Evolution of Data Management

Authors:
Jim Gray
Affiliations:
-
Venue:
Computer
Year:
1996

Citing 6
Cited 5

Understanding the new SQL: a complete guide

Understanding the new SQL: a complete guide
The programmer as navigator

Communications of the ACM
A relational model of data for large shared data banks

Communications of the ACM
Database research: achievements and opportunities into the 1st century

ACM SIGMOD Record
An Introduction to Database Systems

An Introduction to Database Systems
Engine of the Mind: A History of the Computer

Engine of the Mind: A History of the Computer

Database research faces the information explosion

Communications of the ACM
Enabling technologies for improved data management: Hardware

Scientific Programming
Sysadmins and the need for verification information

Proceedings of the 2nd ACM Symposium on Computer Human Interaction for Management of Information Technology
Database theory for users unexpert: a strategy for learning computer science and information technology

ADNTIIC'10 Proceedings of the First international conference on Advances in new technologies, interactive interfaces, and communicability
Digital photography and geographical information in the web 2.0: a quality evaluation of the contents

HCITOCH'11 Proceedings of the Second international conference on Human-Computer Interaction, Tourism and Cultural Heritage

Quantified Score

Hi-index	4.12

Visualization

Abstract

Society has made great strides in capturing, storing, managing, analyzing, and visualizing data. These tasks are generically called data management, and this article sketches its evolution through six distinct phases. The author describes the data management challenges that remain, both technical and societal. The technical challenges are more tractable than the societal challenges. There is little question that most data will be online--because it is both inexpensive and convenient to store it in computers. Organizing these huge data archives so that people can easily find the information they need is the real challenge. Finding patterns, trends, anomalies, and relevant information from a large database is one of the most exciting new areas of data management. The hope is that computers will be able to condense and summarize information for us so that we will be spared the drudgery of searching through irrelevant data for the nuggets we seek. The solution to this will require contributions from many disciplines.