MGSC 300 Ch 3 - Data Management (1)

MGSC 300 Ch 3 - Data Management
- collections of data sets or records stored in a systemic way
- stores data generated by business apps, sensors, operations and transaction-processing
systems (TPS)
- the data in databases are extremely VOLATILE
- medium & large enterprises typically have many databases of various types
***volatile data changes frequently - ANS-databases

database -> file -> record -> field -> byte -> bit - ANS-data hierarchy

bits per second - ANS-Bandwith is measured in

bytes - ANS-storage is measured in

- integrate with data collection systems such as TPS and business applications
- organized way to store, access and manage data
- stores data in table consisting of columns and rows, similar to a spreadsheet
- standard database model adopted by most enterprises - ANS-Database Management System
(DBMS)

provides access to data using a declarative language
SELECT column__name(s)
FROM table__name
WHERE condition - ANS-SQL (Structured Query Language) - DBMS

simplifies data access by requiring that users only specify WHAT data they want to access w/o
defining HOW they will be achieved - ANS-declarative language

- better control of data quality
- better IT security - ANS-centralized database architecture

- allow both local & remote access
- use client/server architecture to process requests - ANS-distributed database architecture

garbage in, garbage out
- lacks integrity/validation and reduces user trust
- incomplete, out of context, outdated, inaccurate, inaccessible or overwhelming - ANS-dirty
data

• Lost business.
• Time spent preventing errors.