The future of data(Base) education: Is the "cow book" dead?

Zachary G. Ives; Rachel Pottinger; Arun Kumar; Johannes Gehrke; Jana Giceva

doi:10.14778/3476311.3476394

The future of data(Base) education: Is the "cow book" dead?

Zachary G. Ives
, Rachel Pottinger
, Arun Kumar
, Johannes Gehrke
, Jana Giceva

Informatics 3 - Associate Professorship of Database Systems

University of Pennsylvania
University of British Columbia
University of California, San Diego
Microsoft Corporation

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

This panel encourages a debate over the future of database education and its relationship to Data Science: Are Computer Science (CS) and Data Science (DS) different disciplines about to split, and how does that effect how we teach our field? Is there a "data" course that belongs in CS that all of our students should take? Who is the traditional database course, e.g. based on the "cow book", relevant to? What traditional topics should we not be teaching in our core data course(s) and which ones should be added? What do we teach the student who has one elective for data science? How does our community position itself for leadership in CS given the popularity of DS?.

Original language	English
Pages (from-to)	3239-3240
Number of pages	2
Journal	Proceedings of the VLDB Endowment
Volume	14
Issue number	12
DOIs	https://doi.org/10.14778/3476311.3476394
State	Published - 2021
Event	47th International Conference on Very Large Data Bases, VLDB 2021 - Virtual, Online Duration: 16 Aug 2021 → 20 Aug 2021

Access to Document

10.14778/3476311.3476394

Cite this

@article{206562f426d24f22abe01fb3d416419b,

title = "The future of data(Base) education: Is the {"}cow book{"} dead?",

abstract = "This panel encourages a debate over the future of database education and its relationship to Data Science: Are Computer Science (CS) and Data Science (DS) different disciplines about to split, and how does that effect how we teach our field? Is there a {"}data{"} course that belongs in CS that all of our students should take? Who is the traditional database course, e.g. based on the {"}cow book{"}, relevant to? What traditional topics should we not be teaching in our core data course(s) and which ones should be added? What do we teach the student who has one elective for data science? How does our community position itself for leadership in CS given the popularity of DS?.",

author = "Ives, \{Zachary G.\} and Rachel Pottinger and Arun Kumar and Johannes Gehrke and Jana Giceva",

note = "Publisher Copyright: {\textcopyright} The authors.; 47th International Conference on Very Large Data Bases, VLDB 2021 ; Conference date: 16-08-2021 Through 20-08-2021",

year = "2021",

doi = "10.14778/3476311.3476394",

language = "English",

volume = "14",

pages = "3239--3240",

journal = "Proceedings of the VLDB Endowment",

issn = "2150-8097",

publisher = "VLDB Endowment",

number = "12",

}

TY - JOUR

T1 - The future of data(Base) education

T2 - 47th International Conference on Very Large Data Bases, VLDB 2021

AU - Ives, Zachary G.

AU - Pottinger, Rachel

AU - Kumar, Arun

AU - Gehrke, Johannes

AU - Giceva, Jana

N1 - Publisher Copyright: © The authors.

PY - 2021

Y1 - 2021

N2 - This panel encourages a debate over the future of database education and its relationship to Data Science: Are Computer Science (CS) and Data Science (DS) different disciplines about to split, and how does that effect how we teach our field? Is there a "data" course that belongs in CS that all of our students should take? Who is the traditional database course, e.g. based on the "cow book", relevant to? What traditional topics should we not be teaching in our core data course(s) and which ones should be added? What do we teach the student who has one elective for data science? How does our community position itself for leadership in CS given the popularity of DS?.

AB - This panel encourages a debate over the future of database education and its relationship to Data Science: Are Computer Science (CS) and Data Science (DS) different disciplines about to split, and how does that effect how we teach our field? Is there a "data" course that belongs in CS that all of our students should take? Who is the traditional database course, e.g. based on the "cow book", relevant to? What traditional topics should we not be teaching in our core data course(s) and which ones should be added? What do we teach the student who has one elective for data science? How does our community position itself for leadership in CS given the popularity of DS?.

UR - https://www.scopus.com/pages/publications/85119998996

U2 - 10.14778/3476311.3476394

DO - 10.14778/3476311.3476394

M3 - Conference article

AN - SCOPUS:85119998996

SN - 2150-8097

VL - 14

SP - 3239

EP - 3240

JO - Proceedings of the VLDB Endowment

JF - Proceedings of the VLDB Endowment

IS - 12

Y2 - 16 August 2021 through 20 August 2021

ER -

The future of data(Base) education: Is the "cow book" dead?

Abstract

Access to Document

Other files and links

Fingerprint

Cite this