https://store-images.s-microsoft.com/image/apps.9894.8bc44b36-c95f-4850-90a0-083c07355606.c89b6696-8978-4a31-bb4a-f590399332c7.2e7c077f-0c3f-41a3-9b4e-178ee402dc6c

Migrate & Modernize to Microsoft Fabric or Azure Synapse Analytics

WaferWire Cloud Technologies

We enable our customers to quickly transform fragmented, legacy, and high-maintenance data environments into a modern, secure, and analytics-ready data estate typically within 4โ€“12 weeks.

As part of WCTโ€™s ๐——๐—ฎ๐˜๐—ฎ ๐—˜๐˜€๐˜๐—ฎ๐˜๐—ฒ ๐— ๐—ผ๐—ฑ๐—ฒ๐—ฟ๐—ป๐—ถ๐˜‡๐—ฎ๐˜๐—ถ๐—ผ๐—ป (DEM) practice, we enable our customers to quickly transform fragmented, legacy, and high-maintenance data environments into a modern, secure, and analytics-ready data estateโ€”typically within 4โ€“12 weeks. Our approach brings the right expertise, proven methodologies, and pre-built accelerators to deliver rapid modernization with minimal disruption.

๐—ง๐—ต๐—ฒ ๐—ผ๐˜‚๐˜๐—ฐ๐—ผ๐—บ๐—ฒ: Reduced technical debt, improved governance, lower operating costs, and a data foundation that allows your business to scale AI and advanced analytics with confidence.

๐—ช๐—ต๐—ฎ๐˜ ๐˜„๐—ฒ ๐—ฑ๐—ผ ๐—ต๐—ฒ๐—ฟ๐—ฒ:

  1. Conduct a comprehensive Assessment of your current data landscape, operational challenges, and business bottlenecks
  2. Define a future-ready target data architecture on the platform of your choice, Microsoft Fabric or Azure Synapse Analytics
  3. Migrate and modernize your critical data, models, and pipelines with minimal disruption
  4. Establish enterprise-grade governance, observability, security, and cost-optimization frameworks
  5. Empower business teams with trusted, high-quality data and intuitive self-service analytics capabilities

You Choose right-fit platform, Fabric or Synapse and we take care of everything else to get you production-ready in weeks, not months

๐—ข๐—ฝ๐˜๐—ถ๐—ผ๐—ป ๐Ÿญ: ๐— ๐—ผ๐˜ƒ๐—ฒ ๐˜๐—ผ ๐—™๐—ฎ๐—ฏ๐—ฟ๐—ถ๐—ฐ ๐˜„๐—ถ๐˜๐—ต ๐—ช๐—–๐—ง

Best when:โ€ฏYou want a single, unified data and analytics experience with strong Power BI integration and less platform overhead.

๐—ช๐—ต๐—ฎ๐˜ ๐˜„๐—ฒ ๐—ฑ๐—ฒ๐—น๐—ถ๐˜ƒ๐—ฒ๐—ฟ

  1. Assessment of current warehouses, marts, reports, and pipelines
  2. Fabric workspace and OneLake structure, security model, and basic governance
  3. Migration of 1โ€“3 priority domains into Fabric (data, models, reports)
  4. Initial set of Fabric-based dashboards and data products

Hand-off with playbooks and training for your data and BI teams

๐—›๐—ผ๐˜„ ๐—ถ๐˜ ๐˜๐˜†๐—ฝ๐—ถ๐—ฐ๐—ฎ๐—น๐—น๐˜† ๐—ฟ๐˜‚๐—ป๐˜€

โ€ข Weeks 1โ€“2โ€ฏโ€“ Assess current estate, pick first use cases, design target setup

โ€ข Weeks 3โ€“6โ€ฏโ€“ Stand up Fabric, migrate and build a working pilot

โ€ข Weeks 7โ€“12โ€ฏโ€“ Expand to more domains and harden operations (monitoring, governance, adoption)

We use our own accelerators (e.g., for moving existing models and reports, unifying customer/subject data, handling documents and semi-structured data) to shorten timelines and reduce risk.

๐—ข๐—ฝ๐˜๐—ถ๐—ผ๐—ป ๐Ÿฎ: ๐— ๐—ผ๐˜ƒ๐—ฒ ๐˜๐—ผ ๐—ฆ๐˜†๐—ป๐—ฎ๐—ฝ๐˜€๐—ฒ ๐˜„๐—ถ๐˜๐—ต ๐—ช๐—–๐—ง

Best when:โ€ฏYou want more control over the platform, prefer a PaaS-style architecture, or plan a phased journey that may later include Fabric.

๐—ช๐—ต๐—ฎ๐˜ ๐˜„๐—ฒ ๐—ฑ๐—ฒ๐—น๐—ถ๐˜ƒ๐—ฒ๐—ฟ

  1. Assessment of current data warehouse(s), marts, ETL, and reporting
  2. Synapse workspace and data lake zone design (raw, curated, semantic)
  3. Migration of a first priority workload (e.g., finance, sales, operations)
  4. Optimized models and pipelines ready for BI and downstream apps
  5. Runbooks, monitoring setup, and guidance for operating the platform

๐—›๐—ผ๐˜„ ๐—ถ๐˜ ๐˜๐˜†๐—ฝ๐—ถ๐—ฐ๐—ฎ๐—น๐—น๐˜† ๐—ฟ๐˜‚๐—ป๐˜€

โ€ข Weeks 1โ€“2โ€ฏโ€“ Assess existing estate and design the target Synapse setup

โ€ข Weeks 3โ€“6โ€ฏโ€“ Build the foundation and deliver a working pilot workload

โ€ข Weeks 7โ€“12โ€ฏโ€“ Migrate additional domains, tune performance, and stabilize operations

Again, we lean on repeatable patterns, accelerators and templates to avoid โ€œone-offโ€ builds and give you a platform you can extend.

๐—ช๐—ต๐˜† ๐—ช๐—–๐—ง?

โ€ข Clear starting point: 2-week assessment that ends with a simple, prioritized plan for Migration

โ€ข Cross-functional PODs: Data engineers, BI developers, and platform engineers working as one team with your stakeholders

โ€ข Accelerator-driven: Reusable code, templates, and patterns from past projects baked into your project from day one

โ€ข Value-focused: First use cases chosen for visible business impact, not just โ€œplumbingโ€

โ€ข Adoption-minded: Training, documentation, and simple ownership models so your teams can run and extend what WCT builds

๐—Ÿ๐—ฒ๐˜โ€™๐˜€ ๐—š๐—ฒ๐˜ ๐—ฆ๐˜๐—ฎ๐—ฟ๐˜๐—ฒ๐—ฑ

๐—–๐—ผ๐—ป๐˜๐—ฎ๐—ฐ๐˜ ๐—ช๐—ฎ๐—ณ๐—ฒ๐—ฟ๐—ช๐—ถ๐—ฟ๐—ฒ ๐—–๐—น๐—ผ๐˜‚๐—ฑ ๐—ง๐—ฒ๐—ฐ๐—ต๐—ป๐—ผ๐—น๐—ผ๐—ด๐—ถ๐—ฒ๐˜€. ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐˜๐—ฟ๐˜‚๐˜€๐˜๐—ฒ๐—ฑ ๐—ฝ๐—ฎ๐—ฟ๐˜๐—ป๐—ฒ๐—ฟ ๐—ณ๐—ผ๐—ฟ ๐—ฐ๐—น๐—ผ๐˜‚๐—ฑ ๐—บ๐—ถ๐—ด๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐˜€๐˜‚๐—ฐ๐—ฐ๐—ฒ๐˜€๐˜€

At a glance

https://store-images.s-microsoft.com/image/apps.23933.8bc44b36-c95f-4850-90a0-083c07355606.c89b6696-8978-4a31-bb4a-f590399332c7.b113ce2e-24c4-42eb-aa1e-19eddcd96953