Luthfy Es-haq

Business Systems Specialist

I lead CRM, automation, analytics, AI, and cloud data initiatives that modernize business operations.

Business Systems Specialist specializing in CRM, automation, analytics, and digital transformation, with 6+ years of combined experience across business analysis, Dynamics 365 CE, Power Platform, BI, and cloud data delivery. I lead enterprise systems initiatives as the primary technical systems owner and internal consultant, translating operational needs into governed platforms, reporting infrastructure, and scalable workflows.

Dynamics 365 CE Power Platform Power BI AI Projects Azure Data
Owner Primary technical systems owner for CRM, automation, analytics, cloud data, and AI projects
Builder Hands-on across solution architecture, automation, reporting models, DAX, SQL, and data pipelines
Operator Governed delivery across requirements, QA, vendor coordination, UAT, change, and documentation
Professional headshot

Professional Focus

CRM, Analytics & Digital Transformation

Business systems ownership, automation, AI project delivery, reporting strategy, and cloud data infrastructure

Proof Points

Career highlights that show systems ownership, delivery scope, and business impact.

Primary Systems Owner

Lead enterprise CRM, automation, analytics, reporting, cloud data, and AI initiatives as the organization's primary technical systems owner and internal consultant.

$2M+ Reporting Impact

Built CRM-to-AWS-to-Power BI reporting infrastructure and a 30+ dashboard analytics suite supporting funder reporting, executive visibility, and impact analysis.

$23K+ Integration Case

Secured approval for an integration initiative by translating operational needs into a business case for CRM automation, reporting, and market intelligence.

AI Governance & Delivery

Established AI governance protocols, market intelligence frameworks, and scalable workflows supporting executive reporting and operational decision-making.

About Me

Built through self-directed learning, persistence, and hands-on delivery.

I entered this field without a formal tech background, coming from an economics and finance foundation while working in operations as a restaurant supervisor. Through self-directed learning and persistence, I built my way into systems, automation, analytics, and CRM delivery by focusing on practical problem-solving and continuously developing technical skills on my own. That path shaped how I work today: disciplined, adaptable, and committed to building solutions that create real business value.

Luthfy working in a collaborative office setting

Technical Skills

Hands-on across platforms, data, cloud, and delivery.

Platforms

Dynamics 365 CE, Dataverse, Power Platform, Power Apps, Power Automate, Customer Insights - Journeys, SharePoint

Data & Analytics

Power BI, DAX, Power Query, SQL, Excel, outcome analysis

Cloud & Integration

AWS, Azure SQL, Azure Data Factory, Azure Blob Storage, REST APIs, Skyvia

Delivery

Requirements gathering, QA, stakeholder management, vendor coordination, technical documentation, change management, UAT, business rules, user stories

Languages

Python, JavaScript, TypeScript, GitHub, ALM, Vercel

Certifications

Credentials that back delivery.

  • AZ-900
  • DP-900
  • Google Data Analytics Professional Certificate
  • PMI-PBA (In progress)

Case Studies

Selected case studies, curated by strongest business and technical signal.

Featured projects appear first. Details have been generalized to respect organizational confidentiality while preserving the scope, tools, technical decisions, and business outcomes.

CRM Automation

80-95% less manual effort

Export Plan Intake & Workflow Automation

Architected Export Plan automation using Dynamics 365 real-time journeys, custom forms, and Power Automate to deliver PDFs, validate intake data, and create CRM interaction records.

Challenge

Export Plan submissions needed immediate client follow-up, multi-condition validation, controlled CRM record creation, and a cleaner advisor follow-up process.

What I Owned

Solution design, custom form flow, Power Automate branching logic, validation expressions, CRM interaction record creation, and the Real-time Journeys PDF delivery path.

Stack

Dynamics 365 CE, Customer Insights - Journeys, Power Automate, Dataverse

Impact

Improved advisor follow-up by combining automated PDF delivery with validated CRM interaction records and a cleaner intake trail.

01

Export Plan Form

The client submits the Export Plan form through the digital intake experience.

02

PDF Delivered

Real-time Journeys immediately sends the relevant PDF/resource email as soon as the form is submitted.

03

Validation Checks

Power Automate evaluates multiple if conditions before allowing the record to move forward.

04

CRM Record Created

Once validated, a CRM record is created so advisors can review and work the intake.

05

Advisor Handoff

Advisors review the CRM interaction record and follow up with better context.

AI Integration

7-person team, 5-phase delivery

Vertex AI Chatbot & CRM Workflow Integration

Led a cross-functional AI chatbot integration initiative focused on lead qualification, export-plan completion support, and advisor handoff through CRM-integrated workflows.

Challenge

The organization needed a practical AI workflow that could support clients, qualify leads, and route advisor follow-up without creating unmanaged automation risk.

What I Owned

Led delivery across a 7-person team, coordinated vendor and internal requirements, shaped CRM workflow integration, and supported governance around AI readiness and handoff logic.

Stack

Vertex AI, Dynamics 365 CE, Power Automate, CRM workflow design, vendor coordination

Impact

Created a structured path for AI-assisted client support, improved lead qualification design, and strengthened advisor handoff through CRM-connected workflows.

01

Client Intent

The chatbot captures client needs and guides users through export-plan support questions.

02

Qualification Logic

Conversation inputs help structure lead qualification and identify follow-up requirements.

03

CRM Workflow

Qualified interactions are designed to connect into CRM workflows for advisor visibility.

04

Advisor Handoff

Advisors receive cleaner context for follow-up instead of starting from a blank intake.

05

Governed Delivery

Requirements, QA, stakeholder feedback, and vendor coordination keep the AI workflow controlled.

Dataverse Design

Stronger data completeness

Dataverse Data Model & Form Experience

Designed a Dataverse schema and model-driven app experience that enforced relational structure, validation, and cleaner data capture at the point of entry.

Challenge

A new business process needed structured data capture, relational integrity across records, and stronger controls to prevent incomplete or inconsistent entries.

What I Owned

Dataverse schema design, custom tables, 1:N and N:N relationships, choice columns, business rules, and JavaScript form scripting for onLoad/onChange behavior.

Stack

Dataverse, Dynamics 365 model-driven apps, JavaScript

Impact

Improved data completeness and consistency through validation, conditional visibility, and auto-population built directly into the user workflow.

01

Data Domain

A new business process is translated into a structured Dataverse data model.

02

Schema Design

Custom tables, relationships, and choice columns define how records connect and behave.

03

Business Rules

Platform rules enforce required logic and guide cleaner data entry at the form level.

04

Form Scripting

JavaScript handles onLoad and onChange behavior for validation, visibility, and auto-population.

05

Cleaner Records

Users complete forms more consistently, giving the business more complete and reliable data.

Azure SQL Backend

Normalized database design

Service Request Management System Backend

Designed and implemented an Azure SQL backend for a service request management system, creating a normalized relational model with lookup tables, constraints, assignment tracking, comments, and a reporting-ready SQL view.

Challenge

The system needed a reliable backend structure that avoided free-text sprawl, enforced valid request categories and statuses, and could support future Power Apps and Power BI integration.

What I Owned

Azure SQL schema design, normalized table structure, primary and foreign keys, priority constraints, seed/reference data, timestamp trigger logic, and reporting view creation.

Stack

Azure SQL Database, T-SQL, relational modeling, SQL views, triggers

Impact

Created a governed backend foundation for request intake, status tracking, assignment history, comments, and analytics-ready reporting.

01

Lookup Tables

Categories and statuses are stored as controlled reference data instead of repeated free text.

02

Request Table

The main service request table stores requester, priority, due date, category, and status data.

03

Relationships

Foreign keys enforce valid category, status, comment, and assignment relationships.

04

Database Logic

Constraints and trigger logic maintain priority rules and updated timestamps at the database layer.

05

Reporting View

A SQL view exposes readable request data for future Power BI reporting and Power Apps display.

View full SQL build script
CREATE TABLE dbo.sr_category (
  category_id INT IDENTITY(1,1) PRIMARY KEY,
  category_name NVARCHAR(200) NOT NULL UNIQUE,
  is_active BIT NOT NULL DEFAULT 1
);

CREATE TABLE dbo.sr_status (
  status_id INT IDENTITY(1,1) PRIMARY KEY,
  status_name NVARCHAR(100) NOT NULL UNIQUE,
  is_closed BIT NOT NULL DEFAULT 0
);

CREATE TABLE dbo.sr_request (
  request_id BIGINT IDENTITY(1,1) PRIMARY KEY,
  title NVARCHAR(200) NOT NULL,
  description NVARCHAR(MAX) NULL,
  requester_name NVARCHAR(200) NOT NULL,
  requester_email NVARCHAR(320) NULL,
  category_id INT NOT NULL,
  status_id INT NOT NULL,
  priority NVARCHAR(20) NOT NULL DEFAULT 'Medium'
    CHECK (priority IN ('Low','Medium','High','Urgent')),
  created_at DATETIMEOFFSET NOT NULL DEFAULT SYSDATETIMEOFFSET(),
  updated_at DATETIMEOFFSET NOT NULL DEFAULT SYSDATETIMEOFFSET(),
  due_at DATETIMEOFFSET NULL,
  CONSTRAINT FK_sr_request_category FOREIGN KEY (category_id)
    REFERENCES dbo.sr_category(category_id),
  CONSTRAINT FK_sr_request_status FOREIGN KEY (status_id)
    REFERENCES dbo.sr_status(status_id)
);

CREATE TABLE dbo.sr_comment (
  comment_id BIGINT IDENTITY(1,1) PRIMARY KEY,
  request_id BIGINT NOT NULL,
  comment_text NVARCHAR(MAX) NOT NULL,
  commented_by NVARCHAR(200) NOT NULL,
  commented_at DATETIMEOFFSET NOT NULL DEFAULT SYSDATETIMEOFFSET(),
  is_internal BIT NOT NULL DEFAULT 0,
  CONSTRAINT FK_sr_comment_request FOREIGN KEY (request_id)
    REFERENCES dbo.sr_request(request_id) ON DELETE CASCADE
);

CREATE TABLE dbo.sr_assignment (
  assignment_id BIGINT IDENTITY(1,1) PRIMARY KEY,
  request_id BIGINT NOT NULL,
  assigned_to NVARCHAR(200) NOT NULL,
  assigned_at DATETIMEOFFSET NOT NULL DEFAULT SYSDATETIMEOFFSET(),
  unassigned_at DATETIMEOFFSET NULL,
  CONSTRAINT FK_sr_assignment_request FOREIGN KEY (request_id)
    REFERENCES dbo.sr_request(request_id) ON DELETE CASCADE
);

INSERT INTO dbo.sr_status (status_name, is_closed)
VALUES
  ('New', 0),
  ('Acknowledged', 0),
  ('In Progress', 0),
  ('Waiting on Requester', 0),
  ('Resolved', 1),
  ('Cancelled', 1);

INSERT INTO dbo.sr_category (category_name)
VALUES
  ('Program Enrollment'),
  ('Service Access / Eligibility'),
  ('Data / Reporting Request'),
  ('Technical Support'),
  ('Account / Profile Update'),
  ('Training / Workshop Request'),
  ('Other');

CREATE TRIGGER dbo.trg_sr_request_updated_at
ON dbo.sr_request
AFTER UPDATE
AS
BEGIN
  SET NOCOUNT ON;

  UPDATE r
  SET updated_at = SYSDATETIMEOFFSET()
  FROM dbo.sr_request r
  INNER JOIN inserted i ON r.request_id = i.request_id;
END;

CREATE VIEW dbo.vw_service_requests AS
SELECT
  r.request_id,
  r.title,
  r.description,
  r.requester_name,
  r.requester_email,
  c.category_name,
  s.status_name,
  s.is_closed,
  r.priority,
  r.created_at,
  r.updated_at,
  r.due_at
FROM dbo.sr_request r
JOIN dbo.sr_category c ON r.category_id = c.category_id
JOIN dbo.sr_status s ON r.status_id = s.status_id;

Analytics Delivery

Campaign targeting and CRM visibility

Marketing Analytics, Segmentation & Embedded BI

Analyzed CRM and marketing data across multiple tables using Power BI, DAX, Power Query, and Excel to improve campaign targeting, stakeholder visibility, and CRM-embedded reporting.

Challenge

Teams needed better visibility into client segments, campaign performance, and marketing outcomes without relying on manually assembled reporting.

What I Owned

CRM data analysis, Power BI modeling, DAX measures, Power Query transformations, reporting design, access configuration, scheduled refreshes, and CRM embedding.

Stack

Dynamics 365 CE, Power BI, DAX, Power Query, Excel

Impact

Improved campaign targeting and contributed to a roughly 10% year-over-year increase in trade newsletter subscriptions.

01

CRM Data

Client, campaign, and engagement data is analyzed across CRM tables and reporting extracts.

02

Segmentation

Power BI, DAX, Power Query, and Excel help identify target client segments and campaign patterns.

03

Reporting Model

Modeled datasets and measures translate raw CRM activity into usable marketing insights.

04

Publishing & Access

Reports are deployed with controlled access and scheduled refreshes for stakeholder use.

05

Embedded Dashboards

Dashboards are embedded in Dynamics 365 CRM so teams can use insights in their workflow.

Data Engineering

100K+ records per cycle

On-Demand ELT Pipeline from Dataverse to Azure SQL

Implemented an on-demand ELT pattern that moved Dataverse data through raw, staged, and published Azure layers before loading curated outputs into Azure SQL.

Challenge

The pipeline needed to meet security requirements, preserve raw and transformed storage layers, and control cost through on-demand execution.

What I Owned

Blob zone design, ADF transformations, Azure SQL loading, app registrations, authentication, access controls, firewall configuration, and cost-aware on-demand execution.

Stack

Dataverse, Azure Blob Storage, Azure Data Factory, Azure SQL, app registrations, access controls

Impact

Created a reliable, cost-conscious ELT process that produced secure, analytics-ready outputs for reporting.

01

Dataverse Extract

Operational data is pulled from Dataverse only when a run is needed.

02

Landing Zone

Raw extracts are stored in Blob Storage to preserve the source layer.

03

ADF Transformations

Data Flows shape the raw files into more usable staged outputs.

04

Publish + SQL Load

Final transformed data is prepared for consumption and loaded into Azure SQL.

05

Secure, Cost-Controlled Access

Firewall rules and on-demand execution keep the pipeline secure and efficient.

Python Analytics

5+ pages transformed into reporting data

SIAL Website Data Collection & Reporting Analysis

Developed a Python/Jupyter workflow that scraped multi-page web data, normalized it into analysis-ready DataFrames, and produced visual reporting outputs.

Challenge

Reporting information was spread across multiple web pages and needed to be collected, parsed, standardized, and analyzed before it could support decision-making.

What I Owned

Scraping workflow development in Jupyter, HTML parsing with BeautifulSoup, cleaning and normalization with Pandas, DataFrame-based analysis, and chart/dashboard creation.

Stack

Python, Jupyter, BeautifulSoup, Pandas, Matplotlib, Plotly

Impact

Enabled event reporting and prospect analysis where no downloadable attendee list was available.

01

Source Pages

Reporting data is gathered from more than five pages on the target website.

02

HTML Parsing

BeautifulSoup extracts the relevant fields and structures them for downstream use.

03

Cleaning & Normalization

Pandas standardizes formats, cleans irregular values, and prepares the data for analysis.

04

Analysis

DataFrames are used to explore patterns, summarize results, and structure reporting outputs.

05

Charts & Dashboards

Matplotlib and Plotly turn the processed data into visuals that are easier to interpret and share.

AWS Reporting

30+ dashboards, ~90% faster reporting

CRM-to-AWS-to-Power BI Reporting Infrastructure

Built and owned the reporting layer for a CRM-to-Skyvia-to-AWS-to-Power BI infrastructure using Athena/SQL views, Power Query, and DAX to support funder reporting and executive visibility.

Challenge

Government and funder reporting required reliable, repeatable analytics from CRM data that moved through a monthly Skyvia-to-AWS ingestion process.

What I Owned

Supported the AWS-side data engineering foundation, then owned Athena/SQL views, Power BI modeling, Power Query transformations, DAX measures, dashboard delivery, gateway connectivity, and CRM embedding.

Stack

Dynamics 365 CE, Skyvia, AWS S3, AWS Glue DataBrew, AWS Glue Crawler, Athena, SQL views, Power BI, DAX, Power Query

Impact

Delivered a 30+ dashboard analytics suite supporting $2M+ in funding, automating roughly 85% of legacy reporting and reducing funder reporting turnaround by about 90%.

01

CRM + Skyvia

CRM data is retrieved through a monthly Skyvia ingestion process and moved into AWS.

02

AWS Storage & Prep

Data lands in S3 and is prepared through DataBrew and crawler-driven metadata discovery.

03

Athena/SQL Views

Athena and SQL views create a queryable layer for downstream Power BI reporting.

04

Power BI Model

Power Query and DAX transform the data into reporting models, measures, and executive dashboards.

05

Funder Reporting

Embedded dashboards support internal reporting, executive visibility, and funder-facing impact analysis.

Sanitized Work Sample

Power BI Gateway Migration Plan

A migration plan for moving a Power BI On-premises Data Gateway from a user-managed workstation to a cloud-hosted Windows VM, improving refresh reliability and reducing single-point-of-failure risk.

View Work Sample

Project Snapshot

How I turn business needs into governed systems delivery.

Business Framing

Translate stakeholder needs into current-state gaps, target workflows, reporting requirements, user stories, and measurable success criteria before building.

System Design

Design the right combination of CRM architecture, Dataverse schema, automation logic, reporting models, cloud data services, and integration patterns for the use case.

Governed Delivery

Apply validation, security, access controls, QA, documentation, UAT, vendor coordination, and controlled release practices so solutions stay reliable after launch.

Measured Outcomes

Focus on cleaner data, reporting reliability, process efficiency, operational visibility, funding support, and faster decisions rather than features alone.

How I Work

Structured, technical, and business-aware.

I start with process clarity

I map the current state, identify friction points, and define the workflow, data, and reporting outcomes before moving into build mode.

I build with governance in mind

I think about validation, security, access, ALM, supportability, and release management early so solutions remain usable and trustworthy after launch.

I work closely with stakeholders

I use workshops, feedback loops, QA, UAT, vendor coordination, and documentation to keep solutions aligned with how teams really operate.

What I Bring

Enterprise ownership paired with business-minded delivery.

Cross-functional thinking

I connect CRM, automation, reporting, AI project delivery, and cloud data pipelines into systems that support operations, advisory work, marketing, executive reporting, and funder-facing analysis.

End-to-end solution delivery

I carry work from requirements and business cases through architecture, implementation, testing, deployment, documentation, adoption, and post-launch ownership.

Business impact mindset

I focus on improving data quality, reporting reliability, process efficiency, and decision visibility in ways teams can adopt and leadership can measure.

Experience

Leading CRM, automation, analytics, AI, and cloud data delivery.

Business Systems Specialist

World Trade Centre Winnipeg | 04/2023 - Current

Lead CRM, analytics, automation, reporting, AI, and cloud data initiatives as the primary internal technical systems owner and internal consultant, with hands-on delivery across Dynamics 365 CE, Power Platform, AWS/Power BI reporting infrastructure, Azure SQL datasets, and governed releases.

Lead Business Analyst

Benbros Motors Ltd | Dar Es Salaam, Tanzania | 01/2011 - 08/2014

Built an early foundation in business analysis, Excel-based analytics, budget variance reporting, inventory dashboarding, and workflow mapping by supporting marketing, finance, inventory, and operations teams with recurring reporting and process improvement.

CRM & Automation Leadership

Lead solution architecture across Dynamics 365 CE, Dataverse, Power Automate, Customer Insights - Journeys, and governed CRM workflows.

Analytics & Reporting Delivery

Own Power BI, DAX, Power Query, SQL/Athena views, and embedded reporting that supports executive, operational, and funder-facing decisions.

Internal Consulting & Vendors

Operate as an internal consultant across business teams while coordinating vendors, external consultants, requirements, QA, and delivery quality.

Governance & Change

Coordinate UAT, change management, documentation, ALM, and controlled releases so solutions move into production with stability and continuity.

Get In Touch

Start a conversation.

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Education

Academic background

Red River College Polytechnic

Diploma in BA: Financial Services (Honors)

04/2022

University of Manitoba

Bachelor of Arts: Economics Major/Management Minor

02/2020

FITT

Diploma in International Trade

Expected 12/2026 | 5/6 courses completed

Value Add

Built for operations, analytics, and trusted delivery.

Strong in translating stakeholder needs into governed, scalable systems across CRM, automation, analytics, AI project delivery, and cloud data pipelines. Comfortable owning the full path from business case and requirements to implementation, adoption, reporting, and release management.