ISYS111 Lecture Notes - Lecture 5: Master Data Management, Data Governance, Data Degradation
25 May 2018
School
Department
Course
Professor
ISYS111 – Fundamentals of Business Information Systems
Week 5 Workshop
Objectives:
1. Discuss ways that common challenges in managing data can be addressed using data
governance
2. Explain how to interpret relationships depicted in an entity-relationship diagram
3. Discuss the advantages and disadvantages of rational databases
4. Explain the elements necessary to successfully implement and maintain data
warehouses
5. Describe the benefits and challenges of implementing knowledge management
systems in organisations
How do we manage data?
• We expect high quality data. Some characteristics of high quality data are:
- Accurate
- Complete
- Timely
- Consistent
- Accessible
- Relevant
- Concise
Why is it difficult to manage data?
• Amount of data is growing exponentially
• Data are scattered throughout organisations and collected by many individuals using
various methods and devices
• Data come from many sources
• Data degrade over time (can become outdated data)
• Data are subject to data rot (outdated, destroyed storage media)
• Data security, quality and integrity are critical, yet easily jeopardised
• Inconsistent, conflicting data due to non-integrated information systems
• Government Regulations
• Companies are drowning in unstructured data
Data Governance:
• An approach to managing information across an entire organisation
Master Data:
• A set of core data that covers a complete enterprise information system
Master data management:
• A strategy plan for data governance
• A proess that spas all of a orgaisatio’s usiess proesses ad appliatios
• Allows companies to store, maintain, exchange and synchronise a consistent,
accurate and timely data
Terms:
• A strategy – a plan
• A process – a series of actions or steps taken in order to achieve a particular end
find more resources at oneclass.com
find more resources at oneclass.com
Document Summary
How do we manage data: we expect high quality data. Inconsistent, conflicting data due to non-integrated information systems. Data governance: an approach to managing information across an entire organisation. Master data: a set of core data that covers a complete enterprise information system. Master data management: a strategy plan for data governance, a pro(cid:272)ess that spa(cid:374)s all of a(cid:374) orga(cid:374)isatio(cid:374)"s (cid:271)usi(cid:374)ess pro(cid:272)esses a(cid:374)d appli(cid:272)atio(cid:374)s, allows companies to store, maintain, exchange and synchronise a consistent, accurate and timely data. Database management systems (dbms): dbms is a set of programs that provide users with tools to add, delete, access, modify and analyse data stored in one place, minimise: A database must be organised so that users retrieve, analyse and understand the data they need. A key to designing an effective database is the data model. A data model is a diagram that represents entities in the database and their relationships. An entity: person, product, service, event, etc.
