FarshidShahoSardar

Fabric Monitoring Tool (FMT) & Data Quality Platform

I led the design and development of a Microsoft Fabric monitoring and data-quality platform for the Information Governance & Digital Enablement function within the Infrastructure Services Division — giving governmental leads and business stakeholders a single point of visibility across Fabric workspaces, lakehouses, notebooks, pipelines, semantic models, Power BI reports, records, schema structures, and data-quality checks.

Designed as a practical governance layer (similar to Microsoft Purview) sitting on top of the department’s Fabric environment, it provided executive and technical overviews of active workspaces, lakehouses, tables, schemas, row/file volumes, refresh status, pipeline health, and failed or stale loads — with lakehouse detail pages showing table-level metadata, storage size, row counts, last-refresh dates, and quality indicators.

A major component was data-quality monitoring: interactive dashboards assessing connected datasets across accuracy, completeness, consistency, reliability, timeliness, and relevance — translating backend checks into visual summaries that sped up issue identification and remediation across capital works, infrastructure, project, budget, milestone, region, and delivery datasets.

The platform also introduced structured metadata, lineage, and relationship mapping — interactive modelling views and data-flow maps from source systems through ingestion pipelines, Python/PySpark notebooks, lakehouses, and dashboard outputs — bridging backend engineering and business-facing information governance, and standardising how assets are scanned, catalogued, checked, and reviewed.

NDIS Power BI Ecosystem

I modernised the Power BI landscape supporting NDIS reporting and internal decision support — re-engineering legacy static outputs into role-aware, interactive dashboards that non-technical users can trust and act on. Solutions included drill-through journeys, field parameters, bookmarks, tooltip pages, and action-based navigation surfacing plan utilisation, caseload health, service expiries, invoice throughput, and exception flags in seconds. I also built paginated, pixel-perfect reports consistent with the shared semantic model.

On the platform side I worked hands-on with Azure Analysis Services as the semantic layer — modelling star-schema tables, refining DAX measures, and partitioning for refresh and query performance. Power BI connected live to AAS for a single source of truth; perspectives and calculation groups simplified self-service while protecting business logic. I designed and enforced Row-Level Security end-to-end via user UPNs, role maps, and Azure AD groups (validated against test personas), tuned ETL handoffs, reduced model weight, and cut query latency while strengthening governance and compliance.

MERIT Lumina — NDIS KPI Tracker & Performance Platform

As Founder & Technical Director, I led the design and delivery of MERIT Lumina — a purpose-built KPI tracking and performance-management platform for the disability-support sector. It helps NDIS providers move away from fragmented spreadsheets and reactive compliance toward a unified, real-time view of organisational performance, bringing operational, financial, workforce, service-delivery, participant-outcome, compliance, and risk data into a single environment.

The platform provides a full executive overview — KPI cards, status indicators, thresholds, trend lines, performance classifications, and risk flags — with dedicated modules for sales, finance, marketing, employee performance, DevOps & delivery, CRM, customer success, client operations, alerts & exceptions, workflow notifications, escalation pathways, owner assignments, action tracking, and report generation.

A key feature is KPI drilldown and exception management: filtering by domain, timeframe, status, and business function to surface underperformance, overdue tasks, unresolved risks, SLA breaches, service-delivery gaps, workforce pressures, client risks, and compliance exceptions — moving organisations from passive reporting to active performance management with owners, escalation, and resolution tracking.

Workflow and accountability features (alerts, approval queues, action registers) support operational governance, while the reporting layer delivers audit-ready outputs, executive summaries, and structured templates across KPI, staff, compliance, participant outcomes, financial, and regional performance — strengthening transparency and leadership line-of-sight across performance, risk, and service quality.

Labour Market Assessment & Information Observatory

I led the design and development of a comprehensive Labour Market Assessment and Labour Market Information Observatory platform supporting national analysis of private-sector employment demand, skills gaps, TVET alignment, and labour-market trends — an end-to-end solution covering the full data lifecycle from survey administration and collection tracking through validation, cleaning, analytics, dashboards, deliverables management, and automated reporting.

What began as a data-collection and analytics solution evolved into a multi-user operational platform used by UNESCO and government stakeholders (Ministries of Education, Higher Education, and Labour & Social Affairs), with role-based administration, bilingual interface elements, province-level structures, survey-link management, response monitoring, stakeholder mapping, visibility reports, and organised deliverables.

A key feature was its row-level security and controlled-access model — restricting users to data relevant to their province, role, institution, or point-of-contact responsibility — functioning as a governed information-management system supporting accountability, traceability, and secure collaboration. It ingested and consolidated data from online survey tools, Excel, PDFs, uploaded files, and paper-based information processed through OCR workflows.

The analytical dashboard suite translated validated data into decision-ready insights — over 1,900 approved responses across 10 provinces, with indicators covering labour-market health, the skills ecosystem, green-economy readiness, digital-economy needs, and province-level employment constraints — supported by KPI cards, heatmaps, filters, methodology notes, and challenges-and-recommendations modules for evidence-based TVET planning and policy.

RS Core — Property Intelligence Platform

As Lead Consultant for a national-level real estate analytics initiative, I led the architecture and deployment of a full-stack analytical platform to uncover market dynamics, investment patterns, and price behaviour across the Australian property landscape — integrating Microsoft Fabric (Data Factory for ingestion, OneLake for lakehouse modelling) to manage and analyse millions of high-volume records.

I oversaw automated pipelines extracting, cleaning, and consolidating data from real estate portals, public land registries, valuation sources, and geographic datasets; and using Python, SQL, and ClickHouse, supported predictive models for rent estimation, sales-price forecasting, temporal market analysis, and regional investment intelligence — initially via a dynamic Power BI suite connected to OneLake with price segmentation, postcode-level geospatial analytics, time-series forecasting, rental-yield and agent-level analytics, and a data-integrity scoring module.

As the project matured, I led its evolution into RS Core — a dedicated web platform with modules for market snapshots, suburb analytics, single-property analysis, property lists, suburb comparison, market correlations, investment scoring, economic intelligence, supply-pressure analysis, agent analytics, property alerts, and finance calculators — consolidating millions of records across listings, suburb profiles, economic indicators, and agent datasets.

A core strength is combining property data with broader economic and financial signals — ABS indicators, house-price-index trends, CPI, wage growth, unemployment, RBA cash-rate context, building approvals, ASX market data, and market-cycle positioning — alongside proprietary investment-score, economic-health, and supply-pressure models, transforming fragmented datasets into a unified intelligence platform for investors, professionals, and planners.

KCPU — Community Perception (AI-Driven)

As Lead Consultant for the Kurdistan Community Perception and Understanding (KCPU) initiative funded by the KRG, I managed a large-scale community assessment using advanced data analytics, AI-driven methodologies, and sophisticated Power BI dashboards. Leading a diverse team of 40+ analysts and specialists, I oversaw comprehensive data collection and deep quantitative and qualitative analysis — sentiment analysis, object detection, data triangulation, and predictive analytics — to capture community perceptions on employment trends, economic needs, and sector-specific opportunities.

Engaging closely with governmental bodies, stakeholders, and educational institutions, I ensured robust, actionable insights for strategic policy development. The approach significantly influenced KRG’s economic planning — directly informing workforce-development policy, vocational training aligned with community demand, and strategic investment in high-potential sectors such as green energy and ICT, supporting sustainable growth and improved employment outcomes.

COVID-19 Media Monitoring & Rumour Tracking (MMRT)

As Lead Consultant for UNICEF’s Media Monitoring and Rumour Tracking (MMRT) initiative during the COVID-19 pandemic, I directed a comprehensive, multi-channel data-collection effort capturing public perceptions, concerns, and behavioural attitudes toward COVID-19 vaccination across online and offline platforms, including face-to-face engagements.

I led meticulous data cleansing and advanced analytics using AI models, sentiment analysis, and predictive algorithms to understand community attitudes, vaccination willingness, prevailing rumours, misinformation, and behavioural barriers. A cornerstone was an advanced, AI-driven Power BI dashboard that dynamically tracked perceptions, predicted behavioural trends, and visualised complex datasets interactively — enabling real-time decision-making for UNICEF and key stakeholders.

Market Analytics & BI (AI-Driven)

As Lead Consultant for Toyota Iraq’s advanced automotive market-analytics initiative, I oversaw the design and implementation of a sophisticated AI-driven analytics system and data-management framework tailored for deep market insight and strategic positioning — integrating multiple complex data streams, from AI-enhanced social-media sentiment and field-level qualitative insights (interviews, focus groups) to quantitative data from targeted online surveys.

Leveraging AI, predictive modelling, and data mining, I led the creation of detailed, interactive Power BI dashboards delivering real-time visualisations, advanced analytics, sales-performance tracking, and predictive forecasting — integrating with existing CRM and SFA systems — and guided narrative-driven strategic recommendations, empowering Toyota’s internal teams through capacity-building and targeted training.