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Data & Analytics · Power BI

The Power BI Reports That Make It Onto the Board Pack — Not Into a Folder.

Most enterprise Power BI estates accumulate hundreds of reports and lose the ten that matter. Daxonet's Power BI Development service builds the right ten — designed around the questions executives ask, performant on real-world data volumes, governed for trust. From semantic model design to embedded analytics, on Fabric or Premium capacity.

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10+
Years Power BI development
DAX
Performance-tuned models
Fabric
OneLake-native semantic
FastTrack
Microsoft co-delivery

Daxonet's Power BI Development service builds executive dashboards, semantic models, paginated reports, and embedded analytics for Malaysian enterprises across D365, AutoCount, Arcstone MES, Fabric, and Azure data sources. Engagements run 4-12 weeks depending on scope. Services include semantic-model design and DAX optimisation, executive dashboard development, paginated reporting, embedded analytics in Power Apps and websites, RLS / OLS security, lifecycle and source-control via Power BI Projects, Premium / Fabric capacity sizing, and Copilot for Power BI rollout.

Six Deliverables

What you actually receive — beyond "we built dashboards".

Six discrete deliverables, each with explicit acceptance criteria. Most engagements include 4-5 of them; the mix depends on your scope.

01

Semantic Model

Star-schema design, DAX-optimised measures, incremental refresh, RLS/OLS, Entra ID groups. The foundation under everything else.

02

Executive Dashboards

Built around board-meeting questions, not data dumps. Mobile-tested. Drill-through paths designed.

03

Paginated Reports

Pixel-perfect for LHDN submissions, audit packs, financial statements, regulatory filings. Scheduled distribution.

04

Embedded Analytics

Power BI inside Power Apps, custom portals, customer-facing websites. Authenticated and themed.

05

Copilot Enablement

Copilot for Power BI rollout, semantic model remediation for natural-language Q&A, prompt library.

06

Lifecycle Setup

Power BI Projects (PBIP) + Git, deployment pipelines (DEV/UAT/PROD), source-control discipline for analytics.

Tech Stack

The data sources we connect natively.

Every connection here is patterns Daxonet has shipped to production. We do not learn on your time.

D365 F&O / BC

Direct via dataverse / Fabric link

AutoCount

SQL connector + Daxonet templates

Arcstone MES

Direct DB or via Fabric Lakehouse

Microsoft Fabric

Direct Lake mode (sub-second)

Azure SQL / Synapse

DirectQuery + import hybrid

Snowflake / BigQuery

Native + Fabric shortcuts

Salesforce / SaaS

Native connectors + Power Automate

Excel / SharePoint

Cleanest path via dataflows

Methodology · 5 phases

How does a Power BI engagement actually run?

Question first. Model second. Dashboard third. Most failed Power BI engagements invert this — they build a dashboard around available data and discover later it doesn't answer the actual question.

  1. 01

    Question Inventory

    Stakeholder workshops. The 10 questions executives actually ask. Locked.

  2. 02

    Model Design

    Star schema. Measures. Granularity. RLS/OLS. Source-system mapping.

  3. 03

    Build

    Semantic model. Dashboards. Paginated reports. Embedded views. Lifecycle pipelines.

  4. 04

    Performance

    DAX tuning. Incremental refresh. Aggregations. Mobile-test.

  5. 05

    Enable

    Admin training. Hand-off to managed services. Quarterly review cadence.

Quality Bar

The quality bar every Daxonet Power BI deliverable meets.

⏱️ Page load < 3 seconds

Tested at full data volume, on the slowest expected user device. No "looks fine on the developer's MacBook".

Mobile-rendered

Every dashboard has explicit mobile layout. Tested on iPhone Safari + Android Chrome.

RLS-enforced

Row-level security tested with at least 3 user roles before sign-off. No "trust me, it works".

Documented measures

Every DAX measure has a description. Auto-published to a model-documentation report.

Lifecycle-ready

Power BI Projects + Git. Deploy pipelines DEV → UAT → PROD. Reproducible builds.

Accessibility-checked

WCAG 2.1 AA contrast, keyboard navigation, alt-text on all visuals. Inclusion is non-optional.

FAQ

What do clients ask before commissioning this service?

What does Daxonet's Power BI Development service actually include?
Six core deliverables. (1) Semantic model design — the data model behind every report, with DAX-optimised measures and incremental refresh. (2) Executive dashboards — designed around questions, not data. (3) Paginated reports for regulatory / printable output (LHDN forms, financial statements, audit packs). (4) Embedded analytics — Power BI inside Power Apps, custom portals, or websites. (5) RLS/OLS security — row-level and object-level access aligned to Entra ID. (6) Lifecycle management — Power BI Projects, Git integration, deployment pipelines.
Why focus on semantic models and DAX, not just dashboards?
Because the dashboards are the cheap part. The semantic model is what determines whether your reports are fast, trustworthy, and reusable across the organisation. Bad semantic models produce reports that take 30 seconds to load, contradict each other, and have to be rebuilt every quarter. Daxonet treats semantic-model design as the primary deliverable — one well-designed model supports 50+ reports without re-engineering.
How does Power BI on Fabric differ from Premium?
Fabric Power BI is the same Power BI service running on Fabric capacity instead of Premium-per-User or Premium-per-Capacity. Practical differences: Fabric capacity covers ALL data workloads (warehouse, lakehouse, ML, streaming, Power BI) under one capacity unit; Premium covers only Power BI. For organisations consolidating their data estate, Fabric is more economical and architecturally cleaner. For organisations using only Power BI without other data workloads, Premium is sometimes simpler. Daxonet's assessment models both.
Do you build paginated reports too, or just dashboards?
Yes — paginated reports are a real part of the service. Most Malaysian enterprises need pixel-perfect, printable output for LHDN submissions, audit packs, regulatory filings, customer-facing financial statements, payroll forms, and similar. Paginated reports (Power BI's successor to SSRS) handle these. Daxonet builds them with the same care we apply to interactive dashboards — formatting, parameterisation, scheduled distribution.
What about Copilot for Power BI?
We rollout Copilot for Power BI as a distinct workstream within Power BI development engagements. Copilot lets users author reports and ask questions in natural language — but only works well on well-designed semantic models with clean column names and clear relationships. Most existing Power BI estates need light remediation before Copilot lands well. Daxonet handles the remediation alongside Copilot enablement.
How do you handle multiple data sources?
Direct connection where the source supports it (D365, Fabric, Synapse, SQL, Snowflake, BigQuery, Salesforce). Fabric Lakehouse / OneLake shortcuts where data is already centralised. Direct Lake mode on Fabric for sub-second queries on large data without import. For sources without direct connectors, Power Automate flows or Azure Data Factory pipelines handle ingestion. We design the data flow before the dashboard — never the other way round.
What's your approach to performance tuning?
Five tactics applied as needed: incremental refresh on the semantic model, DirectQuery for very-large tables, Direct Lake mode on Fabric, aggregations for fact tables, and DAX measure optimisation. Most performance issues are model-design issues; most model-design issues are caught at the design phase, not at the report-rendering phase. We do not build dashboards on a wishful semantic model and tune later — we tune the model first.
Do you handle RLS, OLS, and Entra ID integration?
Yes. Row-Level Security (RLS) restricts users to specific rows based on their identity (e.g. salespeople see only their accounts, regional managers see only their region). Object-Level Security (OLS) hides specific columns or tables (e.g. salary data hidden from non-HR roles). Both bind to Entra ID groups so the access model lives in your existing identity layer, not in Power BI. We design RLS/OLS at semantic-model design time — retrofitting is painful.
Can you take over an existing Power BI estate?
Yes. Take-over engagements include a 2-week assessment that catalogues every report, scores semantic-model quality, identifies orphaned datasets, and produces a remediation backlog. Most established estates have 20-40% of reports unused, 10-30% of datasets duplicated, and 5-15% with broken refreshes. Cleanup is high-ROI and quick — your Power BI capacity load drops measurably.
Ready to start?

Book a 45-minute briefing with a Daxonet principal.

We review your current state, map a phased path to your target outcome, and tell you honestly whether we are the right partner — or who is.

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