Unified Data Analytics Platform

Microsoft Fabric Consulting Australia

End-to-end Microsoft Fabric implementation: OneLake storage, medallion lakehouse architecture, real-time data pipelines, and high-performance Power BI Direct Lake models.

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Microsoft Fabric Consulting Australia Architecture

OneLake

Unified Microsoft Fabric medallion data lakehouse architecture processing batch and streaming telemetry into Gold star-schema semantic models.

The Challenge

Siloed Data Estates and Expensive Fragmented Pipelines

Modern organisations suffer from data fragmented across legacy relational databases, cloud storage buckets, third-party SaaS tools, and local spreadsheets. This creates multiple conflicting versions of truth, slow query performance, and excessive compute licensing costs across separate ingestion and analytics tools.

Data teams spending 80% of their time stitching together fragile ETL pipelines
Slow report refresh times and high latency across large enterprise datasets
Duplicated data storage costs across separate warehouses and data lakes
Inconsistent security models making row-level access governance impossible

How AgenorIT Delivers Microsoft Fabric Consulting Australia

AgenorIT provides specialized Microsoft Fabric consulting for Australian organisations. We architect unified OneLake data estates using the medallion architecture (Bronze, Silver, Gold), build automated ingestion pipelines, and deliver high-performance Direct Lake semantic models that provide instant analytical insights without data duplication.

AgenorIT Engineering Practice

Measurable Outcomes

Expected Business & Architectural Impact

Single Source

Unified OneLake Data Estate

Consolidating all enterprise data into a single, open Delta Parquet format, eliminating duplicate storage and ETL overhead.

Sub-second DAX

Instant Direct Lake Queries

Power BI reports reading directly from OneLake Delta tables with zero import delays and lightning-fast sub-second performance.

Delta Lakehouse

Governed Medallion Architecture

Clear, reproducible data curation stages ensuring raw ingestion data is rigorously cleaned, validated, and business-ready.

GenAI Ready

AI & Copilot Readiness

Cleaned, catalogued enterprise data structured to power generative AI copilots and predictive machine learning models.

What We Deliver

Tangible Engineering Deliverables

We deliver concrete, production-ready artefacts into your repositories and cloud tenants—not slide decks or vague advisory hours.

Lakehouse & Storage

A deployed Microsoft Fabric capacity and workspace topology aligned with departmental governance
OneLake storage foundation with Delta Lakehouse and Delta Lake table optimizations (V-Order compression)
Medallion architecture implementation: Bronze (raw), Silver (cleansed/joined), Gold (star-schema facts & dimensions)

Pipelines & Engineering

Fabric Data Pipelines and Dataflows Gen2 orchestrating automated ingestion from internal and SaaS sources
PySpark notebooks and SQL Stored Procedures for scalable data transformation and deduplication
Automated data quality validation and pipeline error alerting mechanisms

Analytics & Governance

Power BI Direct Lake semantic models with certified measures and business logic
OneLake security definitions including row-level and column-level security policies
Fabric capacity sizing, cost allocation monitoring, and performance tuning guide

Technologies & Toolchains

Engineered using verified, production-grade tools and industry-standard frameworks.

Microsoft Fabric

OneLake

Delta Parquet

Apache Spark / PySpark

Power BI Direct Lake

Data Factory

Dataflows Gen2

Azure Data Lake Storage

T-SQL

Engagement Model

Structured Delivery Process

A disciplined, transparent delivery framework designed for predictability and rapid time-to-value.

Step 01

Data Estate Assessment

Audit existing databases, API sources, reporting bottlenecks, and target analytics use cases across the organisation.

Timeline: 1–2 Weeks

Key output: Fabric Roadmap & Capacity Sizing Plan

Step 02

Lakehouse Architecture & Medallion Design

Design the workspace hierarchy, Delta schema models, data retention policies, and security permissions.

Timeline: 2 Weeks

Key output: Data Model & Security Architecture

Step 03

Pipeline Engineering & Lakehouse Build

Develop automated ingestion pipelines, Spark transformation notebooks, and Delta Lakehouse structures.

Timeline: 3–5 Weeks

Key output: Operational Fabric Lakehouse

Step 04

Direct Lake Models & Handover

Build Direct Lake semantic models, executive reporting views, and deliver technical training to your data analysts.

Timeline: 1–2 Weeks

Key output: Validated Power BI Models & Runbook

Architecture Decision Guide

Evaluating Your Technical Approach

Comparing Legacy Data Warehouses vs Microsoft Fabric OneLake Lakehouse
Architecture Dimension	Legacy Synapse / SQL Warehouse	Microsoft Fabric OneLake
Storage Format
Power BI Performance
Capacity Billing
Data Governance

Verified Engineering Impact

Enterprise Analytics Modernisation with Microsoft Fabric

Client Context

Victorian logistics and freight enterprise consolidating 6 disparate SQL databases into a unified OneLake repository.

Architectural Outcome

Direct Lake query execution under 800ms across 120M+ rows with zero import refresh lag, 8-hour batch windows replaced with 12-minute delta syncs, and 45% reduction in cloud data infrastructure costs.

When Microsoft Fabric is not the right fit

If your organisation only needs to query a single static database with simple transactional reports and does not require cross-departmental data integration, big data processing, or AI model training, standard Azure SQL and basic Power BI reporting is far more cost-effective.

Technical FAQ

Microsoft Fabric Consulting Australia — Technical FAQ

Direct engineering answers to common technical and commercial queries.

OneLake is the unified "OneDrive for data" in Microsoft Fabric. It provides a single SaaS-based data lake for the entire organisation where every data item is stored in open Delta Parquet format, allowing BI analysts, data scientists, and engineers to query the exact same data without making duplicate copies.

Traditional Import mode requires duplicating large datasets into Power BI memory on a schedule, leading to memory limits and stale data. Direct Lake queries Delta tables in OneLake directly with the speed of Import mode, but without any data copying or refresh delays.

Yes. Fabric uses the On-Premises Data Gateway and native connectors in Data Factory and Dataflows Gen2 to securely extract data from on-premises SQL Server, Oracle, SAP, Salesforce, and third-party cloud data warehouses.

Fabric is licensed on unified Capacity SKUs (from F2 up to F2048) or through Microsoft 365 Power BI Premium capacities (P-SKUs). We evaluate your query concurrency and data processing volume to recommend the most cost-effective capacity tier.

Yes. Cleaned Gold-layer data in OneLake can be directly indexed by Azure AI Search and integrated with Azure OpenAI models to build intelligent, context-aware AI copilots grounded in your approved business facts.

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