Chapter 2.

Bridging the Analysis Gap

商業智慧

資訊管理系助理教授電子商務研究中心主任創新育成中心主任

閔庭祥

概述問題的產生企業所需的資訊往往與所蒐集的資料有所落差（ GAP）解決方案組織何種資訊將有助於企業分析瞭解電腦系統如何將原始資料轉換為資訊

概述Multidimensional analysis(多面向分析 )

Difining the differences between operational systems and BI systems

Operation systems： Collect company’s raw data

BI systems： transform raw data into useful information

Multidimensional AnalysisA useful approach for viewing information that allow you to perform flexible and powerful business analysisAlmost always reveals new and interesting information compared to isolated, single-dimension data listsDimensions:distinct categorizationsEX:P30

Fruit by time,market,product……

Operation SystemsOperation Database： support the day-to-day operations of the company(EX:customer order)The data is not necessarily readily available for business analysisThese databases are structured for the purposes of running the day-to-day business by processing transactions,not for effective business analysisBasic functionality:gather,update store,retrieve and archive dataDatabase structure called a relational database management system(RDBMS)

OLTP Systems

Example:ATM

Characteristics:It processes a transaction

It performs all the elements of the transaction in real time

It processes many transactions on a continuous basis

OLTP Systems

OLTP is designed for managing the raw data of businessThe data can be served up quickly ,it is not very useful for an analysis of the overall businessOLTP systems are lousy for analysisThe data resides within multiple,disparately organized,and often old technology systems

Operational ReportingThese applications typically include meaningful reporting capabilities,which have value for performing business analysis and rightly part of an overall BI strategyTwo basic limitations

They report on only their own internally gathered information without the ability to combine data from other systemsOperational reporting does not effectively support multidimensional analysis at the speed of thought

BI systems

A place where data form many oprational systems(and outside data sources) is pulled together for the purpose of analysis

BI system that enable delivery of fast and efficient multidimensional analysis

A specific BI paradigm： online analytical processing(OLAP)

Why OLAP

OLAP provides conceptual and intuitive data model(multidimensional analysis) that users who are not necessarily trained as analysts can understand and quickly relate to

OLAP systems organize the data directly as multidimensinal structures, including easy-to use tools for users to get information

Why OLAP

OLAP is also fast for the userIt is the quick response for getting information

Fast retrieval times let managers and analysts ask and answer more questions in a concentrated period of time

Why OLAP

OLAP systems have robust calculation engines for handing the specialized calculation requirements that a multidimensional structure imposes

OLAP calculation engines structure the data in a way that allows the business analyst to write simple,straightforward formulas that perform across multiple dimensions with only a few lines of code

OLAP systems structuresDimensions for slice and dice

Dimension is a categorically consistent view of data

Data about the members can be compared

Data from the members can be aggregated to summary members

Multidimensional data in an OLAP system is typically visualized as a cube storage structure with lots of mini-cubes or cells P39

OLAP systems structures

Hierarchies for Drill DownAllow you to organize the data into hierarchies that aggregate the detail to higher and higher levels

Measures

Hierarchies for drill downDimensionHierarchy

A ragged hierarchydrill down levels are not parallelAn alternate hierarchyThe second organization of aggregation levels that Use the same source of bottom-level data

MemberThe name or label for any member at any level in a hierarchyLeaf members

Family Relationships

time

2001

Q1

Q2

Q3

Q4

1

2

3

4

Family Relationships

ChildA member directly subordinate

to another member( 1Q1)

ParentA member directly above another member(Q11)

Sibling:the same lever’s member(1--2)

DescendantAny member at any lower level in relation to another(Q and mouth2001)

Ancetor(2001 and Q11)

time

2001

Q1

Q2

Q3

Q4

1

2

3

4

Measure

The data in most BI applications and all OLAPsystems is called a measureA measure is any quantitative expressionA measure is what is being analyzed across multiple dimensionsFour important parameters

Always a quantity or an expression that yields a quantityTake any quantitative format EX:Value RatioCan be derived from any original data source or calculationMust have at least one measure to do any type of OLAP

Measure

Mesaures in business intelligence are gererally known by different name

Metric

Key performance indicator(KPI)

Benchmark

Ratio

OLAP Storage Modes

Most OLAP systems utilize one or may of the following three storage paradidms to support multidimensional analysisDesktop files(DOLAP)

Data sotred on individyal desktop machines

Relational databases servers(ROLAP)Storing data in a relational database

Multidimensional databases servers (MOLAP)Data is placed into special structures that stored on a central server(s)

HOLAP

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