{"id":3310,"date":"2022-03-23T08:00:00","date_gmt":"2022-03-23T14:00:00","guid":{"rendered":"https:\/\/idsinc.com\/?p=3310"},"modified":"2026-03-09T15:13:45","modified_gmt":"2026-03-09T21:13:45","slug":"principe-fc8","status":"publish","type":"post","link":"https:\/\/idsinc.com\/fr\/fc-principle8\/","title":{"rendered":"Fact Crashing\u2122 : Principe 8"},"content":{"rendered":"\n
\n <\/div>\n\n\n\n

Utiliser les donn\u00e9es pour fa\u00e7onner d'autres d\u00e9couvertes<\/h1>\n\n\n\n

Ceci est le dixi\u00e8me volet d'une s\u00e9rie de blogs sur Fact Crashing\u2122<\/a>, l'acc\u00e9l\u00e9ration de la prise en compte des donn\u00e9es ACTION (Ambient, Contextual, Transactional, IoT, Operational, Navigational) au profit de la r\u00e9solution des litiges.<\/p>\n\n\n\n

Il y a 9 principes de Crash de faits<\/a>\u2122. Les blogs pr\u00e9c\u00e9dents couvraient\u00a0: <\/p>\n\n\n\n

Principe 1 : Les donn\u00e9es sont des preuves et sont d\u00e9tectables<\/strong><\/a><\/p>\n\n\n\n

Principe 2 : Les donn\u00e9es doivent \u00eatre trait\u00e9es t\u00f4t<\/strong><\/a><\/p>\n\n\n\n

Principe 2 : Analyse approfondie<\/strong><\/a><\/p>\n\n\n\n

Principe\u00a03\u00a0: D\u00e9finir les probl\u00e8mes de cas comme des requ\u00eates centr\u00e9es sur les donn\u00e9es<\/strong><\/a><\/p>\n\n\n\n

Principe 4 : Identifier, qualifier et hi\u00e9rarchiser les sources de donn\u00e9es<\/strong><\/a><\/p>\n\n\n\n

Principe 5 : Les donn\u00e9es sont soumises aux obligations de conservation et de protection<\/strong><\/a><\/p>\n\n\n\n

Principe 6 : La fiabilit\u00e9 des donn\u00e9es commence par une collecte appropri\u00e9e<\/strong><\/a><\/p>\n\n\n\n

Principe 7 : La compr\u00e9hension des donn\u00e9es est requise pour une analyse correcte<\/strong><\/a><\/p>\n\n\n\n

Maintenant, regardons le principe des huit.<\/p>\n\n\n\n

\n\n\n\n

L'un des aspects int\u00e9ressants des donn\u00e9es structur\u00e9es est que les co\u00fbts de traitement des donn\u00e9es structur\u00e9es sont tr\u00e8s diff\u00e9rents de ceux des donn\u00e9es non structur\u00e9es.<\/p>\n\n\n\n

La courbe de co\u00fbt des donn\u00e9es non structur\u00e9es<\/em><\/strong><\/h3>\n\n\n\n

Avec des donn\u00e9es non structur\u00e9es (emails et documents) nous sommes habitu\u00e9s \u00e0 une courbe de co\u00fbt lin\u00e9aire. Chaque document a un co\u00fbt similaire - le co\u00fbt de l'examen humain. L'efficacit\u00e9 technologique peut modifier la pente des co\u00fbts (moins le co\u00fbt par document) ou la dur\u00e9e des co\u00fbts (mettre fin \u00e0 la r\u00e9vision plus t\u00f4t), mais sinon, le co\u00fbt de la r\u00e9vision (et de la r\u00e9vision privil\u00e9gi\u00e9e) est lin\u00e9aire.<\/p>\n\n\n\n

\"\"<\/figure><\/div>\n\n\n\n


Exemple de courbe de co\u00fbt pour les donn\u00e9es non structur\u00e9es<\/strong><\/em><\/p>\n\n\n\n

<\/p>\n\n\n\n

Pour aggraver encore l'examen des documents, il n'est pas rare dans les litiges de ne pas savoir, au d\u00e9part, quels d\u00e9positaires, quels \u00e9v\u00e9nements, quelles dates sont les plus int\u00e9ressants. C'est le \u00ab brouillard du litige \u00bb. Pour naviguer dans cet inconnu, les parties font traditionnellement ce qu'elles font le mieux : elles examinent les documents et les dossiers. Ils naviguent \u00e0 travers les connaissances institutionnelles de l'entreprise telles qu'elles sont enregistr\u00e9es dans les e-mails et r\u00e9v\u00e9l\u00e9es lors d'entretiens. Bien que traditionnelle, cette approche est co\u00fbteuse. Non seulement en raison du co\u00fbt lin\u00e9aire de l'examen des documents, mais en raison de la vaste port\u00e9e initiale avec laquelle de nombreuses enqu\u00eates et litiges commencent. Ce co\u00fbt lin\u00e9aire, plus large port\u00e9e cr\u00e9e un double impact.<\/p>\n\n\n\n

La courbe de co\u00fbt des donn\u00e9es structur\u00e9es<\/em><\/strong><\/h3>\n\n\n\n

Cependant, les donn\u00e9es structur\u00e9es ont un profil de co\u00fbt tr\u00e8s diff\u00e9rent. Les donn\u00e9es structur\u00e9es co\u00fbtent plus cher que les donn\u00e9es non structur\u00e9es sur le front-end pour vous assurer que vous comprenez ce que les donn\u00e9es repr\u00e9sentent. Dans le m\u00eame temps, apr\u00e8s cette initialisation, les donn\u00e9es structur\u00e9es co\u00fbtent beaucoup moins cher que les donn\u00e9es non structur\u00e9es sur une base marginale (enregistrement par enregistrement).<\/p>\n\n\n\n

Cela s'explique en partie par le fait que les enregistrements de donn\u00e9es structur\u00e9es sont g\u00e9n\u00e9ralement tr\u00e8s coh\u00e9rents d'un enregistrement \u00e0 l'autre. Pas dans le contenu, qui peut varier d'un enregistrement \u00e0 l'autre, mais dans leur format, les types de valeurs qu'ils contiennent et la plage de valeurs qu'ils peuvent contenir (domaine) ou le spectre complet des valeurs qu'ils contiennent (plage).<\/p>\n\n\n\n

Une fois que la mani\u00e8re dont un champ particulier est rempli et utilis\u00e9 est comprise, ces caract\u00e9ristiques peuvent \u00eatre facilement anticip\u00e9es et rapidement extrapol\u00e9es \u00e0 travers des enregistrements suppl\u00e9mentaires. Le co\u00fbt marginal peut donc \u00eatre proche de z\u00e9ro.<\/p>\n\n\n\n

Cependant, l'apprentissage initial du mode de remplissage, de l'application, du type de donn\u00e9es, du format, du domaine et de la plage peut \u00eatre co\u00fbteux. Par cons\u00e9quent, le co\u00fbt initial peut \u00eatre \u00e9lev\u00e9.<\/p>\n\n\n\n

Pour cette raison, le profil de co\u00fbt est une pente descendante rapide avec un co\u00fbt faible \u00e0 nul pour chaque enregistrement suppl\u00e9mentaire. Traiter 10 000 enregistrements n'est pas beaucoup moins co\u00fbteux que de traiter 1 000 000, du moins du point de vue de la gestion et de l'\u00e9valuation des donn\u00e9es.<\/p>\n\n\n\n

\"\"<\/figure><\/div>\n\n\n\n

Exemple de courbe de co\u00fbt pour les donn\u00e9es structur\u00e9es<\/strong><\/em><\/p>\n\n\n\n

<\/p>\n\n\n\n

En raison du profil de co\u00fbt diff\u00e9rent, il est \u00e9conomiquement int\u00e9ressant de traiter d'abord les donn\u00e9es structur\u00e9es, puis d'utiliser les donn\u00e9es structur\u00e9es pour affiner et clarifier la port\u00e9e et la pertinence des donn\u00e9es non structur\u00e9es.<\/p>\n\n\n\n

Par exemple, les donn\u00e9es de paie et le codage des heures peuvent parfois mieux clarifier une p\u00e9riode de classe pour un cas d'heures suppl\u00e9mentaires non pay\u00e9es. De m\u00eame, les membres pr\u00e9sum\u00e9s du groupe pour une affaire de responsabilit\u00e9 du fait des produits pourraient \u00eatre mieux identifi\u00e9s par les registres de vente r\u00e9els que par les communications internes par courrier \u00e9lectronique.<\/p>\n\n\n\n

De plus, dans certains cas, les donn\u00e9es structur\u00e9es peuvent non seulement mieux \u00e9clairer les limites du cas que les donn\u00e9es non structur\u00e9es, mais elles peuvent \u00e9galement mieux d\u00e9finir quelles donn\u00e9es non structur\u00e9es doivent m\u00eame \u00eatre prises en compte ou examin\u00e9es.<\/p>\n\n\n\n

Consid\u00e9rez ce qui suit - imaginez un cas de synchronisation du march\u00e9 o\u00f9 l'\u00e9quipe de cas examine des centaines de milliers d'e-mails. Ils utilisent ensuite ces e-mails pour d\u00e9terminer dans quelles transactions boursi\u00e8res ils doivent creuser. Le co\u00fbt de l'examen de ces centaines de milliers d'e-mails peut s'\u00e9lever \u00e0 des millions de dollars. L'approche alternative de Fact Crashing consiste \u00e0 examiner les transactions boursi\u00e8res, voire des centaines de millions de transactions, pour d\u00e9terminer quelles transactions pr\u00e9sentent un int\u00e9r\u00eat, puis \u00e0 examiner les e-mails les plus \u00e9troitement li\u00e9s \u00e0 ces transactions. En donnant la priorit\u00e9 aux donn\u00e9es structur\u00e9es plut\u00f4t qu'aux donn\u00e9es non structur\u00e9es, le co\u00fbt (et la rapidit\u00e9) de la recherche et de l'examen des transactions int\u00e9ressantes, et m\u00eame de la r\u00e9solution du litige, peuvent \u00eatre consid\u00e9rablement affect\u00e9s.<\/p>\n\n\n\n

\u00c9tant donn\u00e9 que le profil de co\u00fbt des donn\u00e9es structur\u00e9es est si diff\u00e9rent, le co\u00fbt par enregistrement est n\u00e9gligeable, mais la valeur par enregistrement ne l'est pas. En tant que tels, les ensembles de disques \u00e0 volume \u00e9lev\u00e9 deviennent un avantage plut\u00f4t qu'un inconv\u00e9nient. C'est un avantage car chaque enregistrement individuel a une valeur potentielle et parce que de grandes collections d'enregistrements peuvent r\u00e9v\u00e9ler des tendances, des chronologies, des variations statistiques et d'autres mesures d'une mani\u00e8re que les donn\u00e9es structur\u00e9es ne peuvent pas r\u00e9v\u00e9ler.<\/p>\n\n\n\n

"Le Smoking Gun est maintenant la tendance du fumeur"<\/em><\/strong><\/p>\n\n\n\n

Par cons\u00e9quent, les donn\u00e9es structur\u00e9es peuvent \u00eatre utilis\u00e9es pour d\u00e9finir ou fa\u00e7onner de nombreuses dimensions d'un litige donn\u00e9, notamment\u00a0:<\/p>\n\n\n\n

  • La p\u00e9riode de classe<\/em><\/li>
  • Les membres putatifs de la classe<\/em><\/li>
  • L'exposition potentielle<\/em><\/li>
  • Les transactions particuli\u00e8res en cause<\/em><\/li>
  • Employ\u00e9s potentiels (ou d\u00e9positaires) d'int\u00e9r\u00eat<\/em><\/li>
  • Quels mod\u00e8les de produits pourraient \u00eatre d\u00e9fectueux ou en cause<\/em><\/li>
  • Les dates cl\u00e9s des communications d'int\u00e9r\u00eat<\/em><\/li>
  • Etc. Etc. Etc.<\/em><\/li><\/ul>\n\n\n\n

    En retour, ces dimensions, lorsqu'elles sont utilis\u00e9es comme filtres, peuvent conduire \u00e0 une grande efficacit\u00e9 dans la collecte, le traitement, la cat\u00e9gorisation et l'examen des donn\u00e9es non structur\u00e9es des m\u00e9mos, des e-mails, des textes, de la messagerie instantan\u00e9e, des documents et des m\u00e9dias sociaux.<\/p>\n\n\n\n

    En r\u00e9sum\u00e9, \u00e9tant donn\u00e9 que les donn\u00e9es structur\u00e9es ont une courbe de co\u00fbts (et une courbe d'avantages) diff\u00e9rente de celle des donn\u00e9es non structur\u00e9es, non seulement il est souvent plus \u00e9conomique d'essayer de r\u00e9soudre l'int\u00e9gralit\u00e9 du litige avec les donn\u00e9es structur\u00e9es, m\u00eame lorsque vous ne pouvez pas, vous pourrez peut-\u00eatre r\u00e9soudre une partie du litige, et vous pourrez peut-\u00eatre limiter (fa\u00e7onner) la taille, la complexit\u00e9 et les co\u00fbts de la d\u00e9couverte de vos documents.<\/p>\n\n\n\n

    \n\n\n\n

    iDS fournit des solutions de donn\u00e9es consultatives aux entreprises et aux cabinets d'avocats du monde entier, leur donnant un avantage d\u00e9cisif - \u00e0 la fois dans et hors de la salle d'audience. Nos experts en la mati\u00e8re et nos strat\u00e8ges de donn\u00e9es se sp\u00e9cialisent dans la recherche de solutions aux probl\u00e8mes de donn\u00e9es complexes, garantissant que les donn\u00e9es peuvent \u00eatre exploit\u00e9es comme un atout et non comme un handicap.<\/em><\/strong><\/p>","protected":false},"excerpt":{"rendered":"

    Use Data to Shape Other Discovery This is the tenth installment in a blog series on Fact Crashing\u2122, the acceleration of the consideration of ACTION data (Ambient, Contextual, Transactional, IoT, Operational, Navigational) to the benefit of resolving disputes. There are 9 Principles of Fact Crashing\u2122. Earlier blogs covered:  Principle 1: Data is Evidence and is […]<\/p>\n","protected":false},"author":7,"featured_media":3432,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[10,38],"tags":[16],"class_list":["post-3310","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog","category-methodologies","tag-fact-crashing","has-post-title","has-post-date","has-post-category","has-post-tag","has-post-comment","has-post-author",""],"yoast_head":"\nFact Crashing\u2122: Principle 8 - Use Data to Shape Other Discovery<\/title>\n<meta name=\"description\" content=\"In the 10th Fact Crashing\u2122 installment, iDiscovery Solutions discusses the 8th principle, using Data to shape other Discovery.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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