mipro 2005 presentation arian
TRANSCRIPT
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AgendaAgenda
Where are we today?Where are we today?
7 mortal sins7 mortal sinsQuo Vadis BI?Quo Vadis BI?
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Where are we today?
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Data
BI = going from data to decisionBI = going from data to decision
Data isnData isnt information!t information!
Data + structures =Data + structures =
informationinformation
Information isnInformation isntt
knowledge!knowledge!
Information + analytics =Information + analytics =
knowledgeknowledge
Knowledge isnKnowledge isnt decision!t decision!
Knowledge + human =Knowledge + human =decisiondecision
Structure Analytics
Human
Decis
ion
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Last 30 yearsLast 30 years
Economy
BI applicatons
1970 20051990 2000
IBM Microsoft
EIS, MIS
Teradata, Hyperion,
Seagate, Oracle...
RG, DW, OLAP MS OLAP
BSCIndicators
BSCMIS
applications
Golden age of report generators Dashboard
applications
1980
Costs of base technology
(including OLAP)
Total Quality Management
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Complete IT systemComplete IT system
Data WarehouseData Warehouse
Data Marts
Production applications(ERP, MRP...)
OLAP
Analytical applications
(Olap clients, Data Mining...)
Specialized BI applications(Planning & Budgeting, BSC, BPM, CRM, HR...)
Report generators(Crystal, Business Objects, MS Reporting...)
BI
Reporting
Analytical
& reporting
system
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7 mortal sins
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7 mortal sins (57 mortal sins (5--7)7)
"Darwin was right: BI projects need to evolve"Darwin was right: BI projects need to evolve Business demands projects to be short and simple, and to have anBusiness demands projects to be short and simple, and to have an
immediate return, but this could easily lead to the wrong scopinimmediate return, but this could easily lead to the wrong scoping of projects.g of projects.Just as using the same templates time after time mean plans rareJust as using the same templates time after time mean plans rarely evolve,ly evolve,building in the same limitations in to a new system is one of thbuilding in the same limitations in to a new system is one of the greateste greatestinhibitors to success. BI needs to evolve but BI projects shouldinhibitors to success. BI needs to evolve but BI projects should notnot -- theytheyshould start and stop and not evolve.should start and stop and not evolve.
"We can outsource the whole thing"We can outsource the whole thing Enterprises must define their BI key competencies and capabilitiEnterprises must define their BI key competencies and capabilities in orderes in order
to determine what to into determine what to in-- or outsource.or outsource.
"Just give me a dashboard!"Just give me a dashboard! Companies must have a solid and stable BI infrastructure in placCompanies must have a solid and stable BI infrastructure in place first. Theye first. They
should then create a networked approach where these new technoloshould then create a networked approach where these new technologies aregies areable to communicate with other BI technologies inside and outsidable to communicate with other BI technologies inside and outside thee the
organisation, as well as with other technologies such as businesorganisation, as well as with other technologies such as business processs processmanagement and application integration. A management dashboard smanagement and application integration. A management dashboard shouldhouldbe seen as the finishing touch.be seen as the finishing touch.
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Quo Vadis BI?
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Rearrange the BI pyramidRearrange the BI pyramid
5%
15%
80%
Analyses
Dynamic
reporting
Static
eporting
Today (2005)
15%
60%
25%
Analyses
Dynamic
reporting
Static
reporting
Tommorow (2015)
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Business is multidimensional, but whatBusiness is multidimensional, but what
about BI applications?about BI applications?
Fact:Fact: Human perception is multidimensionalHuman perception is multidimensional
Typical business dimensionsTypical business dimensionsTime, Organizational structure, Hierarchies of products,Time, Organizational structure, Hierarchies of products,
Hierarchies of customers (partners),Hierarchies of customers (partners), GeographicGeographical distribution...al distribution...
Conclusion:Conclusion: OLAP data perfectly match humanOLAP data perfectly match humanperceptionperception
Problem:Problem: BI applications generally do not useBI applications generally do not use
OLAP data as much as they shouldOLAP data as much as they should
Solution:Solution: Raise the abstraction level for mostRaise the abstraction level for most BIBI
applicationsapplications toto use OLAP datause OLAP data as a primary sourceas a primary source
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Measurments should be comparableMeasurments should be comparable
Fact:Fact: Human perception is multidimensionalHuman perception is multidimensional
Typical business dimensionsTypical business dimensionsTime, Organizational structure, Hierarchies of products,Time, Organizational structure, Hierarchies of products,Hierarchies of customers (partners),Hierarchies of customers (partners), GeographicGeographical distribution...al distribution...
Conclusion:Conclusion: OLAP data perfectly match humanOLAP data perfectly match humanperceptionperception
Problem:Problem: BI applications generally do not useBI applications generally do not use
OLAP data as much as they shouldOLAP data as much as they should
Solution:Solution: Raise the abstraction level for mostRaise the abstraction level for most BIBI
applicationsapplications toto use OLAP datause OLAP data as a primary sourceas a primary source
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Next 10 years (SMB)Next 10 years (SMB)
BI spendings
2005 201520122007 2010
DW
+
OLAP clients
DW + OLAP clientsDW + OLAP clients
Business analyses
Performance applicationsCBEM and the birth of
networked BI systems
Increase of 50x!
100%
Business analyses
Performance applications
Benchmarking
5,000%
1,500%
2,500%
4,000%