Data
8 Projects
MASC (Manitoba Agricultural Services Corporation)
Enterprise Data Warehouse
Step 01
Business Challenge
Enterprise data was heavily fragmented across multiple legacy systems from different vendors, creating severe vendor lock-in.
Required a centralized Data Warehouse to consolidate data and streamline enterprise reporting from all legacy sources.
Needed a modernized financial system to handle complex Accounts Payable (AP) and Accounts Receivable (AR) operational requirements.
Step 02
Execution & Solution
Acted as Lead Data Architect to design the end-to-end enterprise data model and consult with engineering teams on cloud infrastructure.
Architected a Hybrid Medallion Architecture in Microsoft Fabric, leveraging Bronze and Silver Lakehouse layers alongside a Gold Data Warehouse.
Built and integrated a modern AP/AR financial system based on Dynamics 365 Business Central, utilizing incremental loads for point-in-time accuracy.
Established an Azure SQL Database repository as a fallback strategy to securely archive and retain all historical legacy data.
Tech Stack Used: Microsoft Fabric, Azure SQL Database, Dynamics 365 Business Central, Data Lakehouse, ETL/ELT.
Step 03
Business Outcomes
Delivered a fully-fledged enterprise database empowering the organization with robust, centralized reporting capabilities.
Enabled accurate point-in-time temporal reporting for finance, including complex backdated transactional visibility.
Successfully safeguarded and archived all legacy system data within a secure, queryable database.
Provided flexible storage capable of handling unstructured data by leveraging the new Bronze and Silver Lakehouse architecture.
Enterprise Architecture
Review the complete solution architecture, integration landscape, cloud services, security boundaries, data flow, and enterprise design implemented for this engagement.
Niagara Region
Enterprise Cloud Migration Roadmap
Step 01
Business Challenge
Tasked with assessing a highly fragmented, undocumented legacy estate comprising 60 servers and over 1,000 databases.
Automated discovery tools were strictly blocked due to rigorous internal PII data security and privacy policies.
Critical applications were tightly coupled to unsupported legacy SQL Server instances with rigid uptime dependencies.
Step 02
Execution & Solution
Acted as Lead Enterprise Architect to conduct an extensive technical assessment and author strategic target-state architecture blueprints.
Pivoted to a highly secure, manual reverse-engineering framework to safely map complex application dependencies, workloads, and schema compatibility.
Introduced a Four-Pillar architectural execution methodology (Stabilize -> Standardize -> Optimize -> Modernize) to evaluate cloud migration feasibility.
Mandated a strict Side-by-Side Rebuild and Migration modeling strategy for production upgrades to guarantee zero-risk rollback capabilities.
Target Tech Stack & Platforms: Azure SQL Managed Instance, Azure SQL Database, Microsoft Fabric, Legacy SQL Server.
Step 03
Business Outcomes
Designed a roadmap to eliminate unsupported legacy platforms, significantly reducing enterprise security vulnerabilities.
Established a highly actionable, secure cloud migration blueprint fully aligned with strict government data privacy regulations.
Paved the way for operational consistency through standardized patching, security configurations, and audit-ready governance.
Enterprise Architecture
Review the complete solution architecture, integration landscape, cloud services, security boundaries, data flow, and enterprise design implemented for this engagement.
City of Calgary (Legal Department)
Data and Document Migration
Step 01
Business Challenge
Legacy Fact tables contained severe repeating MatterId anomalies, threatening overall reporting integrity.
Faced strict data type constraints when mapping legacy on-premises databases to the target Dynamics Dataverse.
Encountered severe API source throttling and timeouts during Azure Data Factory (ADF) pipeline executions.
Step 02
Execution & Solution
Spearheaded the legacy system migration for the Legal Department into a modern, unified Microsoft cloud ecosystem.
Architected an Azure SQL staging layer to handle all casting, format validation, and truncation rules prior to pushing data to Dynamics.
Engineered a SQL window function to create a ranked composite key, isolating Rank 1 records to guarantee strict early-stage deduplication.
Mitigated ADF API throttling by strategically tuning Data Integration Units (DIUs) and reducing the degree of parallel copying.
Developed custom serverless Azure Functions to automate the extraction and metadata indexing of legal documents directly into SharePoint.
Tech Stack Used: Azure Data Factory, Microsoft Dynamics, Azure Functions, SharePoint, Azure SQL Database, Power BI.
Step 03
Business Outcomes
Established a highly reliable, deduplicated single source of truth for all enterprise legal reporting.
Eliminated API throttling timeouts during heavy batch processing and full historical loads.
Delivered real-time operational metrics and tracking across complex legal document workflows via Power BI.
Enterprise Architecture
Review the complete solution architecture, integration landscape, cloud services, security boundaries, data flow, and enterprise design implemented for this engagement.
Zad Holding
Enterprise Big Data Architecture & Analytics
Step 01
Business Challenge
Enterprise data was heavily siloed across sales, production, finance, and operations domains within a large-scale food manufacturing environment.
Required a centralized big data architecture capable of processing complex, high-volume datasets to deliver daily automated reporting.
Faced significant bottlenecks in capturing fresh, real-time operational data directly from the factory floor into centralized analytical repositories.
Step 02
Execution & Solution
Led a 5-person engineering team to design, build, and deploy an end-to-end enterprise big data architecture.
Engineered complex ETL/ELT pipelines utilizing Azure Databricks, SSIS, and KNIME, supported by highly optimized SQL stored procedures.
Developed statistical models and data transformation scripts .
Formulated custom Power Apps interfaces and automated workflows to stream live operational data directly into the central reporting layer.
Tech Stack Used:SSAS OLAP Cubes, SSIS, KNIME, Power BI, Power Apps, SQL Server.
Step 03
Business Outcomes
Successfully established a unified data foundation, empowering executive stakeholders with comprehensive cross-domain analytics.
Implemented SSAS multi-dimensional cubes and configured Power BI enterprise gateways with incremental refresh patterns, achieving fully automated daily reporting.
Eliminated manual data entry latency on the factory floor by deploying real-time Power Apps integration.
Extracted deep, actionable financial insights through advanced statistical modeling, driving strategic operational improvements.
Enterprise Architecture
Review the complete solution architecture, integration landscape, cloud services, security boundaries, data flow, and enterprise design implemented for this engagement.
Annalect India
Ticketing & Resource Allocation System
Step 01
Business Challenge
Internal operational workflows and resource approvals were disjointed, relying on manual requests that hindered cross-departmental coordination.
Lacked a centralized tracking system, making it difficult to monitor ticketing queues, isolate process bottlenecks, and measure actual team resource utilization.
Required a highly accessible, low-friction application that employees could adopt instantly for submitting requests.
Step 02
Execution & Solution
Architected and deployed a unified enterprise ticketing and resource allocation system leveraging the Microsoft Power Platform ecosystem.
Built intuitive, front-end canvas interfaces using Power Apps to enable seamless ticket creation and resource request submissions.
Engineered complex automated routing rules and multi-tier approval pipelines utilizing Power Automate to eliminate manual administrative overhead.
Integrated the underlying SQL Server transactional data stores with Power BI to create live operational dashboards.
Tech Stack Used: Power Apps, Power Automate, Power BI, Power Platform, SQL Server.
Step 03
Business Outcomes
Significantly accelerated resolution timelines by replacing manual routing with automated notifications and real-time status tracking.
Empowered leadership with full transparency into team resource utilization and ticketing bottlenecks via embedded Power BI analytics.
Dramatically improved cross-team coordination and administrative efficiency across the enterprise.
Enterprise Architecture
Review the complete solution architecture, integration landscape, cloud services, security boundaries, data flow, and enterprise design implemented for this engagement.
Annalect India
ITSM Analytics & Jira Power BI Integration
Step 01
Business Challenge
IT leadership lacked clear, actionable visibility into Jira Service Management ticket lifecycles, operational efficiency, and agent performance.
Required a highly customized and cost-effective analytics solution without purchasing expensive, out-of-the-box Jira reporting plugins.
Raw incident data was trapped in heavily nested JSON payloads within REST APIs, making direct analytical querying and SLA tracking nearly impossible.
Step 02
Execution & Solution
Architected a custom, cost-effective ITSM analytics solution integrating Jira Service Management directly with Power BI reporting tools.
Constructed automated data extraction pipelines utilizing Jira REST APIs and Power Automate to reliably ingest ticket lifecycles and service metrics.
Engineered robust data transformations to normalize raw JSON payload data, building custom tabular models specifically designed to track SLAs and incident trends.
Tech Stack Used: Jira REST APIs, Power BI, Power Automate, JSON Parsing, Tabular Data Modeling.
Step 03
Business Outcomes
Delivered interactive Power BI dashboards, granting leadership immediate, actionable insights into IT operational efficiency.
Streamlined administrative oversight by establishing automated data refresh cycles and rigorous security-mapped reporting views.
Significantly optimized reporting costs by leveraging existing Power Platform infrastructure instead of acquiring third-party ITSM analytics add-ons.
Enterprise Architecture
Review the complete solution architecture, integration landscape, cloud services, security boundaries, data flow, and enterprise design implemented for this engagement.
Annalect India
Multi-Agency Operational Dashboards Suite
Step 01
Business Challenge
Operational data was scattered across disparate agency branches, making enterprise-wide visibility into recruitment, portfolio management, and administration highly disjointed.
Lacked scalable dimensional models, causing slow reporting aggregations and hindering exploratory slice-and-dice analysis by leadership.
Required rigorous role-based data privacy and governance to ensure regulatory compliance across multiple internal departments.
Step 02
Execution & Solution
Designed and deployed a comprehensive suite of executive Power BI dashboards to unify recruitment, administration, and resource allocation metrics.
Architected end-to-end ETL data pipelines to ingest, clean, and consolidate multi-agency data streams into a centralized repository.
Engineered optimized dimensional data models designed specifically to support rapid visual aggregation and dynamic exploratory analysis.
Implemented strict Row-Level Security (RLS) frameworks within Power BI to guarantee data privacy and governance.
Tech Stack Used: Power BI, Data Modeling, ETL Pipelines, Row-Level Security (RLS).
Step 03
Business Outcomes
Delivered unprecedented executive visibility into operational expenses and cross-agency resource utilization.
Directly empowered leadership to transition from reactive reporting to proactive, evidence-based managerial decision-making.
Ensured strict data governance and compliance across the enterprise through scalable role-based access controls.
Enterprise Architecture
Review the complete solution architecture, integration landscape, cloud services, security boundaries, data flow, and enterprise design implemented for this engagement.
Zad Holding (Qatar Flour Mills)
ZPI Multi-Company Performance Index Engine
Step 01
Business Challenge
Operating companies across the holding group lacked a standardized method to capture, aggregate, and report crucial performance metrics.
Senior management required a secure, multi-tenant platform to ingest periodic KPIs from diverse, decentralized divisions.
Manual metric reporting lacked rigorous data governance, resulting in validation bottlenecks prior to executive review.
Step 02
Execution & Solution
Directed a 6-person engineering team to architect, build, and deploy a custom multi-tenant KPI capture and analytics platform.
Engineered secure, custom data-entry web interfaces using C# and ASP.NET to seamlessly ingest divisional performance metrics into a centralized repository.
Designed robust SSIS ETL pipelines and SSAS OLAP cubes to aggregate cross-company data sources into standardized, governable performance benchmarks.
Enforced rigorous data governance protocols within the application layer to automatically validate incoming metrics before publishing reporting suites.
Tech Stack Used: C#, ASP.NET, MS SQL Server, SSIS, SSAS OLAP Cubes, Power BI.
Step 03
Business Outcomes
Built and delivered interactive Power BI executive dashboards, empowering group-level leadership to evaluate division-wise growth and operational efficiency instantly.
Ensured 100% data validity and standardized benchmarking across the enterprise through strict front-end governance protocols.
Successfully scaled and maintained the custom platform to support nearly a decade of continuous enterprise performance tracking.
Enterprise Architecture
Review the complete solution architecture, integration landscape, cloud services, security boundaries, data flow, and enterprise design implemented for this engagement.
ERP
1 Projects
Zad Holding
Enterprise ERP Implementation & Analytics
Step 01
Business Challenge
Enterprise data was heavily siloed across distinct departments and business units, preventing holistic organizational visibility.
Lacked standardized reporting processes across multiple subsidiaries, forcing a heavy reliance on manual inter-company reconciliations.
Required a unified enterprise reporting strategy capable of consolidating fragmented subsidiary data into a single, reliable source of truth.
Step 02
Execution & Solution
Led the enterprise reporting architecture design for a large-scale Ramco ERP implementation.
Engineered a centralized SQL reporting database to ingest, map, and consolidate departmental data from various Ramco modules.
Developed custom temporal data models to accurately support complex historical and point-in-time reporting requirements.
Architected an advanced Qlik Sense analytics layer, designing executive KPI dashboards and presenting actionable insights directly to senior stakeholders.
Tech Stack Used: Ramco ERP, SQL Server, Qlik Sense, Enterprise Data Modeling.
Step 03
Business Outcomes
Successfully standardized reporting processes and significantly reduced manual data reconciliation efforts across multiple business units.
Established a robust data architecture that provided executives with accurate, consistent, and cross-subsidiary analytical capabilities.
Delivered a highly structured technical data foundation that ultimately prepared the organization for its future enterprise SAP migration initiative.
Enterprise Architecture
Review the complete solution architecture, integration landscape, cloud services, security boundaries, data flow, and enterprise design implemented for this engagement.
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