Align this section structure with the AI & Data Science Services page: strategy → foundation → migration → operations.
Why a Modern Data Platform?
A modern data platform centralizes structured, semi‑structured, and unstructured data in a scalable, cloud-native architecture so teams can trust, share, and operationalize insights at speed. It decouples storage and compute, supports streaming and batch, and enables self-service analytics for business users.
Key Value Drivers
Break down data silos
Create a single source of truth with unified lakehouse patterns (OneLake, Delta Lake, Snowflake Data Cloud) instead of fragmented marts and shadow IT.
Improve performance and scalability
Scale elastically for large data volumes and high concurrency, with near real-time analytics using Direct Lake in Fabric, Databricks medallion architecture, and Snowflake multi‑cluster compute.
Reduce total cost of ownership
Retire legacy EDW and ETL tools, move to SaaS and usage-based models, and standardize on open formats (Delta, Parquet, Iceberg) to avoid lock-in and duplication.
Enable AI and advanced analytics
Give data scientists and analysts governed access to high-quality data for ML, GenAI, and real-time decisioning, with native notebook, ML, and semantic modeling capabilities.
Strengthen governance and compliance
Implement unified security, lineage, data quality, and access controls using Fabric governance, Databricks Unity Catalog, and Snowflake’s fine‑grained policies.
Data Platform Modernization & Migration
iLink’s Data & AI team modernizes legacy warehouses and BI stacks into cloud-native data platforms using Microsoft Fabric, Azure Databricks, and Snowflake.
Modernization focus areas:
Legacy DW & BI modernization
Migrate from on‑prem DW/old platforms and legacy BI tools to modern lakehouse and Fabric/Snowflake architectures with Power BI at the semantic layer.
Cloud-to-cloud and hybrid migrations
Move workloads between Snowflake, Databricks, and Fabric or consolidate multi‑cloud estates while keeping open table formats and avoiding re‑engineering.
Real-time and streaming architectures
Implement near‑real‑time analytics using Event Hubs, Kafka, Fabric Real‑Time Analytics, and Databricks streaming pipelines for use cases like POS, supply chain, and IoT.
Platform Capabilities at a Glance
Microsoft Fabric
- Unified SaaS data platform with OneLake, lakehouse, warehouse, data engineering, real‑time analytics, and Power BI tightly integrated.
- Direct Lake for high‑performance BI, Real‑Time Intelligence for streaming, and strong governance/integration with the Microsoft 365 and Azure ecosystem.
Azure Databricks
- Open, lake‑centric analytics platform built on Delta Lake, ideal for large‑scale data engineering, ML, and medallion architectures.
- Strong support for batch and streaming, advanced ML workflows, and Unity Catalog for centralized governance across data products.
Snowflake
- Cloud‑agnostic data cloud with elastic multi‑cluster compute, support for structured and semi‑structured data, and built‑in collaboration and marketplace capabilities.
- Simplified administration with near‑zero maintenance and robust security and governance for enterprise analytics workloads.
iLink Data Platform Services
Data Advisory & Strategy
01
Data Foundation & Architecture
02
Migration & Modernization
03
Data Engineering & Operations
04
Governance & Security
05
- Data platform strategy and roadmap aligned to business OKRs.
- Platform fit analysis and decisioning across Fabric, Databricks, and Snowflake for specific use cases.
1
Data Advisory & Strategy
01
- Data platform strategy and roadmap aligned to business OKRs.
- Platform fit analysis and decisioning across Fabric, Databricks, and Snowflake for specific use cases.
2
Data Foundation & Architecture
02
3
Migration & Modernization
03
4
Data Engineering & Operations
04
5
Governance & Security
05
Why iLink for Data Platforms?
Position iLink’s differentiation similar to the “Why iLink” section on your AI & Data Science page, but tailored to Fabric/Databricks/Snowflake.
- Deep, multi-platform expertise
250+ Fabric analytics engineers and 90+ Databricks-certified professionals, plus a dedicated Snowflake practice with certified consultants and reference architectures.
- Featured and strategic partnerships
Microsoft Fabric Featured Partner with early‑adopter status, extensive Power BI track record, and recognized Databricks and Snowflake capabilities.
- Proven success across industries
Data platform implementations for Fortune 500 companies in manufacturing, QSR, healthcare, financial services, and more, including cases with Fabric + Snowflake and Databricks data mesh patterns.
- Thought leadership and accelerators
Roadshows, webinars, hackathons, and POVs focused on Fabric vs. Snowflake vs. Databricks, plus reusable frameworks, greenprints, and migration accelerators.
Selected Data Platform Success Stories
Use card-style layouts similar to the AI & Data Science page to highlight outcomes.
Global Restaurant Chain
Marketing analytics on Fabric + Snowflake Enabled self‑service marketing analytics by introducing Fabric as the semantic and reporting layer on top of Snowflake, reducing report cycle time from hours to seconds.
