Data Management: Databases
and Organizations
6th edition – Richard T. Watson
Summary by Inge van Manen – – October 2017
Section 1: The Managerial Perspective
World’s data doubles every 1-2 years
Managerial perspective: why enterprises design and maintain data management systems
(DMS)
o Ch1: components of organizational memory and its common problems
o Ch2: relationship between information and organizational goals
Newell-Simon model: humans receive input, process it, and produce output (Figure 1)
o Limited memory, restricted processing ability → use of external tools
Figure 1 The internal memory of a human with usage of external tools (Source: Data Management: Databases and
Organizations (Richard T. Watson))
, Chapter 1: Managing data
Organizations have data management systems (DMS)
o Can be simple or complex, personal or public
Data management requires designing, using, and managing memory systems
Individual data management
o Humans have limited memory capacity → most things in external memory
Smartphone
To-do list
Calendar
o External memories have
Storage medium
Structure for storing data
Interface designed for rapid data entry and retrieval
Trade-off decision: what can you show?
Organizational data management
o Storage medium: mostly electronic (Ch …)
o Structure: commonly tables
o Storage devices organized for rapid data entry and retrieval → comer at a price, so
trade-off between speed and cost
Different types of information systems:
Abbr. Type of system Description
TPS Transaction Processing Handles common business tasks such as accounting, inventory,
System purchasing and sales
MIS Management Converts TPS data into info for planning, controlling, and
Information System managing an organization
DSS Decision Support Support managerial decision making by providing models for
System processing and analyzing data
BI Business Intelligence Gather, store and analyze data to improve decision making
OLAP Online Analytical Provide a multidimensional view of data
Processing
Data Mining Use of statistical analysis and artificial intelligence techniques
to identify hidden relationships in data
Machine Learning Using software to make decisions or recommendations
traditionally made by humans
and Organizations
6th edition – Richard T. Watson
Summary by Inge van Manen – – October 2017
Section 1: The Managerial Perspective
World’s data doubles every 1-2 years
Managerial perspective: why enterprises design and maintain data management systems
(DMS)
o Ch1: components of organizational memory and its common problems
o Ch2: relationship between information and organizational goals
Newell-Simon model: humans receive input, process it, and produce output (Figure 1)
o Limited memory, restricted processing ability → use of external tools
Figure 1 The internal memory of a human with usage of external tools (Source: Data Management: Databases and
Organizations (Richard T. Watson))
, Chapter 1: Managing data
Organizations have data management systems (DMS)
o Can be simple or complex, personal or public
Data management requires designing, using, and managing memory systems
Individual data management
o Humans have limited memory capacity → most things in external memory
Smartphone
To-do list
Calendar
o External memories have
Storage medium
Structure for storing data
Interface designed for rapid data entry and retrieval
Trade-off decision: what can you show?
Organizational data management
o Storage medium: mostly electronic (Ch …)
o Structure: commonly tables
o Storage devices organized for rapid data entry and retrieval → comer at a price, so
trade-off between speed and cost
Different types of information systems:
Abbr. Type of system Description
TPS Transaction Processing Handles common business tasks such as accounting, inventory,
System purchasing and sales
MIS Management Converts TPS data into info for planning, controlling, and
Information System managing an organization
DSS Decision Support Support managerial decision making by providing models for
System processing and analyzing data
BI Business Intelligence Gather, store and analyze data to improve decision making
OLAP Online Analytical Provide a multidimensional view of data
Processing
Data Mining Use of statistical analysis and artificial intelligence techniques
to identify hidden relationships in data
Machine Learning Using software to make decisions or recommendations
traditionally made by humans
