Facts To Forecasts

How to Design Data Analytics & Decision Systems

53 modules

214 lessons

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Part 1

Appendices

Appendix A - Diagram Templates by StepSign in
Appendix B - Mapping Concepts to Real-World Data StacksSign in
Appendix C - Readiness Checklists (Step N -> Step N+1)Sign in
Appendix D - Glossary (Canonical Definitions)Sign in

Part 2

Course Setup and the Incremental Ladder

Course Setup and the Incremental LadderSign in
Why "Facts to Forecasts"Sign in
How to Use This CourseSign in
The Incremental Ladder (Step 0 -> Step 7)Sign in
The Course LensesSign in
Diagram Legend and Notation TypesSign in

Part 3

What Is a Data Analytics & Decision System?

What Is a Data Analytics & Decision System?Sign in
Reports vs Analytics vs Decision SystemsSign in
Descriptive to Prescriptive ThinkingSign in
The Decision LoopSign in

Part 4

Data as a Model of the World

Data as a Model of the WorldSign in
Entities, Events, RelationshipsSign in
Operational vs Analytical ViewsSign in
Domain AlignmentSign in

Part 5

Facts, Metrics, and Dimensions

Facts, Metrics, and DimensionsSign in
Facts and DimensionsSign in
Events as the Building BlockSign in
From Facts to MetricsSign in

Part 6

People and Roles in Data Systems

People and Roles in Data SystemsSign in
Producer RolesSign in
Modeling and Analysis RolesSign in
Decision-Makers and ResponsibilitiesSign in

Part 7

Diagramming Data Analytics Systems

Diagramming Data Analytics SystemsSign in
End-to-End Flow DiagramsSign in
Lineage and Dependency GraphsSign in
Decision Flow MapsSign in

Part 8

Step 0 Data Modeling for Analytics

Step 0 Data Modeling for AnalyticsSign in
Entities vs EventsSign in
Identifiers, Keys, RelationshipsSign in
Slowly Changing DimensionsSign in

Part 9

Step 0 Descriptive Statistics

Step 0 Descriptive StatisticsSign in
Core AggregationsSign in
Distributions and PercentilesSign in
Variability and TrendsSign in

Part 10

Step 0 Analytical Queries

Step 0 Analytical QueriesSign in
Group-By ThinkingSign in
Joins for MeaningSign in
Rolling Windows and ComparisonsSign in

Part 11

Step 0 Common Analytical Patterns

Step 0 Common Analytical PatternsSign in
Cohorts and FunnelsSign in
Retention and ChurnSign in
Conversion and AttributionSign in

Part 12

Step 0 First Analytics Environment

Step 0 First Analytics EnvironmentSign in
A Minimal Analytical DatabaseSign in
Core Tables and ViewsSign in
From Manual Queries to First DashboardsSign in

Part 13

ETL vs ELT (Conceptual)

ETL vs ELT (Conceptual)Sign in
ETL and ELT PrimitivesSign in
Modern ELT ContextSign in
Trade-OffsSign in

Part 14

Sources of Data

Sources of DataSign in
Operational Databases and APIsSign in
Event Streams and LogsSign in
External and Third-Party DataSign in

Part 15

Batch vs Streaming Pipelines (Conceptual)

Batch vs Streaming Pipelines (Conceptual)Sign in
Batch IngestionSign in
Streaming and Near-Real-TimeSign in
Selecting the ModeSign in

Part 16

Pipeline Orchestration

Pipeline OrchestrationSign in
DAGs of Tasks and JobsSign in
Scheduling, Dependencies, RetriesSign in
Failures and IdempotencySign in

Part 17

Data Cleaning and Transformation

Data Cleaning and TransformationSign in
Type Normalization and UnitsSign in
Deduplication and ReconciliationSign in
Missing and Noisy DataSign in

Part 18

Data Quality and Validation

Data Quality and ValidationSign in
Expectations and RulesSign in
Checks at Ingestion vs in the WarehouseSign in
Alerting and Health ReportingSign in

Part 19

Analytical Storage Architectures

Analytical Storage ArchitecturesSign in
WarehousesSign in
Lakes and Lakehouse ConceptsSign in
Selecting an Analytical Storage ArchitectureSign in

Part 20

Schemas for Analytics

Schemas for AnalyticsSign in
Dimensional ModelsSign in
Fact and Dimension Tables in PracticeSign in
Normalized vs Denormalized Trade-OffsSign in

Part 21

Tables, Views, and Semantic Layers

Tables, Views, and Semantic LayersSign in
Raw vs Curated LayersSign in
Views and Semantic LayersSign in
Logical vs Physical ModelsSign in

Part 22

Partitioning, Clustering, and Performance

Partitioning, Clustering, and PerformanceSign in
Partitioning StrategiesSign in
Indexing and Clustering ConceptsSign in
Cost and PerformanceSign in

Part 23

Governance, Access, and Security

Governance, Access, and SecuritySign in
Access Control BoundariesSign in
Masking and AnonymizationSign in
Privacy and Compliance PostureSign in

Part 24

Multi-Environment and Multi-Region Warehousing

Multi-Environment and Multi-Region WarehousingSign in
Dev, Stage, and Prod for DataSign in
Residency and Multi-Region ConstraintsSign in
Replication and DR ConceptsSign in

Part 25

BI Tools and Visualization

BI Tools and VisualizationSign in
What BI Tools ProvideSign in
Choosing Chart TypesSign in
Visual Storytelling PatternsSign in

Part 26

Dashboards, Reports, and Ad Hoc Analysis

Dashboards, Reports, and Ad Hoc AnalysisSign in
Dashboard TypesSign in
Static Reports vs Interactive ExplorationSign in
Drill-Down and Cross-FilteringSign in

Part 27

Semantic Metrics Layer

Semantic Metrics LayerSign in
Define Metrics OnceSign in
Preventing Metric FragmentationSign in
Serving Metrics to Tools and SystemsSign in

Part 28

Designing Dashboards for Decisions

Designing Dashboards for DecisionsSign in
Leading vs Lagging IndicatorsSign in
Guardrails and Trade-OffsSign in
Owners and DecisionsSign in

Part 29

Self-Service Data Culture

Self-Service Data CultureSign in
Analyst vs Self-Serve FlowsSign in
Templates, Curated Datasets, TrainingSign in
Empowerment with GovernanceSign in

Part 30

BI Platform Operations

BI Platform OperationsSign in
Content Sprawl and StalenessSign in
Performance Tuning for BI WorkloadsSign in
Monitoring Usage and UsefulnessSign in

Part 31

Why Experimentation?

Why Experimentation?Sign in
Correlation vs CausationSign in
Experiments as Intervention TestsSign in
When Not to ExperimentSign in

Part 32

Experiment Design Basics

Experiment Design BasicsSign in
Treatment and ControlSign in
Randomization and AssignmentSign in
Sample Size and Duration IntuitionSign in

Part 33

Experimentation System Architecture

Experimentation System ArchitectureSign in
Exposure Logging and Event CaptureSign in
Experiment Configuration SurfacesSign in
Bucketing, Flags, and Rollout ControlsSign in

Part 34

Metrics for Experiments

Metrics for ExperimentsSign in
Primary vs Secondary MetricsSign in
Guardrail Metrics for SafetySign in
Metric Alignment with DecisionsSign in

Part 35

Analyzing Experiments (Conceptual)

Analyzing Experiments (Conceptual)Sign in
Differences Between GroupsSign in
Confidence and UncertaintySign in
Overlaps and Multiple ExperimentsSign in

Part 36

Operationalizing Experimentation

Operationalizing ExperimentationSign in
Experiment Review ProcessesSign in
Libraries of LearningsSign in
Integrating into RhythmsSign in

Part 37

From Descriptions to Predictions

From Descriptions to PredictionsSign in
Prediction-Shaped QuestionsSign in
Supervised Learning at a High LevelSign in
Prediction as a Decision InputSign in

Part 38

Data for Predictive Models

Data for Predictive ModelsSign in
Feature Engineering ConceptsSign in
Splits and LeakageSign in
Drift ConceptsSign in

Part 39

Evaluating Predictive Models

Evaluating Predictive ModelsSign in
Accuracy, Error, CalibrationSign in
Precision vs Recall Trade-OffsSign in
Offline vs Online EvaluationSign in

Part 40

Forecasting Time-Series

Forecasting Time-SeriesSign in
Time-Series StructureSign in
Horizons and GranularitySign in
Uncertainty and IntervalsSign in

Part 41

Model Serving and Integration

Model Serving and IntegrationSign in
Batch vs Real-Time ScoringSign in
Feature Stores ConceptuallySign in
Wiring Predictions into FlowsSign in

Part 42

Monitoring Models in Production

Monitoring Models in ProductionSign in
Performance Over TimeSign in
Drift, Label Delay, Feedback GapsSign in
Retraining and Lifecycle ManagementSign in

Part 43

Decisions and Decision Frameworks

Decisions and Decision FrameworksSign in
Repeated vs One-Off DecisionsSign in
Thresholds, Playbooks, PoliciesSign in
Human vs Automated BoundariesSign in

Part 44

Decision Rules and Policy Engines

Decision Rules and Policy EnginesSign in
Rules Engines ConceptuallySign in
Combining Metrics and Model OutputsSign in
Versioning and Auditing RulesSign in

Part 45

Resource Allocation and Optimization (High-Level)

Resource Allocation and Optimization (High-Level)Sign in
Allocation ProblemsSign in
Optimization as Constraint SatisfactionSign in
Heuristics vs Exact MethodsSign in

Part 46

Human-in-the-Loop Decision Systems

Human-in-the-Loop Decision SystemsSign in
Recommendations vs Auto-ApprovalSign in
Escalations, Overrides, and AnnotationsSign in
UX for Decision MakersSign in

Part 47

Observability and Feedback Loops for Decisions

Observability and Feedback Loops for DecisionsSign in
Logging Decisions and OutcomesSign in
Post-Decision Analysis and RecalibrationSign in
Continuous Improvement LoopsSign in

Part 48

End-to-End Analytics Platform Architecture

End-to-End Analytics Platform ArchitectureSign in
End-to-End Flow in a Platform ArchitectureSign in
Logical vs Physical ComponentsSign in
Control Planes and Platform ControlSign in

Part 49

Multi-Tenant and Multi-Domain Data Platforms

Multi-Tenant and Multi-Domain Data PlatformsSign in
Multi-Team Platforms and Shared Failure DomainsSign in
Data Contracts and Domain OwnershipSign in
Autonomy vs Standardization in Multi-Domain PlatformsSign in

Part 50

Governance, Ethics, and Compliance

Governance, Ethics, and ComplianceSign in
Access, Privacy, Usage Boundaries as Platform PropertiesSign in
Bias and Fairness Concerns in Data and Decision SystemsSign in
Documentation, Audits, and Accountability for Reviewable BehaviorSign in

Part 51

Operating Analytics and Decision Systems

Operating Analytics and Decision SystemsSign in
SLOs for Pipelines, Warehouses, and BISign in
Incident Handling and Data Outage PlaybooksSign in
Capacity Planning and Cost ManagementSign in

Part 52

Organizational Adoption and Data Culture

Organizational Adoption and Data CultureSign in
Maturity Transitions - From Reports to Decision SystemsSign in
Training, Documentation, and Evangelism as System InterfacesSign in
Incentives and Alignment - Rewarding Correct DecisionsSign in

Part 53

Reference Architectures and Maturity Models

Reference Architectures and Maturity ModelsSign in
Early Stage Reference Architecture - One Database, One Truth BoundarySign in
Growth Stage Reference Architecture - From Single Slice to Shared PipelinesSign in
Mature Stage Reference Architecture - Unified Semantics, Decisions, and GovernanceSign in

Course overview