Our Fabric Data Warehousing Implementation Services are designed to help organizations modernize their data estate, streamline analytics operations, and build scalable, secure, and governed data architectures. We provide end-to-end services covering strategic planning, warehouse setup, data ingestion, semantic modeling, Power BI integration, security, and training.
Whether you’re migrating from legacy platforms or building a greenfield data environment, our certified experts ensure your Fabric deployment is future-ready, optimized for performance, and aligned with business outcomes.
✅ Architecture Planning - Choose between Lakehouse and Data Warehouse modes, define storage zones and select access layers.
✅ Data Ingestion & Integration - Build pipelines using Dataflows Gen2 and Pipelines to ingest data from SQL, SAP, Salesforce, APIs, flat files, and more.
✅ Warehouse & Lakehouse Setup - Provision and configure Microsoft Fabric Warehouse or Lakehouse environments with partitioning, schema design, and workload optimization.
✅ Data Modeling & Semantic Layer - Create business-friendly star/snowflake schemas, calculated tables/measures, and Power BI datasets for analytics consumption.
✅ Power BI Integration - Connect Power BI with Fabric datasets for real-time dashboards, report authoring, and deployment pipelines.
✅ Governance & Security - Implement Row-Level Security (RLS), Microsoft Purview policies, access controls, lineage tracking, and compliance configurations.
✅ Training & Knowledge Transfer - Conduct enablement sessions for business users, data engineers, analysts, and governance teams.
✅ Unified Platform : One integrated solution for lake, warehouse, and BI—no data duplication or siloed tools.
✅ Real-Time Analytics : Direct Lake access enables sub-second query performance without ETL overhead.
✅ Reduced TCO : Simplified architecture reduces infrastructure and licensing costs.
✅ Enterprise Governance : Built-in compliance, data lineage, and role-based security support.
✅ Faster Time-to-Insight : Simplified ingestion pipelines and pre-built connectors accelerate implementation.
✅ Scalable & Cloud-Native : Fabric adapts to growing workloads and data sources with elastic compute and storage.
✅ Power BI-Ready : Deep native integration with Power BI supports governed self-service BI across the organization.
Small Project
Timeline: 2 – 3 Weeks
Scope & Features :
Ingest and model data from 1–2 sources.
Provision a single Fabric Warehouse or Lakehouse.
Build 1 semantic model and connect with Power BI.
Enable role-based access and basic governance.
Targeted for use cases like finance or HR dashboards.
What Includes :
✅ Discovery & requirements gathering for 1–2 use cases.
✅ Setup of Fabric environment (Workspace, Warehouse/Lakehouse).
✅ Ingestion using Dataflows Gen2 from up to 2 structured sources.
✅ Development of 1 Power BI dataset and dashboard.
✅ Row-Level Security (RLS) and basic access control.
✅ Documentation & 1 training session for analysts.
✅ 2 weeks post-go-live support
For any specific questions or Doubts ,
Medium Project
Timeline: 4–6 Weeks
Scope & Features :
Ingest and model data from 3–5 sources.
Use a combination of Lakehouse + Warehouse.
Design multi-zone architecture (bronze/silver/gold layers).
Create multiple semantic models and department-specific dashboards.
Apply governance and compliance controls using Microsoft Purview.
What Includes :
✅ Business & technical assessment for 3–5 workflows/data areas.
✅ Setup of Fabric workspace with both Warehouse and Lakehouse components
✅ Development of 3–5 data pipelines using Pipelines/Dataflows Gen2.
✅ Creation of 2–3 Power BI datasets with calculated measures.
✅ Implementation of security, auditing, and data lineage.
✅ User training (2 sessions) for analysts and data stewards.
✅ 4 weeks post-go-live support + performance tuning.
For any specific questions or Doubts ,
Large Project
Timeline: 8–12 Weeks
Scope & Features :
Ingest and model data from 6+ systems (ERP, CRM, APIs).
Establish enterprise-grade Lakehouse and Warehouse layers.
Automate ingestion across 10+ pipelines with custom logic.
Enable real-time reporting with Direct Lake + Power BI.
Implement governance, compliance, security, and lineage across all data assets.
What Includes :
✅ Enterprise-wide discovery workshops and current-state assessment.
✅ Full configuration of multi-zone Fabric data architecture (bronze/silver/gold).
✅ Custom schema and semantic modeling for multiple departments.
✅ Power BI integration with 5+ interactive dashboards and role-based access.
✅ Implementation of Microsoft Purview (security, RLS, classification, lineage).
✅ Multi-session training across departments (IT + Business).
✅ 8 weeks of post-go-live support with optimization and CoE enablement.
For any specific questions or Doubts ,
Conduct stakeholder workshops to understand business goals, data challenges, and reporting needs.
Assess current data estate: review databases, reporting tools, integrations, and governance models.
Identify all data sources, target user personas (analysts, executives, operations), and access needs.
Recommend best-fit architecture (Warehouse, Lakehouse, or hybrid) based on data complexity and latency needs.
Define project scope, success KPIs, and implementation roadmap aligned with business value.
Design logical and physical data models (star/snowflake schemas) for reporting use cases.
Plan ingestion pipelines and define data zones:
Bronze: Raw ingestion
Silver: Cleansed/validated data
Gold: Curated datasets for analytics
Define security architecture: roles, permissions, and access layers.
Select ingestion methods (Dataflows Gen2, Pipelines) and modeling approach (Direct Lake or Import).
Document solution architecture including workspace structures and data refresh strategies. |
Set up Microsoft Fabric workspace and provision Lakehouse or Warehouse environments.
Create ingestion pipelines using Dataflows Gen2 and Pipelines to extract data from identified sources.
Configure data transformation logic, validation rules, and job schedules.
Create relational tables, views, relationships, and calculated measures in SQL or Power BI datasets.
Build reusable datasets for reporting across departments.
Integrate semantic layer with Power BI for real-time dashboards and KPI tracking.
Apply Microsoft Purview policies for data classification, sensitivity labeling, and retention.
Configure Row-Level Security (RLS) and object-level permissions on datasets and tables.
Enable audit logging for data access and changes.
Set up version control, workspace roles (admin, contributor, viewer), and deployment pipelines.
Ensure compliance with internal policies and external regulations (GDPR, HIPAA, ISO 27001).
Conduct User Acceptance Testing (UAT) with business users to validate datasets, dashboards, and workflows.
Review query performance and optimize SQL/DAX expressions, table structures, and pipeline execution.
Implement monitoring and alerts for data refresh failures, latency issues, and load thresholds.
Perform peer reviews and final data quality checks.
Finalize change requests and lock down production workspace for go-live.
Deliver hands-on training for IT teams, analysts, and end-users (role-based sessions).
Provide documentation: data models, dashboards, user guides, and SOPs.
Assist with go-live activities: deployment, refresh validation, alert testing, and rollback plans.
Offer post-go-live support for 2–4 weeks (hyper care), including enhancement backlog creation.
Conduct final knowledge transfer and project closure review.
You've got questions. We've got answers.
It is a cloud-native, fully managed enterprise data warehouse built on OneLake and part of the Microsoft Fabric platform. It supports real-time analytics and seamless integration with Power BI, Purview, and external data systems.
Fabric unifies lakehouse and data warehouse architectures into one platform, eliminating data movement and enabling Direct Lake access for real-time Power BI performance without scheduled refreshes or duplication.
SQL Server, Azure SQL, Salesforce, SAP, Oracle, REST APIs, Excel, CSV, and more—via native connectors or Dataflows Gen2/Pipelines.
Yes.
Data engineers can build ingestion and modeling pipelines, while business users can consume governed datasets in Power BI. Role-based security and semantic models ensure both flexibility and control.
Team Academy is headquartered in Doha, Qatar, serving as a leading provider of professional training and development solutions. Our services extend across the Middle East, North Africa (MENA), and South Asia regions, delivering high-impact learning experiences tailored to the needs of modern businesses.
Where as we provide services in person in Qatar premises , for other regions we do the service online .