraints, and a plan that survives contact with reality.
02
Ship
Deliver in small increments with reviewable diffs and visible progress week by week.
03
Operate
Monitoring, runbooks, and a proper handover — so your team can own it long-term.
What you get
- Readable transformations with documentation
- A testing strategy that matches your actual risk
- Monitoring, alerting, and runbooks from day one
What we avoid
- Frameworks without clear return on investment
- Over-abstracted platforms too early in the journey
- Tooling decisions driven by hype, not fit
The core team
Two engineers who lead the work on every engagement — backed by a trusted network of specialists for whatever the project demands.
Person 1
Analytics Engineer
Works at the intersection of data and business — from reporting layer design and analytics engineering to data pipelines and cloud delivery on AWS. Turns raw data into something the business can actually use and trust.
Person 2
Data Platform Engineer
Builds the infrastructure that makes data reliable at scale — Azure, Fabric, Databricks, pipelines, orchestration, and IaC from the ground up. Covers data modeling where it matters. The person ensuring the platform holds in production and doesn’t surprise anyone at 2 AM.
International experience
Delivery across multiple European markets, with selected US experience.
Designed and implemented a flexible reporting layer with advanced personalization for client-facing analytics. The work improved KPI visibility, strengthened metric consistency, and supported more effective decision-making across the organization.
I can highly recommend a company that designed and implemented a cloud-based analytics solution on the Azure stack, covering data storage, integrations, automation, and reporting optimization. Python-based automation and cloud workflows improved data reliability, reduced manual operations, and enabled more scalable analytics use cases.
Supported the organization’s transition from Tableau to Power BI, helping establish a modernized reporting environment and improving the overall analytics structure. The work included preparing and adapting reporting assets, supporting database-related improvements, and ensuring a smooth migration of reports during infrastructure changes. The updated reporting environment improved accessibility of insights and supported more consistent data usage across the organization.
Provided consulting on the design and evolution of the organization’s data and analytics architecture. The engagement included defining concepts for a scalable data platform, improving reporting capabilities, and supporting the integration of multiple data sources. The work contributed to a clearer roadmap for future analytics development and more structured data usage across the organization.
Developed operational reporting solutions integrating multiple data sources to support daily decision-making processes. The work focused on building a reliable reporting layer and improving data accessibility for operational teams. The solution provided consistent visibility into key operational metrics and helped streamline routine analysis for business stakeholders.
Contact
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RALA Data Solutions
Tell us what you’re trying to achieve, what’s currently painful, and any constraints — cost, tooling, or timeline. We’ll reply with a clear next step.
- Response within one business day