One data environment instead of many separate tools
Reports are already in Power BI, but each team prepares data differently. Pipelines were created in several tools, metric definitions are diverging, and access and costs are difficult to control. Microsoft Fabric organizes these layers in one environment—from data ingestion and storage through preparation to analysis and reporting.
Astrafox starts with the decisions the data needs to support. We inventory sources, dependencies, reports, roles, and workloads. We then design the target architecture, an implementation or migration plan, and an accountability model for further development.
When Microsoft Fabric makes sense
- Teams work with different copies of data. A shared data layer and agreed definitions reduce manual reconciliation of results.
- Power BI has grown beyond reporting alone. The project also covers data ingestion, transformations, models, permissions, monitoring, and maintenance.
- Pipelines and warehouses are fragmented. A Fabric architecture organizes their roles, dependencies, and method of publishing data.
- Data arrives continuously. Real-Time Intelligence supports scenarios in which a team monitors events and responds to important signals.
- The organization is planning a migration. We first assess the use of current solutions, requirements, and risks, and only then establish the migration sequence.
What we implement and develop in Microsoft Fabric
OneLake, lakehouse, and data warehouse
We design how data is stored and shared in OneLake. We assign the roles of the lakehouse and warehouse according to the data type, teams, and analysis method. We establish the workspace structure, data layers, naming, accountability, and quality rules so a user can trace a report back to its source and metric definition.
Data pipelines in Data Factory
We build and organize pipelines that feed the platform from ERP and CRM systems, databases, APIs, files, and custom applications. The project covers transformations, schedules, dependencies, error handling, quality controls, and monitoring. We document the logic so development of the environment does not depend on one person’s knowledge.
Real-Time Intelligence
We design event analytics for processes that require a current view of the situation. We establish which signals matter, how long to retain the data, who receives the information, and what action follows a detected event. A data stream does not complete the process—the result needs to reach an accountable person who knows what to do next.
Power BI in Fabric
Power BI is the reporting and analytics layer in the Fabric ecosystem. We design semantic models, reports, permissions, and the publication process using data prepared on the platform. As a result, KPI definitions, data quality, and maintenance accountability are established together with the report rather than only after discrepancies appear.
See Power BI implementation and development →
Security and permissions
We organize roles, access to workspaces and data, and administrator responsibilities. The project addresses information classification, environment separation, the change-release path, monitoring, and the organization’s access requirements. We design permissions from the outset together with the data architecture.
Capacity and cost control
We select the capacity model based on workloads, the number of users, the refresh method, and the development plan. We monitor resource use, identify costly operations, and establish rules for launching additional workloads. Cost depends on the architecture and measured usage, so we do not start by prescribing one configuration for every company.
Migration to Microsoft Fabric
A migration starts with a map of sources, pipelines, models, reports, schedules, permissions, and owners. The assessment covers not only code but also solution usage and the business significance of the data. This becomes the basis for the work sequence, result-matching criteria, and user cutover plan.
We migrate solutions from Alteryx and other data-preparation environments, warehouses, and BI platforms. We recreate the necessary logic, simplify unnecessary dependencies, validate the results, and document the new environment. We do not automatically copy every element—we retain what provides value and has an owner.
Migration validated in a real-world environment
In a project for an international organization, the scope included auditing Alteryx flows, mapping the logic, migrating data preparation to Microsoft Fabric, recreating schedules and quality controls, and validating results. The new architecture was connected to Power BI. This is an example of a migration in which the technical transfer of flows was one stage—data consistency, reporting continuity, and the ability to maintain the solution were equally important.
Fabric and DataFlow in one data environment
DataFlow organizes data preparation when a company needs explicit logic, quality controls, and AI support for building flows. Microsoft Fabric provides a broader data and analytics environment. We connect the two solutions according to the role each needs to perform in the architecture—without duplicating transformations or accountability.
For example, DataFlow prepares and controls data from operational systems, Fabric stores it and makes it available to teams, and Power BI presents agreed metrics. AI-generated proposals undergo validation, and a person with the appropriate permissions approves the change.
Maintenance and continued development
After launch, we monitor pipelines, refreshes, capacity use, permissions, and errors. We develop the platform with additional sources, data layers, semantic models, and reports. The backlog connects business priorities with technical work so the environment owner can see what is being maintained, what is being developed, and who is accountable for each change.
See SLA-based support for solutions and integrations →
How we deliver an implementation
- Discovery. We establish the decisions, recipients, sources, current solutions, and acceptance criteria.
- Architecture and plan. We design the roles of OneLake, the lakehouse, warehouse, pipelines, Power BI, permissions, and monitoring.
- First scope. We launch a selected data pipeline and report to verify the architecture in a real-world scenario.
- Migration or development. We move subsequent dependencies, compare results, and conduct tests with data owners.
- Maintenance. We establish monitoring, request handling, accountability, and the development backlog.
What determines scope and cost
The scope follows from the number and type of sources, data quality, existing pipelines, transformation complexity, number of environments, security requirements, workloads, reports, and maintenance responsibilities. The first discussion does not require complete documentation. It is enough to identify an important report or process, its sources, and the issue that currently takes time or undermines trust in the data.
Frequently asked questions about Microsoft Fabric
What is Microsoft Fabric used for?
Microsoft Fabric brings data and analytics work into one environment. It includes data ingestion and processing, OneLake, a lakehouse, a warehouse, event analytics, and Power BI. We select the implementation scope according to the organization’s architecture and needs.
How does Power BI work with Microsoft Fabric?
Power BI uses data and models prepared in Fabric and remains the reporting and analytics layer. The project covers shared metric definitions, semantic models, permissions, and the report publication method.
What does a migration to Microsoft Fabric involve?
We start by inventorying sources, pipelines, models, reports, and dependencies. We then design the target environment, migrate the selected scope, compare results, conduct tests, and switch users over in stages.
Can Alteryx flows be migrated to Microsoft Fabric?
Yes. We first map the workflows, components, schedules, and quality controls in use. We then recreate the necessary logic in the target architecture and validate the results before cutover.
How do you control Microsoft Fabric costs?
Costs are controlled by matching capacity to workloads, monitoring usage, optimizing operations, and establishing rules for launching additional workloads. We assess the model based on how the environment is actually used, not only on the number of reports.
Does Astrafox maintain Microsoft Fabric environments after implementation?
Yes. We monitor pipelines, refreshes, capacity, and errors, handle requests, and develop sources, models, and reports through an agreed backlog.