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Introducing  DATA  WAREHOUSING  2010 A tour of definition
RienMatthijsse 1st computer:		1976 ICT:        		1986 ICT freelancer: 	1998 TGF’er: 	  April 	2009
MONDAY
Data Warehousing is no  Rocket science
Sir Isaac Newton
Physics E=mc²
Thermodynamics
Astronomy
The position  of a  Data Warehouse
Decisions Decisions Decisions
Business Performance Indicators
Organization structure
Information Provisioning
Integration
Centralized archive
Solution: Data Warehouse
So what’s so different?
Capturing business processes
Current state
Twinkling
Storage & Retrieval
History
Batch oriented
To BI  or  Data Warehouse
Business  Intelligence
Data Warehouse
Business Intelligence Data warehouse ETL Hardware RDBMS
Talk the talk @ the right place @ the right person
Data  as Information
Presentation
Star models
Ralph Kimball
Ralph Kimball
Product Group Product Customer CustomerGroup Product Line Customer Variety Day Period Week Month Year Per  Product Group Howmuch Revenue Qty Ordered ….. Country Country In the last month Per Country
Multi- Dimensional Data modeling
Historical  correctness
History
Versioning through time
Slow moving Type 2
Data Warehouse  expert
Expert
Literature
Terminology ‘Talk the talk’
Get involved!
Sorry!
Experience
Thank you
END OF PRESENTATION

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Introducing dwh 2010

Notes de l'éditeur

  1. Blue MondayMeestdepressieve dag van het jaarOnzelaatstegoedevoornemensgaanverloren
  2. DWH is omgeven met mysiekMaarDWHinggewooneen ICT discipline en GEEN ROCKETSCIENCE
  3. De appelvaltnietver van de boomZwaartekracht is overalActie = reactie
  4. NatuurkundeKracht = Massa * VersnellingSnelheid = Inisnelheid + versnelling * tijdIntegraalPlaats = init snelheid * tijd + ½ * versnelling * tijd
  5. WarmteVerbrandingRaketmoteren
  6. Plaatsbepaling in de ruimtePlanetenZwartegaten
  7. Niet 1x DWH genoemd: dusDWHing <> RocketscienceGeen NewtonGeenmoeilijkeformulesGeenraketmoterenGeenplaneten en zoHihi
  8. Waarom/waarvooreen DWH inzetten?
  9. Business == beslissingennemenGoedebeslissingen == goederelevanteinformatie
  10. Hoe neemthoger management beslissingen?Waarkomtinformatievandaan?Is deze correct?
  11. Hoe komenzeaaninformatie?Bestaandesystemenleverennietaltijd de juisteVeelalvindenzeinformatiezelf en bewaren die in excel sheets of access databases
  12. CorrectheidAccuraatheidTijdigheid
  13. InformatieuitverschillendebronsystemenSamengebracht in 1 omgevingEeneenduidigheidVastgesteldedefinitie
  14. Iedereenmaaktgebruik van 1 bronvoor businessinformatie
  15. Zo’noplossingheeteen DWH
  16. Vergelijking OLTP> DWH
  17. OLTPregistreren data van business processenVeelgebruikers, tegelijkertijdWeinig resource beslag per gebruikerKorte/kleinetransacties
  18. OTLP data over day-to-day businessGeen to beperkteopslag van historie: eenhuidige order is gekoppeldaan de huidigeinformatie van eenklant
  19. De onderliggende database is continue in beweging, mutatiesvindenveelvuldigplaats
  20. DWH focus:opslag en snelletoegangvoorgrote volumes voorrapportage/analyses
  21. Archief: historie
  22. Wijzigingenzijn batch georienteerd en vindenplaats op vasteverwerkingswindows.
  23. Wanneerspreken we over BI en wanneer over DWHNu vaakverwarrendmn door de specialisten.
  24. BI: het omgaan met informatie relevant bij de uitvoering van eenzekere business.
  25. DWH: opslag en beschikbaarstellen van data
  26. DWH is gereedschapkistvoor BI
  27. Blackbox
  28. Wanneerwordt data informatie?Hoe stel je gebruikers data alsinformatiebeschikbaar?
  29. VeelalstermodellenEen semi genormaliseerdedatamodelvormDimensiesFacts: semi additief
  30. Ooit in de begin jaren ‘90 bedacht door Ralph KimballGrondlegger
  31. Dimensies:Facts:Eenduidigevertaling vaneen BQ  SQL op eensterschema
  32. Profi talk
  33. DWH == historischecorrectheid
  34. Profi talk
  35. Parker is geen expert overnight gewordenJaren van oefenen
  36. Geenwondermiddelbeschikbaar
  37. Lees relevanteliteratuur en boeken
  38. Baboushka talk
  39. Zorgdat je betrokkenraaktbijeen DWH project
  40. Data Warehousing for dummies bestaatniet