Week 5 - lecture

This week coverage:
.Technology environment in developing BI apps.
.Role of data warehouse.
.Evolution of OLAP technology.

Quick summary of what I got in this week lecture:
.Technology needed by BI apps:

• intuitive access

• speed

• data from many sources

• flexible, attractive reports

.Simple BI architecture does not work

• revised with new architecture that got DATA WAREHOUSE on it

.BI and data warehouse

• BI may say "I don't need data warehouse" and vice versa

• BUT, main goal of BI: provide an easy, powerful, fast system

.Data warehouse

• may have redundancy

• well integrated

• time variant

• non-noisy data

• subject oriented

.Differences between OLAP and DW(data warehouse)

• DW is better at: Handling sparse data (?), Data volatility, Large numbers of dimensions, Large volumes of data, Development time(application evolution), Learning curve, Standards, interoperability, Data loading time (?)
  

• OLAP is better at: Calculation intensity, complexity, Handling complex drill hierarchies , Query response time, Consistency, reliability, Network impact, General ease of use for end-users, Development time (function evolution), Cost of simple deployment?
  

.DW vs OLAP

• OLAP is FAST!!

• DW deals with gathering data from multiple sources

• The rest is OLAP

.12 Codd's rules

• **Refer to lecture note**