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Lecture Structure
- Hasso (00:00:01)
- Quality (00:00:38)
- Robert Pirsig (00:00:38)
- know what it is (00:00:38)
- cannot be He ne t You (00:00:38)
- Even though quality (00:00:38)
- Zoom in die Informationsqualität (00:01:10)
- N ChkOIT1ITI StE e (00:03:24)
- ursprünglich nur um Korrektur einer Abrechnung in Höhe von 67 Euro gebeten (00:03:24)
- Als eine Französin aus Lothringen unlängst ihre Telefonrechnung bekam blieb ihr (00:03:24)
- Telefonkundin erhält Rechnung über 63 Millionen Euro (00:03:24)
- Deutsche Namen (00:04:25)
- Schwierige Namen (00:04:53)
- Falsche Duplikate (00:05:51)
- Q E Alexander B lke Jens Ble holder Chnscogh Bohm Karsten Draba Fsl x Naumann Melan e We s (00:05:51)
- Melanie Weis (00:05:51)
- Ur ternehmenscluplikate (00:06:24)
- Datenqualität Probleme (00:08:49)
- Datenqualität Probleme Klassif katio von Dat (00:09:19)
- K fe llel 6 INEQTIIBK T cEre bfeI e F verletztW (00:09:19)
- Attributabh ngigkeit CFSVETZÜTÜ e v EL2 a c e erteE ndeut gke t verletzt Falsche ReferenzReferentielle Integritat KFYPÜSWS WerteVe ew E ngebettete Wene (00:09:19)
- KUNDE Geb dam 123 3 Schemaebene DatenebeneMark Kuhn 18 2 8 Ei ut i V Unzuläss ger Wert Femende Werte Attributabh ngigkeit sC re bfeh e V 5L2f Falsche WerteADRESSE IME im l Falcnhe Referem 11 M (00:09:19)
- I assifi ation von Datenfehlern (00:09:20)
- Heterogenität E nheiten (00:09:20)
- Schem tisch Unfersch edl che (00:09:20)
- Kryptische Werte (00:09:20)
- E ndeut gkevt verletzt (00:09:20)
- Schem aebene (00:09:20)
- DQ Probleme Auswirkungen (00:10:46)
- DQ Probleme Auswirkun Hilfsmittel (00:13:19)
- 50 80 iger Einträge im (00:13:19)
- Se bstentwickeiteTools (00:13:19)
- Programmiersprachen (00:13:19)
- Text Editor (00:13:19)
- Hilfsmittel (00:13:20)
- Gesuncle lvlenschenverstand (00:13:45)
- Gesunder Menschenverstand (00:13:46)
- Gesuncler ME lSCh6 lV FSt l 1d (00:13:47)
- l ru v rl l I cnI3 u luc l ul S139 u lliu (00:13:47)
- 1Ä fm on pmpcn) hu um m kcnl) xalucd al S139 mill on s ih (00:13:47)
- G6SU lC e V el 1SC 1e 1V Standardisierung (00:14:46)
- Geburtsdaten (00:14:46)
- 10 0006 = 10T EURO = 10k EUR (00:14:46)
- Numerische Daten (00:14:46)
- Hewlett Packard Development Com (00:14:46)
- Dr Ing h c F PorscheAG (00:14:46)
- Frankfurt a M Frankfurt M Fre (00:14:46)
- 1 f m @ luca 2115189 m mm (00:14:46)
- Rudo (00:14:46)
- S 1( 0 Wacnn a property tha (00:14:46)
- Standardis erung (00:14:47)
- Standardisierung (00:16:13)
- Strukturierung Personen (00:16:14)
- VOITIHIIIE (00:16:41)
- An rede Tifel (00:16:41)
- An rede Titel (00:16:41)
- Vßf ame (00:16:41)
- Nachname (00:16:41)
- An rede Tit l (00:16:41)
- Strukturierung Strukturierung (00:16:50)
- Strukturierung Stf ßen (00:16:51)
- Strukturierung Stf ße (00:17:09)
- Versteckter Mehrwert (00:17:34)
- Uberbl ck (00:19:20)
- Wie entstehen Duplikate? (00:22:56)
- Mehrere De nitionen eines Kernobjekts sind die lege ßne von Kunde Eli UmE11119hmnn? @ ie en in Ihrem Ur ta neh nml (00:24:08)
- Duplikaterkennung (00:29:30)
- Lösung Algorithmen (00:29:30)
- Duplikaterkennung ist das Finden mehrerer Repräsentationen (00:29:30)
- Duplikate (00:30:59)
- Wirkungen von Duplikaten (00:40:08)
- Duplikaterkennung hat viele Duplikate (00:41:23)
- Duplikaterkennung (00:43:39)
- Überblick (00:46:28)
- Overview S milaritv l leasures Jaccard (00:46:44)
- L6VEl lShtei ÜiSt 1Ce (00:47:19)
- L6V6 1Shteil 1 ÜiSta 1Ce (00:49:25)
- LeVeI 1ShtEi 1 ÜiSt lC6 (00:49:26)
- gj Jyw f f 1 ll 1il1( I (00:53:32)
- 4 54fg 4 (00:53:32)
- Q H321 3432B231 (00:53:32)
- E mn waQ (00:55:27)
- 4Le er shreinD sr1113JonesX( X ms Paul (00:55:27)
- Distance (00:59:00)
- 6543 (00:59:00)
- Ü mer u LEVenShtEil C iSt l 1Ce (00:59:34)
- LEVEl lS l CEiFl Distance (01:01:04)
- Ü I eF l I LEVel lS ltGil C iSt lCe (01:01:42)
- Jaro (01:01:43)
- Jaro Winkler (01:06:34)
- sim M 0 92 (01:06:34)
- sim M 0 79 (01:06:34)
- upwards for having common prefixes (typically p=O 1) (01:06:34)
- p constant scaling factor for how much the score is adjusted (01:06:34)
- I length of common pre x up to a maximum of 4 characters (01:06:34)
- Extension of Jaro distance considering a common pre x (01:06:34)
- Overview Similarity Measures Jaccard (01:09:24)
- Token based Similar ty Measuras (01:09:47)
- Overview Similarity Measures Jaccard (01:14:03)
- Soundex Digit Letters Soundex codes a last name based (01:14:09)
- both with and without the pre x (01:14:09)
- Jenkins Jansen (01:14:09)
- Van Con De Di La or Le code (01:14:09)
- JOHNSON J525 (01:14:09)
- J520 (01:14:09)
- JONES (01:14:09)
- PUAL (01:14:09)
- Letter Contexf (01:18:54)
- JOHNSON 686 (01:18:54)
- JONES (01:18:54)
- PUAL (01:18:54)
- PAUL (01:18:54)
- Example (01:18:54)
- same code and 0 are (01:18:54)
- Multiple occurrences of the (01:18:54)
- Code length is not restricted (01:18:54)
- based on the context (01:18:54)
- Letters get different codes (01:18:54)
- for German last names (01:18:54)
- Overv ew S milarity Measures J accard (01:20:58)
- Monge Elkan (01:21:06)
- Overview Similarity Measures Jaccard (01:24:15)
- Double (01:24:15)
- Rulä (01:24:15)
- Y S011 TF IDF (01:24:15)
- 34 Menge Elkan (01:24:15)
- Edit based (01:24:15)
- Domain dependent Similarity Measures (01:24:39)
- Überblick (01:29:43)
- C SSifiC tiOI 1 (01:29:44)
- Überblick (01:31:29)
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