02 / Platforms, analytics & AI
Data platforms, integration & warehousing
Enterprise data warehouses, big data and data lake platforms, data integration and virtualization, built to feed analytics reliably.
Why it matters
Analytics and AI are only as good as the platform beneath them. Jadara designs and builds the data layer: integration pipelines from source systems, enterprise data warehouses modeled for reporting, big data and data lake platforms for scale, virtualization layers for governed access, and master and reference data solutions for consistency. We also migrate and reverse-engineer legacy warehouses onto modern distributed platforms.
What you get
Outcomes that outlast the engagement.
A target data architecture with integration, storage, semantic and consumption layers
Reliable pipelines with monitoring, quality checks and lineage
Warehouse and semantic models that business users can query with confidence
Migration from legacy databases to distributed platforms without losing history
Scope of work
Clear scope. Connected work.
Architecture & modeling
- Current and target data architecture
- Dimensional and 3NF modeling and semantic layers
- Data and analytics integration architecture
Integration
- ETL/ELT pipelines, real-time integration and change data capture
- Data virtualization and unified access layers
- API integration and streaming services
Platforms
- Enterprise data warehouses, big data and data lake platforms
- Master and reference data management
- Legacy migration and reverse engineering
Scope, deliverables and acceptance criteria are defined for each engagement.
How we work
From the first session to the final handover.
Many sources, one platform
Assess
We inventory sources, uses and operating constraints, and define analysis, retention and security requirements.
Design
We design the architecture, data models and semantic layer around the nature, volume and velocity of the data.
Build & test
We build pipelines and models in increments, with component, integration and business acceptance testing.
Operate & optimize
We monitor performance, cost and feed quality, and hand over operations with documentation and knowledge transfer.
Common questions
A little more clarity.
Warehouse, lake or lakehouse?
A warehouse suits structured, agreed reporting models; a lake accommodates varied formats and needs more cataloging and governance; a lakehouse combines the two. We choose by data and use, not by trend.
Can you work with our existing platform?
Yes. We work on the integration, storage and analytics platforms the organization already owns, and recommend change only when there is a clear case for it.
How do you handle legacy migration?
By reverse-engineering existing KPIs and reports, modeling a new warehouse that preserves history, and migrating in waves with validation and a rollback plan.
Connected capabilities
All capabilities
Business intelligence & advanced analytics
KPI frameworks, dashboards, self-service analytics and predictive models that turn governed data into decisions.
Metadata, data catalog & lineage
An enterprise catalog with a business glossary, automated scanning, end-to-end lineage and impact analysis, so people find, understand and trust data.
Data quality management
Profiling, business rules, scorecards and monitoring across the six quality dimensions, so decisions and reports rest on data people can trust.
Illustrative photographs
START A CONVERSATION
Tell us about your initiative.
A data office to establish, an index cycle to prepare for, a platform to deliver, a program to rescue. Share the context and we will come back with the right team and a scoped proposal.
Discuss a projectOpens an email to our team. Proposals and RFP responses are prepared in Arabic and English.
HEADQUARTERS
7076 ALSAHBA 4431Riyadh, Saudi Arabia
What helps us respond precisely
- The initiative or challenge to address
- The systems and data sources involved
- The regulatory requirements or measurement cycle in view
- The timeline and the stakeholders