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D ATA S CIENCE E COSYSTEM M. T AMER ZSU N ANCY R EID R AYMOND N G U. - - PowerPoint PPT Presentation

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D ATA S CIENCE E COSYSTEM M. T AMER ZSU N ANCY R EID R AYMOND N G U. W ATERLOO U. T ORONTO UBC D ATA S CIENCE /B IG D ATA IN THE N EWS Canadian Data Science Workshop 2 D ATA S CIENCE E VERYWHERE !... Canadian Data Science Workshop 3 D

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DATA SCIENCE ECOSYSTEM

  • M. TAMER ÖZSU

NANCY REID RAYMOND NG

  • U. WATERLOO
  • U. TORONTO

UBC

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Canadian Data Science Workshop

DATA SCIENCE/BIG DATA IN THE NEWS…

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Canadian Data Science Workshop

DATA SCIENCE EVERYWHERE!...

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Canadian Data Science Workshop

DATA SCIENCE EVERYWHERE!...

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Canadian Data Science Workshop

DATA SCIENCE EVERYWHERE!...

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Canadian Data Science Workshop

DATA SCIENCE VOCABULARY

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Canadian Data Science Workshop

WHAT IS DATA SCIENCE?

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Canadian Data Science Workshop

WHAT IS DATA SCIENCE?

  • “Data science, also known as data-driven science, is an

interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining.”

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Canadian Data Science Workshop

WHAT IS DATA SCIENCE?

  • “Data science, also known as data-driven science, is an

interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining.”

  • “Data science intends to analyze and understand actual

phenomena with ‘data’. In other words, the aim of data science is to reveal the features or the hidden structure of complicated natural, human, and social phenomena with data from a different point of view from the established or traditional theory and method.”

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Canadian Data Science Workshop

WHAT IS DATA SCIENCE?

  • Fourth paradigm
  • “… change of all sciences moving from observational, to

theoretical, to computational and now to the 4th Paradigm – Data-Intensive Scientific Discovery”

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Canadian Data Science Workshop

WHAT IS IMPORTANT?

Need to solve a real problem using data… No applications, no data science.

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Canadian Data Science Workshop

DATA SCIENCE AS A UNIFIER

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Data Science

Humanities Machine/ Statistical Learning Application Domain Expertise Visualization

Mathematical Optimization

Social Science Law Data Management

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Canadian Data Science Workshop

DATA SCIENCE AND BIG DATA

  • They are not the “same thing”
  • Big data = crude oil
  • Big data is about extracting “crude oil”, transporting it in “mega tankers”,

siphoning it through “pipelines”, and storing it in “massive silos”

  • Data science is about refining the “crude oil”

Carlos Samohano Founder, Data Science London

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Canadian Data Science Workshop

DATA SCIENCE AND ARTIFICIAL INTELLIGENCE

Data Science Artificial Intelligence

ML/DM/ Analytics

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Canadian Data Science Workshop

DATA SCIENCE AND ARTIFICIAL INTELLIGENCE

Data Science Artificial Intelligence

ML/DM/ Analytics

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“Data science produces insights. Machine learning produces predictions”

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Canadian Data Science Workshop

DATA SCIENCE APPLICATION EXAMPLES

  • Fraud detection
  • Investigate fraud patterns in past data
  • Early detection is important
  • Before damage propagates
  • Harder than late detection
  • Precision is important
  • False positive and false negative are both

bad

  • Real-time analytics

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Canadian Data Science Workshop

DATA SCIENCE APPLICATION EXAMPLES

  • Recommender systems
  • The ability to offer unique

personalized service

  • Increase sales, click-through rates,

conversions, …

  • Netflix recommender system valued at

$1B per year

  • Amazon recommender system drives a

20-35% lift in sales annually

  • Collaborative filtering at scale

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Canadian Data Science Workshop

DATA SCIENCE APPLICATION EXAMPLES

  • Predicting why patients are being

readmitted

  • Reduce costs
  • Improve population health
  • Find the “why” behind specific

populations being readmitted

  • Data lakes of multiple data sources
  • Investigate ties between readmission and

socioeconomic data points, patient history, genetics, …

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Canadian Data Science Workshop

DATA SCIENCE APPLICATION EXAMPLES

  • “Smart cities”
  • Not well-defined

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Canadian Data Science Workshop

DATA SCIENCE APPLICATION EXAMPLES

  • “Smart cities”
  • Not well-defined

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Canadian Data Science Workshop

DATA SCIENCE APPLICATION EXAMPLES

  • “Smart cities”
  • Not well-defined
  • Generally refers to using data and

ICT to

  • Better plan communities
  • Better manage assets
  • Reduce costs
  • Deploy open data to better engage

with community

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Canadian Data Science Workshop

DATA SCIENCE APPLICATION EXAMPLES

  • Moneyball
  • How to build a baseball team on a very

low budget by relying on data

  • Sabermetrics: the statistical analysis of

baseball data to objectively evaluate performance

  • 2002 record of 103-59 was joint best in

MLB

  • Team salary budget: $40 million
  • Other team: Yankees
  • Team salary budget: $120 million

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Canadian Data Science Workshop

HOLISTIC APPROACH TO DATA SCIENCE

Dissemination & Visualization Ethics, Policy & Social Impact

Core

Data Acquisition Data Preservation

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Modeling & Analysis Management of Big Data Making Data Trustable & Usable Data Security & Privacy

Application Application Application Application

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Canadian Data Science Workshop

CORE RESEARCH ISSUES & INTERACTIONS

Making Data Trustable & Usable Modelling & Analysis Data Visualization & Dissemination Big Data Management

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Canadian Data Science Workshop

CORE RESEARCH ISSUES & INTERACTIONS

Making Data Trustable & Usable Modelling & Analysis Data Visualization & Dissemination Big Data Management

  • Data cleaning
  • Sampling
  • Data provenance

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Canadian Data Science Workshop

CORE RESEARCH ISSUES & INTERACTIONS

Making Data Trustable & Usable Modelling & Analysis Data Visualization & Dissemination Big Data Management

  • Data cleaning
  • Sampling
  • Data provenance
  • Data lakes
  • Batch & online access
  • Platforms

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Canadian Data Science Workshop

CORE RESEARCH ISSUES & INTERACTIONS

Making Data Trustable & Usable Modelling & Analysis Data Visualization & Dissemination Big Data Management

  • Data cleaning
  • Sampling
  • Data provenance
  • Data lakes
  • Batch & online access
  • Platforms
  • Models & methods for data

lakes

  • Unsupervised

classification & AI

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Canadian Data Science Workshop

CORE RESEARCH ISSUES & INTERACTIONS

Making Data Trustable & Usable Modelling & Analysis Data Visualization & Dissemination Big Data Management

  • Data cleaning
  • Sampling
  • Data provenance
  • Data lakes
  • Batch & online access
  • Platforms
  • Models & methods for data

lakes

  • Unsupervised

classification & AI

  • Visualization for wider

audience

  • Visualization for data

exploration

  • Open data technologies

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Canadian Data Science Workshop

CORE RESEARCH ISSUES & INTERACTIONS

Making Data Trustable & Usable Modelling & Analysis Data Visualization & Dissemination Big Data Management

  • Data cleaning
  • Sampling
  • Data provenance
  • Data lakes
  • Batch & online access
  • Platforms
  • Models & methods for data

lakes

  • Unsupervised

classification & AI

  • Visualization for wider

audience

  • Visualization for data

exploration

  • Open data technologies
  • DM support for

provenance

  • Data preparation for big

data management

  • Cleaning for data

analysis

  • DM for ML
  • ML for DM
  • Visual analytics

…

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