Download Chapter 14 * Database Management

UNIT 3 – MODULE 4:
Database Management
INTRODUCTION
• Managing data is a critically
important function.
• It enables strategic searching
& manipulation of data that
would manually take large
amounts of time.
• GIS has two data types that
requires management:
spatial & attribute data.
Credit: C. Jones, GIS & Computer Cartography, 1997
ADVANTAGES
• There are many benefits to
having a computerized
database:
– Can be utilized for other
purposes (e.g. marketing).
– Reduction in redundancies
(unnecessary data duplication).
– Easy to maintain (e.g.
automated updating).
– Can quickly sift through
information based on multiple
parameters.
Credit: Alaska Department of Natural Resources
DATABASE CREATION
• There are four major steps for database creation:
1. Data Investigation – consider the type of data you
want for a database (e.g. what are you trying to
prove/show with the data?). No GIS software
required.
2. Data Modeling – forming a conceptual model by
assessing entities & attribute data characteristics
(i.e. how will data be linked?). No GIS software
required.
3. Database Design – creating a user-friendly
database design. Dependent on GIS software to be
used and data model chosen.
4. Database Implementation – infusing the database
with attribute data by a specific procedure.
SPATIAL & ATTRIBUTE LINK
• Relationship between databases and GIS will
vary. For example: a simple raster GIS will not
require a database.
• One relationship option is having attribute file
data separated from a raster image.
• Most vector GIS utilize a hybrid approach,
where spatial data is stored within the GIS
data structure, and attribute data is stored in a
database management system (DBMS).
• All spatial & attribute data could also be found
within the same DBMS.
• Bottom line: there are options.
CONCLUSION
• It is important to understand
how information is stored
within a GIS.
• This enhances your ability to
manipulate data, which
assists in what you’re trying
to show or resolve.
• It also allows you to better
understand how data-related
errors might have occurred.
Credit: ESRI