Data, BI & Decision Intelligence
Amayztech connects fragmented operational data, builds trusted data foundations, and turns them into reporting and decision-ready insight. From integration pipelines and data warehouses to semantic models and Power BI dashboards, we design the layer between your source systems and the decisions people need to make.
End-to-end data capability
Design the structure, ownership and flow of data around reporting and decision requirements.
Connect applications, databases, files, APIs and operational systems into reliable pipelines.
Create governed analytical stores for cross-system reporting, history, scale and reuse.
Build dimensional models, semantic layers, shared measures and trusted KPI definitions.
Deliver Power BI dashboards, operational reports, management reporting and drill-through analysis.
Surface trends, exceptions, bottlenecks and priorities so people can act while the information still matters.
The foundation matters
When reporting depends on manual extracts, spreadsheets and conflicting definitions, the dashboard inherits the uncertainty.
The reporting layer can only be as reliable as the data foundation beneath it.
Where trust breaks down
Operational systems, spreadsheets and documents hold different parts of the picture.
Teams repeatedly extract, combine and correct the same information.
Reports arrive late — and meetings become debates about which number is right.
How we start
We start with the decisions, source systems, history, refresh needs and governance requirements. Then we choose the shortest reliable path — direct integration where it is enough, or a warehouse, lakehouse or governed data layer where scale, history and reuse require more.
No unnecessary architecture. No fragile reporting shortcuts.
The data path
From fragmented source systems to a governed data foundation and decision-ready reporting.
Data starts across the applications, databases, documents and files already running the operation.
Reliable pipelines connect, transform, validate and reconcile information across those sources.
Where history, scale, reuse or governance requires it, we establish the analytical layer behind reporting.
Technical data becomes reusable business definitions, models, measures and governed KPIs.
The trusted data layer powers the reports, dashboards, alerts and analysis people use to make decisions.
What we design & build
Connect operational applications, databases, APIs, files and third-party systems through reliable ingestion and transformation pipelines.
Build centralized analytical foundations that bring multiple sources together, preserve history and support governed reporting at scale.
Establish trusted definitions, validation rules, ownership and access so reports are built from data people can rely on.
Turn technical data structures into reusable business measures, dimensions and definitions that reporting teams use consistently.
Build operational, management, board and regulatory reporting with the drill-through and context needed to understand what is happening.
Move beyond static reporting by surfacing trends, exceptions, ageing, bottlenecks and priorities that support action.
Technology & engineering
We combine BI tools with the data engineering, integration and modeling work required to make them useful in a real operating environment.
Analytics and BI
Integrated ingestion, engineering, warehouse/lakehouse and Power BI workloads over OneLake
Where clients already have established platforms, we can integrate with and extend the existing environment rather than forcing a replacement.
Industry use cases
The dashboards below are synthetic examples built to show the kind of decision surface we design. The data is illustrative — the structure is how these operations actually report.
Regulators & Public Authorities
Supervisory data is often distributed across licensing records, filings, casework, spreadsheets and manually assembled reports. That makes basic questions about workload, ageing and attention difficult to answer quickly.
What becomes visible
Financial Services
Data can sit across core systems, workflow tools, document repositories and spreadsheets, making pipeline reporting late and cycle-time analysis difficult to trust.
What becomes visible
Associations & Licensing Bodies
Membership, renewal, licensing and continuing-education information often lives in separate systems and spreadsheets, limiting early visibility into lapses and incomplete requirements.
What becomes visible
Professional & Legal Services
Engagement progress is often spread across practice systems, documents, email and individual trackers, so blocked work and capacity issues surface later than they should.
What becomes visible
How we deliver
Clarify the decisions, metrics, users, source systems, history, refresh needs, security and reporting obligations.
Choose the right integration and storage pattern, then build pipelines across applications, databases, files and APIs.
Create trusted models and measures, reconcile against source reality, and build the reports and dashboards people actually use.
Document the data model, apply appropriate access controls, train the team and establish a practical path for new measures, reports and enhancements.
Why Amayztech
Integration, pipelines, warehouses, models and data quality are part of the solution when the reporting requirement needs them.
We design around cases, approvals, applications, obligations, transactions, documents and the real states work moves through — not only generic executive KPIs.
Measures, dimensions and reporting logic are designed so different teams are not arguing over whose spreadsheet is correct.
Documentation, reusable models, administrative control and handover are part of the engagement rather than an afterthought.
Not always. If the reporting requirement can be served reliably from a small number of structured sources, direct integration may be the better answer. A warehouse or lakehouse becomes valuable when you need cross-system history, reusable data, stronger governance, analytical performance or a common source for many reports.
Yes. Amayztech can design the data and reporting layer across Microsoft technologies such as Fabric, Power BI, SQL and related integration services, while connecting the operational systems around them.
Yes. Most engagements start with an existing environment. We connect and extend systems where that is the practical choice rather than requiring wholesale replacement.
No. Source quality, missing fields, inconsistent definitions and reconciliation issues are normally part of the discovery and engineering work. The important step is making those issues visible rather than hiding them inside the dashboard.
Yes, but the goal is not simply to reproduce the spreadsheet visually. We identify the data sources, calculations and business rules behind it and automate the reporting path where practical.
A focused dashboard using accessible, reasonably structured data can often be delivered in weeks. A broader warehouse, multi-system integration or governance programme depends on source complexity, history and data quality.
Yes. Engagements can include ongoing dashboard enhancement, data-pipeline support, new reporting requirements, model changes and operational support.
Tell us which report takes too long, which numbers your teams do not trust, or which operational question your current systems cannot answer. We can work backwards from that requirement to the data, architecture and reporting layer needed to solve it.
