Design Session: "Data-Driven Organization Based on Intelligent Data Platform"

Intelligence IconExecutive Brief

Duration: 4 hours (can extend to full day with deep-dives)

Target Audience: C-suite, IT Leadership, Data Teams, Business Unit Leaders

Outcome: Actionable roadmap for becoming a data-driven organization using Microsoft Fabric

Compute Icon SESSION ARCHITECTURE

Analysis IconPart 1: The Reality Check
"Your Data Estate Isn't Working - Let's Fix It"
Duration: 45 minutes

1.1 The Fragmentation Audit (20 min)

  • Interactive exercise: Map your current data landscape
  • Identify the "data graveyards" - where valuable data goes to die
  • Calculate your real data duplication factor (typically 3-7x)
  • The cost of "shadow IT" analytics solutions

1.2 The Failed Promise of Data Lakes (15 min)

  • Why your data lake became a swamp
  • The mesh paradox: solving silos by creating more silos
  • Real numbers: 73% of data lakes never reach production value

1.3 The AI Readiness Gap (10 min)

  • Quick assessment: "Can you train an ML model on last quarter's data in <1 hour?"
  • The brutal truth: Most can't even locate all relevant data
  • Setting the stage: No AI transformation without data foundation
Key Deliverable: Heat map of your data pain points
Cloud IconPart 2: The OneLake Revolution
"One Lake to Rule Them All"
Duration: 60 minutes

2.1 Architectural Deep-Dive (20 min)

  • OneLake vs traditional approaches - live comparison
  • The "OneDrive for Data" mental model
  • Delta Lake format: Why open standards matter
  • Shortcuts: Virtual data without movement

2.2 Hands-On Lab (25 min)

Participants use their laptops

  • Create a OneLake workspace
  • Set up shortcuts to existing data (S3, ADLS, on-prem)
  • Query across clouds without moving data
  • Experience the "it just works" moment

2.3 Governance Without Friction (15 min)

  • Domains and workspaces: Decentralized ownership, centralized control
  • Microsoft Purview integration: Compliance by default
  • Data lineage and discovery: Finding data in seconds, not days
Key Deliverable: Working OneLake proof-of-concept with participant's data
Insight IconPart 3: Analytics Acceleration with Fabric
"From Data to Decision in Minutes, Not Months"
Duration: 60 minutes

3.1 The Unified Experience (15 min)

  • Live demo: Data engineering to BI in one platform
  • The "Office for Data" paradigm
  • Cost model that makes sense: Capacity, not complexity

3.2 Scenario Workshops (35 min)

Break into groups, each tackling different use cases:

Track A: Real-Time Operations
  • Build streaming pipeline with EventStreams
  • Create real-time dashboard
  • Set up alerts and automated actions
Track B: Predictive Analytics
  • Data preparation with Dataflows Gen2
  • Train ML model in Fabric
  • Deploy and monitor predictions
Track C: Self-Service Analytics
  • Business user creates semantic model
  • Natural language queries with Copilot
  • Publish insights to Teams

3.3 Integration Reality (10 min)

  • Fabric + Power Platform: Low-code analytics apps
  • Fabric + Dynamics: Embedded insights
  • Fabric + Microsoft 365: Analytics where users live
Key Deliverable: Working analytics pipeline for participant's scenario
AI IconPart 4: AI-Powered Transformation
"Making Every Employee a Data Analyst"
Duration: 60 minutes

4.1 Copilot Everywhere (15 min)

  • Live coding with Copilot in Notebooks
  • Natural language to SQL/KQL
  • Automated insight generation
  • Report creation in seconds

4.2 Building Custom AI Solutions (30 min)

Hands-On: Create a Data Agent

  • Connect to your OneLake data
  • Configure RAG pipeline
  • Build natural language interface
  • Test with real business questions

4.3 The LLM Advantage (15 min)

  • Direct Azure OpenAI integration
  • SynapseML for distributed AI
  • Custom models grounded on your data
  • Production deployment patterns
Key Deliverable: Working AI agent querying participant's data
Stage Run IconPart 5: The Roadmap Workshop
"From Vision to Value in 90 Days"
Duration: 45 minutes

5.1 Maturity Assessment (10 min)

Quick scorecard across five dimensions:

  1. Data Foundation (centralization, quality, governance)
  2. Analytics Capability (self-service, real-time, predictive)
  3. AI Adoption (experimentation, production, scale)
  4. Cultural Readiness (data literacy, executive sponsorship)
  5. Technical Architecture (modern stack, cloud-native, integrated)

5.2 The 30-60-90 Framework (25 min)

Days 1-30: Foundation
  • Provision Fabric capacity
  • Create OneLake structure
  • Migrate first dataset
  • Enable 10 power users
  • Quick win: First dashboard in production
Days 31-60: Expansion
  • Connect all major data sources
  • Build semantic layer
  • Launch self-service program
  • Deploy first ML model
  • Implement governance framework
Days 61-90: Acceleration
  • Scale to 100+ users
  • Production AI workloads
  • Automated pipelines
  • Executive dashboards
  • Measure and showcase ROI

5.3 Success Metrics (10 min)

  • Define KPIs that matter
  • Set up measurement framework
  • Create feedback loops
  • Plan iteration cycles
Key Deliverable: Customized 90-day implementation plan

Pattern 1: "The Medallion Architecture"

DatabaseERP/CRM
Event StreamIoT/Events
Cloud EndpointAPIs
OneLake
Bronze

Raw Data Landing

LakehouseLakehouse Storage
Data FactoryData Ingestion
0TB/day
Data Engineering
Silver

Cleaned & Validated

NotebookSpark Processing
PipelineQuality Checks
0% Quality
Semantic Model
Gold

Business-Ready Analytics

Power BIPower BI
CopilotAI Insights
0sec Query
DashboardDashboards
ReportReports
Data ScienceML Models
Performance
10x Faster

Query Performance

Quality
99.9% Quality

Data Accuracy

Cost
60% Cost

Reduction

  • Pre-built templates for common industries
  • Automated quality checks at each layer
  • Version control and rollback capabilities

DESIGN PATTERNS & ACCELERATORS

Pattern 2: "Domain Mesh on OneLake"

  • Central IT provides platform
  • Business units own their domains
  • Shared semantic models
  • Federated governance

Pattern 3: "AI-First Analytics"

  • Every pipeline AI-enhanced
  • Copilot as default interface
  • Automated anomaly detection
  • Predictive maintenance built-in

INTERACTIVE ELEMENTS

Challenge 1: "The Data Scavenger Hunt"

Teams compete to find and analyze hidden insights in sample dataset using different Fabric tools. Winner finds the "$1M optimization."

Challenge 2: "Build vs Buy Calculator"

Real-time ROI calculation comparing:

  • Current state (multiple vendors, custom integration)
  • Future state (Fabric unified platform)
  • Typically shows 40-60% TCO reduction

Challenge 3: "The Copilot Challenge"

Business users vs data engineers: Who can answer complex business questions faster? (Spoiler: Business users with Copilot usually win)

PRE-WORK REQUIREMENTS

Participants should bring:

  1. Laptop with browser
  2. Sample dataset (CSV, Excel, or connection details)
  3. Top 3 analytics pain points
  4. One "impossible" analytics request from the business

We'll provide:

  1. Fabric trial capacity
  2. Sample datasets
  3. Pre-configured environments
  4. Implementation templates

POST-SESSION SUPPORT

Week 1: Technical deep-dive session with IT team
Week 2: Business alignment workshop
Week 3: Proof-of-concept review
Week 4: Go/No-go decision checkpoint

Success Criteria:

  • 100% of participants can query data using natural language
  • 80% identify immediate use case for their department
  • At least 3 quick wins identified for 30-day plan
  • Executive sponsorship secured
"Every company claims to be data-driven. Most are actually opinion-driven with data decoration. Today, you've seen the difference. The question isn't whether to transform - it's whether you'll lead or follow.

Your competitors are 90 days away from having this capability. Where will you be?"

Next Step: Lock in your Fabric proof-of-concept. Real data. Real scenarios. Real results.
This isn't just training. It's transformation with keyboards out and skepticism welcomed. Ready to run it?
Dr. Estera Kot

Dr. Estera Kot

CTO @ Clouds on Mars | Lecturer | Researcher | Architect | R&D Lead | Innovating with Big Data, Analytics and AI

Dr. Estera Kot is the Chief Technology Officer at Clouds On Mars, where she drives the company's innovation in Data & AI strategy and execution. A former Principal Product Manager at Microsoft, she played a key role in building performance-critical components of Azure Synapse Analytics and Microsoft Fabric, focusing on Apache Spark and high-efficiency analytical engines.

Estera is a Polish-born engineer by passion, fluent in several programming languages and recognized for her hands-on technical depth. She earned her Ph.D. in Computer Science with distinction, specializing in machine and deep learning for medical imaging. Her research has led to numerous scientific publications and a U.S. patent in big data processing.

Her career spans global tech leaders like Intel, Sony, and Procter & Gamble. She is a respected educator and mentor, having designed full-time and postgraduate AI-in-Cloud programs at the Warsaw University of Technology. Her students now work at CERN, Google, Meta, and other top-tier institutions worldwide. Estera is a guest lecturer at UCLA—one of the top public research universities in the U.S.—and Łazarski University in Warsaw.

As a speaker, she's presented at top industry events including MLADS (Microsoft's internal AI and data science conference in Redmond), the inaugural FabCon in Las Vegas, and several AI and cloud conferences across Europe. She also produces educational content on YouTube, making complex AI topics accessible and practical.

Estera is committed to building scalable, ethical, and real-world-driven AI solutions, with a focus on impact over hype.

Ready to Transform Your Data Strategy?

Join the data revolution with Clouds on Mars. Let our experts guide your organization to become truly data-driven with cutting-edge Microsoft Fabric solutions.