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Turn Your Data into One Connected Analytics Platform

Data & Analytics with Microsoft Fabric

Bring your data, engineering, analytics and business intelligence together with Microsoft Fabric. From OneLake and data engineering to enterprise data warehousing, real-time intelligence, Power BI and AI-powered data experiences, we help organizations design and implement scalable Microsoft Fabric solutions that turn distributed data into trusted business insights.

Whether you are starting a new data platform, modernizing an existing solution or moving from traditional Azure data services to Microsoft Fabric, we can help you design the right architecture and implement it.

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What is Microsoft Fabric?

Microsoft Fabric is Microsoft's unified data and analytics platform, bringing data integration, data engineering, data warehousing, real-time intelligence, business intelligence and AI-powered data experiences into a single SaaS environment.

At the centre of Fabric is OneLake, a unified data lake for the organization. Fabric workloads can work with data through this common foundation, helping organizations reduce separate data silos and build a more connected data estate.

For organizations that have spent years building separate ETL platforms, data lakes, warehouses, analytical systems and reporting solutions, Fabric provides an opportunity to rethink the architecture as one connected platform.

But adopting Fabric is not simply about moving existing pipelines and reports into a new technology. The architecture still matters. You need to decide:

  • How should your data be organized in OneLake?
  • Should you use a Lakehouse, Warehouse, SQL Database or a combination?
  • What should be ingested, mirrored, accessed through shortcuts or transformed?
  • How should data engineering and transformation workloads be structured?
  • How should semantic models and Power BI solutions consume the data?
  • How should real-time data be processed and analyzed?
  • How should security, governance, environments and deployment be managed?
  • How should Fabric capacity be planned and optimized?
  • How can AI agents securely work with your enterprise data and business context?

This is where our experience in enterprise data architecture, engineering, analytics and AI comes together with Microsoft Fabric.

What Can We Implement with Microsoft Fabric?

We can help you design and implement an end-to-end Fabric data platform rather than treating Fabric as only another reporting or ETL technology.

  • Enterprise Data Platform

    Build a centralized data estate using OneLake, Lakehouses, Warehouses and other Fabric workloads, bringing together data from operational systems, cloud platforms, databases, files, APIs and other enterprise sources. We help define how the platform should be organized so that data is reusable, governed and ready for analytical and AI workloads.

  • Data Integration & Engineering

    Design ingestion and transformation solutions using Fabric Data Factory, pipelines, notebooks, Spark and other Fabric engineering capabilities. We can support batch, incremental and near-real-time processing patterns and help determine the most appropriate approach for each source and workload.

  • Modern Data Warehouse

    Design and implement dimensional, analytical and enterprise data warehouse solutions using Fabric Warehouse, Lakehouse and SQL-based architectures. The right architecture depends on your data, business requirements, reporting workloads, engineering practices and future analytical needs rather than simply choosing one Fabric workload.

  • OneLake, Mirroring & Shortcuts

    Bring distributed enterprise data closer together without unnecessarily copying everything. Depending on the source and requirement, we can design solutions using OneLake, Mirroring and Shortcuts to provide a more unified data estate while maintaining appropriate ownership and access patterns.

  • Real-Time Intelligence

    Design solutions for streaming, event and operational data using Microsoft Fabric Real-Time Intelligence. This enables organizations to analyze events and changing business conditions as they happen rather than depending only on traditional scheduled data processing and reporting.

  • Power BI & Semantic Models

    Build the business consumption layer using Power BI and governed semantic models. We can help create reusable business metrics, analytical models, reports and dashboards so that users across the organization work with consistent and trusted information.

  • Fabric Data Agents & Conversational Analytics

    Build Microsoft Fabric Data Agents that allow users to interact with enterprise data using natural language. Instead of requiring every user to understand tables, columns, SQL or KQL, a Data Agent can provide a conversational experience over supported Fabric data sources, helping users ask business questions and obtain data-driven answers. Data Agents can work with Fabric sources including Lakehouses, Warehouses, SQL databases, mirrored databases, KQL databases and other supported analytical artifacts.

  • Fabric IQ & Business Context

    Take analytics beyond tables and columns by describing enterprise data in the language of the business. Fabric IQ can represent concepts such as customers, products, orders, shipments or assets, together with their properties, relationships and business meaning. This business context can then be used by people, analytics solutions and AI agents. This creates an important bridge between the technical structure of enterprise data and the way the business actually understands and talks about it. Fabric IQ is currently a preview capability within Microsoft Fabric.

  • Integrating Fabric with Microsoft Foundry

    Extend your Fabric data platform into enterprise AI and agentic solutions using Microsoft Foundry. Fabric Data Agents can be connected to Foundry Agent Service, allowing Foundry agents to use governed enterprise information from Microsoft Fabric as part of their responses and workflows. Fabric IQ can also be connected to Foundry agents, allowing agents to reason using business entities, relationships and semantic meaning rather than relying only on the physical structure of tables and columns. This enables solutions where an enterprise agent can combine Fabric data with instructions, APIs, business applications, other knowledge sources and workflows while continuing to respect appropriate Fabric permissions and access controls.

  • Security & Governance

    Design workspace structures, access controls, data security, lineage and governance practices appropriate for enterprise Fabric environments. Security and governance should be part of the architecture from the beginning rather than something added after the solution has been implemented.

Microsoft Fabric in the Real World – Our Experience with Retail and Finance Solutions

Technology alone does not create a successful data platform. The platform must organize data around real business requirements and make that information useful to people across the organization. We have implemented Microsoft Fabric solutions for retail and finance scenarios, bringing data from different operational systems into centralized analytical platforms and making it available for engineering, analysis, reporting and business decision-making.

  • Retail – Building a Connected Retail Data Platform

    Retail data rarely comes from one system. Sales transactions, products, inventory, customers, stores, promotions, suppliers and digital channels can all live in different applications and data platforms. We have used Microsoft Fabric to bring these datasets into a unified analytical architecture where data can be integrated, processed, modelled and made available for business analysis and reporting.

    A Fabric-based retail solution can support areas such as:

    • Sales and revenue analysis
    • Store and channel performance
    • Product and category performance
    • Inventory and stock analysis
    • Customer purchasing behaviour
    • Promotion and campaign analysis
    • Historical trends
    • Executive and operational Power BI reporting

    The objective is not simply to move retail data into OneLake. The objective is to create a trusted data platform where business users can understand what is happening across the operation using consistent information that can be reused across reports, analytical workloads and AI solutions.

  • Finance – Creating a Governed Financial Analytics Platform

    Finance data requires accuracy, consistency, traceability and controlled access. Data may originate from ERP systems, accounting applications, operational databases and supporting business systems, while management reporting often requires information to be combined across many of them. We have implemented Fabric solutions that bring financial and operational information together into a governed analytical environment.

    A Fabric-based finance platform can support areas such as:

    • Financial performance analysis
    • Revenue and expense reporting
    • Budget versus actual analysis
    • Profitability analysis
    • Customer and product financial analysis
    • Management and executive reporting
    • Historical analysis and reconciliation
    • Controlled access to sensitive financial information

    Our focus is on building the underlying architecture correctly so that financial and management reporting is based on reliable and reusable data rather than separate datasets created independently for individual reports.

How Can You Engage with dinesQL?

Every organization has a different level of internal capability and requires a different type of support. You do not have to outsource your complete Microsoft Fabric project to work with us. We offer three primary engagement models.

  • Complete Fabric Implementation – Outsource the Entire Project to Us

    You provide the business requirements and access to the required systems, and we take responsibility for designing and implementing the solution. A complete engagement can include: Requirements → Architecture → Environment Setup → Data Integration → Data Engineering → Lakehouse/Warehouse → Semantic Models → Power BI → Deployment → Knowledge Transfer. This model is suitable when you need an experienced team to take responsibility for delivering your Microsoft Fabric solution end to end.

  • Architecture & Design – Let Us Design It Before You Build It

    You may already have an internal engineering team but need experienced architects to make the important decisions before implementation begins. We can work with you on:

    • Existing environment assessment
    • Fabric suitability assessment
    • Target architecture
    • OneLake design
    • Workspace and domain design
    • Lakehouse and Warehouse architecture
    • Data integration patterns
    • Mirroring and Shortcut strategy
    • Real-time architecture
    • Security and governance
    • Capacity and performance considerations
    • Deployment approach
    • Implementation roadmap

    At the end of the engagement, your team can continue the implementation with a clearly defined architecture, recommended patterns and implementation plan.

  • Fabric Experts & Resources – Extend Your Existing Team

    If your organization already owns and manages the project, we can provide experienced Microsoft Fabric architects, data engineers, BI engineers and consultants to work alongside your existing team. Resources can support a particular area of the implementation or participate throughout the project. This model is suitable when you need additional Fabric skills or capacity without outsourcing the complete project.

Why Work with dinesQL?

We bring more than 20 years of experience in data platforms, data warehousing, analytics and business intelligence, combined with hands-on experience implementing modern Microsoft data platforms.

Microsoft Fabric may be a relatively new platform, but many of the difficult problems it addresses are not new. Designing a successful enterprise data platform still requires experience in:

  • Data architecture
  • Data integration
  • Data engineering
  • Data modelling
  • Data warehousing
  • Performance and scalability
  • Security and governance
  • Business intelligence
  • Enterprise analytics
  • AI and agent integration

Our focus is therefore not simply on implementing Fabric features. Our focus is on designing and implementing the right data solution using Microsoft Fabric.

Frequently Asked Questions

Can dinesQL design our complete Microsoft Fabric architecture?

Yes. We can assess your existing data environment, business requirements and future plans and design an end-to-end Fabric architecture covering OneLake, workspaces, Lakehouses, Warehouses, data integration, engineering, real-time workloads, Power BI, security, governance and AI integration.

Should we use a Lakehouse or Warehouse?

There is no single answer that applies to every organization. Fabric supports multiple analytical patterns, and enterprise implementations may use a Lakehouse, Warehouse or a combination of workloads. We determine the appropriate architecture based on your source systems, transformation requirements, engineering skills, analytical workloads, reporting requirements and future plans.

Can we migrate our existing Azure data platform to Fabric?

Yes. If you currently use services such as Azure Data Factory, Azure Data Lake, Azure Synapse, Azure SQL, Databricks or Power BI, we can assess the current architecture and determine what should move to Fabric, what should remain where it is and what should be redesigned. We do not recommend migrating a component simply because an equivalent capability exists in Fabric. The first step should be understanding whether moving it provides a technical or business benefit.

Can Fabric work with our existing data without moving everything?

Yes. Not all enterprise data has to be physically copied into a new location. Depending on your source systems and requirements, Fabric provides capabilities such as OneLake Shortcuts and Mirroring that can be considered as part of the architecture. We can assess your data sources and determine where ingestion, replication, mirroring, shortcuts or other integration patterns are most appropriate.

Do we need to replace Power BI when adopting Fabric?

No. Power BI is a core workload within Microsoft Fabric. Your existing Power BI environment can form part of the broader Fabric architecture, and we can help determine how existing semantic models, reports, workspaces and data sources should evolve as part of the Fabric implementation.

Can you help us if we have already started implementing Fabric?

Yes. We can review the existing implementation, understand the architecture and identify areas that may require improvement. Depending on what has already been implemented, we may recommend extending the existing design, changing specific components or redesigning parts of the solution. We normally assess the existing environment before making that recommendation.

Can you help us with Fabric capacity and performance?

Yes. Capacity and performance should be considered as part of the architecture rather than only after the solution has been implemented. We can review workloads, data volumes, processing patterns, concurrency and usage requirements and help design the solution with performance and Fabric capacity utilization in mind.

Can you build Data Agents over our Fabric data?

Yes. We can design and implement Microsoft Fabric Data Agents that allow users to ask natural-language questions against supported enterprise data in Fabric. The solution can include configuring the appropriate data sources, providing additional instructions and business context, testing the questions users are expected to ask and integrating the Data Agent into a broader AI solution where required.

Can Fabric be integrated with Microsoft Foundry agents?

Yes. Microsoft supports integrating Fabric Data Agents with Foundry Agent Service, allowing a Foundry agent to use Fabric as a source of enterprise data. Fabric IQ can also provide business context to agents, allowing them to work with concepts and relationships that are meaningful to the business. This is particularly useful when building enterprise agents that need to combine organizational data with APIs, applications, workflows and other knowledge sources.

Can you implement only one part of our Fabric solution?

Yes. You may engage us for a specific area such as architecture and design, data ingestion, data engineering, Lakehouse implementation, data warehouse implementation, Real-Time Intelligence, Power BI and semantic models, Data Agents, Fabric IQ, Foundry integration, migration, performance optimization or security and governance. You do not need to outsource the complete project.

Do you provide Fabric resources to work with our internal team?

Yes. We can provide technical resources who work as part of your existing project team while your organization retains overall ownership of project management and delivery. This can be for a specific requirement or for a longer implementation period.

Do you provide support after implementation?

Yes. Depending on the engagement, we can continue supporting, monitoring, enhancing and reviewing the Fabric environment after implementation. If the existing solution was implemented by another organization, we would normally perform an assessment before taking responsibility for ongoing support.

We are not sure whether Microsoft Fabric is right for us. Can you help?

Yes. Your first engagement with us does not have to be an implementation project. We can assess your existing architecture, data sources, workloads, business requirements, internal skills and future plans and determine whether Microsoft Fabric is appropriate and how it should fit within your existing technology estate.

How do we start?

Start by talking with our AI Agent. Tell the Agent about your existing data platform, the challenges you are facing and what you are planning to achieve with Microsoft Fabric. Our AI Agent can explain our Fabric services, help you understand how we may be able to support your project and answer questions about working with us. When you are ready, you can also make an appointment with one of our consultants directly through the AI Agent to discuss your requirements in detail. From there, we can determine whether you need a complete Fabric implementation, architecture and design support, or experienced Fabric resources to work with your existing team. You can also write to us directly, go to Contact Us page and initiate the first conversation.

Planning a Microsoft Fabric Project?

Whether you are building a new data platform, modernizing an existing environment, moving workloads to Fabric or exploring how Fabric data can support AI and agentic solutions, talk with us. Talk with our AI Agent to discuss your requirements, learn how we can help and make an appointment with one of our consultants.

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