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INFS1602

Satisfactory Essays

Strategic Business Objectives
Operational Excellence
New products, services and business models
Customer and Supplier Intimacy
Improved Decision Making
Competitive Advantage
Survival
Value Chain Model
Primary Activities
Inbound Logistics (warehousing systems)
Operations (machining systems)
Sales and Marketing (electronic ordering)
Service (equipment maintenance)
Outbound Logistics (automated shipment scheduling)
Support Activities
Admin/Management (messaging/scheduling)
Infrastructure (hardware/software used by primaries)
HR (workforce planning)
Technology development
Procurement (electronic ordering from suppliers)

IS can be used for
Synergising companies together for lower operating costs (tying together …show more content…

Master data - data most important in the operation of the business
Data can be stored in data warehouses. However, they need data cleansing to standardise the data.
Data mart - categorisation of data from data warehouses customised for a specific group.
Stages in decision making:
Intelligence->design->choice->implementation
2 types of business intelligence system:
Data mining: find for more hidden relationship through without any ideas about the existence of those relationship and data that they do not collect it before.
OLNP: multidimensional analysing, summarising data to get information from existing data they can collect
Trend of BI:
Social media: new platform for intelligence, help business identify customer’s view about performance and customer relationship of business in the market.
Cloud service: minimize cost of storage of data, minimize time of processing and summarizing data.
Visualization(important): (real time updating) easier for business to do and understand the data, easier to identify potential and most influential customers.

Business Intelligence (BI) components
Information and knowledge discovery (Collects current data)
Ad hoc queries and reports
Online Analytical Processing (OLAP) (multidimensional)
(hidden relationships, complements OLAP)
Association discovery
Clustering (attribute based) and classification (pre-knowledge segmentation)
Unstructured data analysis
Web content mining (web crawler

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