Microsoft Azure
Azure Analytics Modernization Services
Move from aging data warehouses, cubes and fragmented reporting to a unified analytics platform on Microsoft Fabric, Azure Databricks and Power BI.
Modernize Analytics on Microsoft Fabric and Azure
Many analytics estates on Microsoft technology grew in layers: an on-premises SQL Server warehouse, SSIS packages, SSAS cubes, a Synapse workspace added later, and hundreds of Power BI reports built on top of each other. Each layer works, but together they are slow to change, expensive to run and hard to govern. Microsoft Fabric offers a way to consolidate onto OneLake with a lakehouse, a warehouse, real-time analytics and Power BI under one capacity model.
Hanoi Technology helps you decide what to move, in which order and to which target, whether that is Fabric Data Warehouse, a Fabric lakehouse, Azure Databricks or a combination. We migrate logic, validate results against the old system and retire legacy components only when the business is confident in the new numbers.
The Challenge
Why Legacy Analytics Is Hard to Modernize
The difficulty lies in the business logic accumulated over years, not in the storage.
Business Logic Buried in Code
Stored procedures, SSIS transformations and cube calculations contain undocumented rules. Migrating them blindly reproduces technical debt; ignoring them breaks reports.
Unclear Target Architecture
Fabric warehouse, Fabric lakehouse, Azure Databricks and Synapse all overlap. Teams struggle to decide which workloads belong where and how they share data.
Report Proliferation
Duplicate Power BI datasets with slightly different definitions of the same metric erode trust and multiply refresh load on source systems.
Parallel Running Costs
Running old and new platforms side by side is necessary for validation, but without a firm decommissioning plan it can last for years and double costs.
Business Value
What Modern Azure Analytics Delivers
One Copy of Data in OneLake
Lakehouse and warehouse tables are stored in open Delta Parquet format in OneLake, and shortcuts reference data in Azure Data Lake Storage, Amazon S3 or other locations without copying it.
Faster Reports with Direct Lake
Power BI semantic models in Direct Lake mode read Delta tables directly, avoiding large scheduled imports while keeping interactive performance.
Simpler Capacity and Cost Management
Fabric capacities consolidate compute for engineering, warehousing and BI, giving one place to monitor and manage consumption.
Shared, Governed Metrics
Certified semantic models and a medallion structure give every report the same definitions of revenue, margin or churn.
Ready for AI and Data Science
Data scientists work on the same governed tables in notebooks, and Copilot and data agents in Fabric can answer questions over curated data.
Open Interoperability
Delta and Apache Iceberg formats, along with Azure Databricks interoperability, avoid locking data into a single engine.
Modernize the Logic, Not Just the Platform
A lift-and-shift of the warehouse onto Fabric preserves every inefficiency. The real return comes from rationalizing models, retiring unused reports and agreeing shared metric definitions while the migration is underway.
Our Services
Hanoi Technology’s End-to-End Azure Analytics Modernization Services
From assessment to decommissioning, with validation at every step.
Analytics Estate Assessment
We inventory databases, ETL packages, cubes, semantic models and reports, measure usage and complexity, and identify what to migrate, consolidate or retire.
- Estate inventory and usage analysis
- Complexity scoring
- Modernization roadmap
Target Architecture Design
We design the Fabric or Databricks architecture, including workspaces, capacities, medallion layers, security, Git integration and deployment pipelines.
- Target architecture
- Workspace and capacity plan
- Security model
Synapse and SQL Warehouse Migration
We migrate Synapse dedicated SQL pools and SQL Server warehouses to Fabric Data Warehouse, using Microsoft migration tooling where it helps and converting T-SQL that is not supported.
- Converted schemas and code
- Data migration
- Reconciliation reports
Lakehouse Engineering
We build bronze, silver and gold layers in Fabric lakehouses or Azure Databricks with Spark notebooks, pipelines and data quality checks.
- Medallion lakehouse
- Transformation notebooks
- Data quality rules
Power BI Modernization
We consolidate datasets into certified semantic models, convert to Direct Lake where suitable, and rebuild or migrate reports from SSRS, SSAS or other BI tools.
- Certified semantic models
- Migrated reports
- Report usage monitoring
Real-Time Analytics
We add streaming analytics with Fabric Real-Time Intelligence, Eventstream and Eventhouse for operational dashboards and alerts.
- Streaming ingestion
- KQL databases
- Real-time dashboards and alerts
Our Approach
Our Modernization Roadmap
Phased delivery that keeps the business running on trusted numbers.
- 01
Assess and Prioritize
We analyze the estate, interview report owners and select a first domain with clear value and manageable complexity.
Deliverables: Assessment report · Prioritized domain backlog
- 02
Design the Platform
We define the target architecture, capacities, workspaces, security and DevOps approach, and prove critical patterns with a short technical spike.
Deliverables: Architecture blueprint · Proof of concept results
- 03
Migrate the First Domain
We move data, transformations and semantic models for one domain end to end, and run old and new systems in parallel.
Deliverables: Migrated domain · Reconciliation results
- 04
Scale Domain by Domain
We repeat the pattern for remaining domains, reusing frameworks and refining standards along the way.
Deliverables: Migrated domains · Updated standards
- 05
Decommission and Optimize
We retire legacy components once sign-off is given, then tune capacity usage and refresh schedules.
Deliverables: Decommissioning plan · Capacity optimization report
Use Cases
Analytics Modernization Use Cases
Where modernizing on Azure produces tangible improvements.
Synapse Dedicated Pool Migration
A data team moves its dedicated SQL pool and pipelines to Fabric Data Warehouse and Data Factory, removing the need to pause and resume pools to control cost.
SSAS Cube Retirement
Multidimensional cubes are replaced with Power BI semantic models, keeping familiar measures while enabling self-service reporting.
Finance Reporting Consolidation
Month-end reports scattered across Excel and several datasets are rebuilt on a single certified model with consistent definitions.
Retail Sales Lakehouse
Point-of-sale, e-commerce and inventory data combine in a medallion lakehouse for daily margin and stock analysis by store.
Multi-Cloud Data Access
OneLake shortcuts expose data held in Amazon S3 alongside Azure data, letting analysts query both without building duplicate pipelines.
Operational Monitoring
Manufacturing telemetry streams into Eventhouse, with Real-Time Intelligence dashboards and alerts when metrics drift outside thresholds.
Technology
Analytics Technologies We Use on Azure
Microsoft-native analytics services plus open formats.
- Microsoft Fabric
- OneLake
- Fabric Data Warehouse
- Fabric Lakehouse
- Fabric Real-Time Intelligence
- Power BI
- Direct Lake
- Azure Databricks
- Azure Synapse Analytics
- Azure Data Lake Storage
- Delta Lake
- Apache Spark
- Apache Iceberg
- dbt
- Azure DevOps
- Microsoft Purview
Platforms
Analytics Platforms We Work With Alongside Azure
Why Hanoi Technology
Why Organizations Choose Hanoi Technology
Senior, Cross-Functional Teams
Strategy, data, AI, cloud and engineering specialists work as one team, so nothing is lost between hand-offs.
Proven Delivery
More than 50 projects delivered for clients in North America, Europe and Asia-Pacific.
Radical Transparency
A written update every week and a demo of working software every sprint, so you always know where things stand.
Cost-Effective Global Delivery
Experienced engineers from our Hanoi delivery hub, with working-hour overlap for every major time zone.
Success Story · Real estate
Transparent AI property valuation for a multi-city marketplace
A growing real estate marketplace wanted buyers to trust its prices. We built a valuation engine and property pages that compare the estimated value with the asking price.
Read the Full StoryMore Success Stories
E-commerce and retail
+32%conversion ratePersonalized shopping experience for a US fashion retailer
A fast-growing US fashion and lifestyle retailer had plenty of traffic but a 2.1% conversion rate. We combined a recommendation engine with a simpler path from discovery to checkout.
Logistics
−25%operational costsRoute optimization and fleet visibility for a regional logistics company
A regional delivery company handling thousands of shipments a day was planning routes and dispatching by hand. We built dynamic route optimization, a fleet dashboard and a driver app.
Resources
Featured Resources
Industry trends and practical guidance to help you get more value from data, AI and technology.
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Plan a Modernization You Can Validate
Book a free consultation to review your current analytics estate. We will suggest a first domain to modernize and explain how we would prove the new platform matches your trusted numbers.
Azure Analytics Modernization FAQ
Should we move to Microsoft Fabric or Azure Databricks?
Both are strong choices and they interoperate through Delta Lake and OneLake. Fabric suits organizations that are deeply invested in Power BI and Microsoft 365, want a SaaS experience and prefer capacity-based pricing. Azure Databricks suits teams with heavy data engineering and machine learning workloads and strong Spark skills. Many enterprises use both. We evaluate your workloads, skills and governance needs before recommending a target.
What happens to Azure Synapse Analytics?
Microsoft continues to support Azure Synapse Analytics, but new analytics investment and features are focused on Microsoft Fabric, and Microsoft publishes migration guidance for moving dedicated SQL pools and pipelines to Fabric. There is no need to panic-migrate, but new development on Synapse should be weighed carefully. We assess which of your Synapse workloads map easily to Fabric and which need redesign.
How do you ensure numbers match after migration?
We define reconciliation tests for every migrated table and key metric, comparing row counts, aggregates and sample records between the old and new systems. Old and new run in parallel for an agreed period, and business owners sign off on critical reports before the legacy component is retired. Differences are logged, explained and either fixed or accepted as intentional corrections.
How long does analytics modernization take?
A focused assessment takes a few weeks. Migrating a first domain end to end typically takes one to three months, depending on the volume of logic and reports involved. Larger estates are modernized domain by domain over several quarters. Because each domain delivers working results, the business sees value early rather than waiting for a single cutover at the end.
How is Fabric priced?
Fabric uses capacity units purchased as pay-as-you-go or reserved capacity, shared by all workloads in assigned workspaces, plus OneLake storage. Power BI viewer licensing depends on capacity size. Costs therefore depend on how workloads are scheduled and optimized. We size capacity based on your actual workloads, use the Fabric Capacity Metrics app to monitor consumption, and recommend when to scale or reserve.
Will our existing Power BI reports keep working?
In most cases, yes. Reports can be repointed to new semantic models built on Fabric tables, and Direct Lake can replace large import models where suitable. Where many reports rely on duplicated datasets, we consolidate them onto certified models and migrate reports gradually. We track report usage so effort goes into reports people actually use, and unused reports are archived.