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◎Data Product Systems

Data Product Systems

Pipelines and structures turn raw data into packaged, sellable, and repeatable products with defined schemas and use cases.

Routing Notes

  • Parent Systems Across Domains
  • Signal Working Systems

What It Is

Pipelines and structures turn raw data into packaged, sellable, and repeatable products with defined schemas and use cases.

What This Domain Trains You To Notice

This domain is valuable because data and AI systems expose the full path from collection to action. They make it obvious that storage, transformation, meaning, trust, and incentives all shape the value of the output.

Why It Transfers

The transfer advantage is strong here. Learning to ask where data came from, how it changed, and who is rewarded by its use builds a habit that improves product, operational, and strategic thinking in other domains. This domain gets more useful when it is compared with adjacent systems instead of being treated as a silo. That is where reusable judgment starts to form.

Related Domains

  • Data warehousing systems
  • Data lake / lakehouse systems
  • ETL / ELT systems
◆Data Brokering

Data Brokering

Data Brokering is the collection, aggregation, and sale of data from multiple sources.

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Preview for Data Product Development
◆Data Product Development

Data Product Development

Data Product Development is the process of building products that leverage data to deliver value to users.

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Preview for Dataset Development
◆Dataset Development

Dataset Development

Dataset Development is the creation, curation, and refinement of datasets for analysis or product use.

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▶Demographic Prediction Model and Machine Learning Pipeline

Demographic Prediction Model and Machine Learning Pipeline

Built predictive audience demographic datasets using graph databases and AI/ML. Trained models to predict demographic attributes of mobile device audiences...

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Preview for Enhanced IP Geolocation Model for Security and Verification
▶Enhanced IP Geolocation Model for Security and Verification

Enhanced IP Geolocation Model for Security and Verification

Designed a novel IP geolocation confidence model combining location observation data with network topography analysis to improve the accuracy of geographic...

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Preview for Location Observation Fraud Outlier Identification
▶Location Observation Fraud Outlier Identification

Location Observation Fraud Outlier Identification

Used Tableau and sampled data to identify impossible or improbable movement patterns in location observation datasets, then designed a system to tag and filter...

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○Machine Learning and Data Science

Machine Learning and Data Science

Projects involving predictive modeling, ML pipelines, feature engineering, and data-driven decision systems.

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▶Machine Learning Pipeline for Automated Ad Pricing

Machine Learning Pipeline for Automated Ad Pricing

Before TensorFlow existed, built a continuously-learning SQL-based machine learning system that optimized real-time bid pricing for programmatic advertising —...

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Preview for Scoring Algorithm for Customer Revisit Attribution
▶Scoring Algorithm for Customer Revisit Attribution

Scoring Algorithm for Customer Revisit Attribution

Designed, implemented, and tested 150 iterations of a scoring algorithm to determine the likelihood of a customer revisiting a physical store, based on mobile...

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Preview for Voronoi Regions for International Geofencing
▶Voronoi Regions for International Geofencing

Voronoi Regions for International Geofencing

Created an algorithm to build an optimal international geofencing system for hundreds of millions of postal address regions, incorporating feedback from 32...

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Michael Orlando

Systems, ventures, writing, and public proof arranged so the right people can find the right next step.

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