{"id":8401,"date":"2026-08-13T13:15:58","date_gmt":"2026-08-13T11:15:58","guid":{"rendered":"https:\/\/t2b.ch\/?page_id=8401"},"modified":"2026-08-13T13:41:06","modified_gmt":"2026-08-13T11:41:06","slug":"datenmanagement","status":"publish","type":"page","link":"https:\/\/t2b.ch\/en\/datenmanagement\/","title":{"rendered":"Data Management"},"content":{"rendered":"<div data-elementor-type=\"wp-page\" data-elementor-id=\"8401\" class=\"elementor elementor-8401\" data-elementor-post-type=\"page\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-29d214c6 elementor-section-boxed elementor-section-height-default elementor-section-height-default wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-column-slider-no wpr-equal-height-no\" data-id=\"29d214c6\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-96f6dc1\" data-id=\"96f6dc1\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-99e7e32 elementor-widget elementor-widget-html\" data-id=\"99e7e32\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h1 style=\"text-align: center;\"><span style=\"font-size: clamp(32px, 6vw, 58px); font-weight: bold; color: #ffffff;         line-height: 1.15; display: inline-block;\">Data Management &amp; Data Products <br>that your AI can trust.<\/span><br><br><span style=\"font-size: 20px; font-weight: 400; color: #ffffff; line-height: 1.3; display:  inline-block;\">We help Swiss companies and public authorities organize their data so that AI can work with it reliably: clear responsibilities, clean definitions, resilient data products. Your data stays within your own infrastructure. And we start with a concrete use case, not a concept paper.<\/span><\/h1>  \t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-4cbe2204 elementor-section-boxed elementor-section-height-default elementor-section-height-default wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-column-slider-no wpr-equal-height-no\" data-id=\"4cbe2204\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-1d0e8117\" data-id=\"1d0e8117\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-8bb28a0 elementor-widget elementor-widget-html\" data-id=\"8bb28a0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t <style>\r\n  .t2b-content table{width:100%;border-collapse:collapse;margin:1.5em 0}\r\n  .t2b-content th,.t2b-content td{padding:.7em .9em;text-align:left;vertical-align:top;border-bottom:1px solid\r\n  rgba(128,128,128,.28)}\r\n  .t2b-content thead th{border-bottom-width:2px;font-weight:600}\r\n  .t2b-content .t2b-scroll{overflow-x:auto;-webkit-overflow-scrolling:touch}\r\n  .t2b-content ul{margin:1em 0;padding-left:1.4em}\r\n  .t2b-content li{margin-bottom:.5em}\r\n  .t2b-content h2{margin-top:2em}\r\n  .t2b-content h3{margin-top:1.5em}\r\n  .t2b-content .t2b-cta{border-left:4px solid currentColor;padding:1em 1.4em;margin:2.5em 0;opacity:.95}\r\n  .t2b-content .t2b-cta p{margin:.4em 0}\r\n  <\/style>\r\n\r\n  <div class=\"t2b-content\">\r\n\r\n    <p>Data management determines whether AI creates real impact in a company or stays stuck in the prototype stage. The   bottleneck isn't the model, but whether the data is findable, understood, maintained, and owned. We help Swiss companies turn scattered data assets into resilient data products \u2013 with clear roles, pragmatic architecture, and an approach oriented toward value rather than tools.<\/p>\r\n\r\n    <h2>What is Data Management?<\/h2>\r\n\r\n    <p>Data management encompasses all the tasks a company uses to capture, integrate, quality-assure, describe, protect, and provide its data. This includes data architecture, master data management, data integration, data quality, metadata, and data governance. The goal is for every person and every system in the company to receive exactly the data they need \u2013 in reliable quality, at the right time, and with clearly defined authorization.<\/p>\r\n\r\n    <p>In practice, data management rarely fails because of the technology. It fails because no one is clearly responsible, because the same metric has three different values in three systems, or because knowledge about data assets depends on individual people.<\/p>\r\n\r\n    <h2>From Data to Data Products<\/h2>\r\n\r\n    <p class=\"translation-block\">Ein <strong>Datenprodukt<\/strong> ist ein klar abgegrenzter Datenbestand, der wie ein Produkt gef\u00fchrt wird: mit     \r\n  benanntem Owner, dokumentierter Bedeutung, zugesicherter Qualit\u00e4t, stabiler Schnittstelle und definiertem Lebenszyklus.  \r\n  Es ist damit mehr als eine Tabelle oder ein Report \u2013 es ist eine verl\u00e4ssliche Zusage an alle, die damit arbeiten.<\/p>    \r\n\r\n    <p>The difference to classic project thinking:<\/p>\r\n\r\n    <ul>\r\n      <li class=\"translation-block\"><strong>Zweckgebunden statt universell<\/strong> \u2013 ein Datenprodukt l\u00f6st eine konkrete fachliche Fragestellung,   \r\n  statt alle denkbaren Auswertungen abdecken zu wollen.<\/li>\r\n      <li class=\"translation-block\"><strong>Verantwortet statt verwaist<\/strong> \u2013 es gibt eine Person, die \u00fcber Inhalt, Qualit\u00e4t und Freigabe       \r\n  entscheidet.<\/li>\r\n      <li class=\"translation-block\"><strong>Documented rather than implicit<\/strong> \u2013 definitions, origin, and currency are traceable.<\/li>  \r\n      <li class=\"translation-block\"><strong>Wiederverwendbar statt einmalig<\/strong> \u2013 andere Bereiche und Systeme k\u00f6nnen darauf aufbauen, auch      \r\n  KI-Anwendungen.<\/li>\r\n    <\/ul>\r\n\r\n    <p>Data products are the point at which data management turns from a cost center into a value contribution: they make the\n  benefit visible and fundable.<\/p>\r\n\r\n    <h2>Why AI Doesn't Work Without Data Management<\/h2>\r\n\r\n    <p>AI applications amplify the quality of the underlying data \u2013 for better or worse. A chatbot built on unstructured and outdated documents delivers confidently phrased wrong answers. Semantic search only finds what is cleanly described. And AI-driven process automation is only as reliable as the master data it accesses.<\/p>\r\n\r\n    <p>Concretely, AI requires the following from data management:<\/p>\r\n\r\n    <div class=\"t2b-scroll\">\r\n      <table>\r\n        <thead>\r\n          <tr><th>Requirement<\/th><th>What does it mean ...<\/th><\/tr>\r\n        <\/thead>\r\n        <tbody>\r\n          <tr><td><strong>Discoverability<\/strong><\/td><td>Data catalog and metadata, so it's clear which source is authoritative<\/td><\/tr>\r\n          <tr><td><strong>Quality<\/strong><\/td><td>Measurable rules instead of gut feeling \u2013 completeness, currency, consistency<\/td><\/tr>\r\n          <tr><td><strong>Context<\/strong><\/td><td>Business definitions, so that a model correctly interprets \"customer\" or \"revenue\"<\/td><\/tr>\r\n          <tr><td><strong>Access Control<\/strong><\/td><td>Traceable access control that also applies to AI agents<\/td><\/tr>\r\n          <tr><td><strong>Nachvollziehbarkeit<\/strong><\/td><td>Origin and processing path of every value \u2013 a prerequisite for audit and trust<\/td><\/tr>\r\n        <\/tbody>\r\n      <\/table>\r\n    <\/div>\r\n\r\n    <p>That's why we don't start AI initiatives by selecting a model, but by asking which data the application actually needs to carry \u2013 and whether it can do so today.<\/p>\r\n\r\n    <h2>Organisation und Verantwortlichkeiten im Datenmanagement<\/h2>\r\n\r\n    <p>Datenmanagement ist zu einem grossen Teil eine Organisationsfrage. Technik l\u00e4sst sich beschaffen, Verantwortung     \r\n  nicht. Erfolgreiche Datenorganisationen kl\u00e4ren deshalb fr\u00fch, wer welche Entscheidungen trifft \u2013 und verankern das dort,  \r\n  wo das fachliche Wissen liegt, nicht ausschliesslich in der IT.<\/p>\r\n\r\n    <h3>Governance that works in everyday life<\/h3>\r\n\r\n    <p>We advise against extensive governance frameworks that no one reads after rollout. What works is a lean framework that clarifies three things: What data domains exist, and who is responsible for them? How are definitions decided when departments disagree? And how is data quality measured? Everything else is better developed alongside the first concrete data products than on the drawing board.<\/p>\r\n\r\n    <h2>Data management consulting in Basel, Bern, and throughout Switzerland<\/h2>\r\n\r\n    <p class=\"translation-block\">Als Schweizer Beratungsunternehmen mit Standorten in <strong>Basel<\/strong> und <strong>Bern<\/strong> arbeiten wir  \r\n  seit 2001 an der Schnittstelle von Fachbereich, Daten und IT. Unsere Herkunft liegt in der Integrations- und\r\n  Unternehmensarchitektur \u2013 wir kennen gewachsene Systemlandschaften und die Realit\u00e4t hinter den Pr\u00e4sentationsfolien.<\/p>  \r\n\r\n    <p>For clients in northwestern Switzerland and the Bern area, we're on-site at short notice; across Switzerland we work in a hybrid model. Where requirements call for it, your data stays within your own infrastructure.<\/p>\r\n\r\n    <h2>H\u00e4ufige Fragen zum Datenmanagement<\/h2>\r\n\r\n    <h3>What is the difference between data management and data governance?<\/h3>\r\n    <p>Data management encompasses the operational work with data \u2013 integration, quality assurance, provisioning. Data governance is the overarching framework: it defines who decides, which rules apply, and how responsibilities are distributed. Governance without operational data management remains paper; data management without governance leads to siloed solutions.<\/p>\r\n\r\n    <h3>Where should we start?<\/h3>\r\n    <p>With a concrete use case that resolves a noticeable bottleneck \u2013 not with a company-wide data catalog. A first productive data product creates a learning curve, credibility, and budget for the next steps.<\/p>\r\n\r\n    <h3>Do we need a data platform before we can use AI?<\/h3>\r\n    <p>No. For many AI use cases, it's enough to specifically prepare and take ownership of the actually needed data assets. A complete platform is rarely the prerequisite \u2013 more often it's the result of several successful data products.<\/p>\r\n\r\n    <h3>How many roles do we need to fill?<\/h3>\r\n    <p>In smaller organizations, data owner and data steward are often filled part-time by the same people. What matters isn't the number of positions, but that responsibility is clearly assigned by name and accepted in everyday practice.<\/p>\r\n\r\n    <div class=\"t2b-cta\">\r\n      <p><strong>Where does your data management stand today?<\/strong><\/p>\r\n      <p>In a no-obligation initial conversation, we assess your starting point and show you which next step will have the greatest impact.<\/p>\r\n      <p><a href=\"https:\/\/t2b.ch\/en\/contact\/\">Book a call \u2192<\/a><\/p>\r\n    <\/div>\r\n\r\n  <\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-74dd5c43 elementor-section-boxed elementor-section-height-default elementor-section-height-default wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-column-slider-no wpr-equal-height-no\" data-id=\"74dd5c43\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-2512de7c\" data-id=\"2512de7c\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-705f0320 elementor-widget elementor-widget-heading\" data-id=\"705f0320\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">One conversation. Your use cases. Clear answers.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b47cd18 elementor-widget elementor-widget-text-editor\" data-id=\"b47cd18\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align:center\">In 45 minutes, we show you where AI can realistically save you time or money and what you should start with. You speak directly with our CEO. And if we don\u2019t see a viable use case, we will tell you openly.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c206c07 elementor-align-center elementor-widget elementor-widget-button\" data-id=\"c206c07\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-lg\" href=\"mailto:info@t2b.ch?subject=Anfrage%20Erstgespr%C3%A4ch%20zur%20KI-Unterst%C3%BCtzung\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Book a call<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"<p>Datenmanagement und Datenprodukte, auf die sich Ihre KI verlassen kann. Wir helfen Schweizer Unternehmen und Beh\u00f6rden, ihre Daten so zu ordnen, dass KI darauf verl\u00e4sslich funktioniert: klare Verantwortlichkeiten, saubere Definitionen, belastbare Datenprodukte. Ihre Daten bleiben in Ihrer eigenen Infrastruktur. Und wir starten mit einem konkreten Anwendungsfall, nicht mit einem Konzeptpapier. Datenmanagement entscheidet dar\u00fcber, ob KI<\/p>","protected":false},"author":6,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"site-sidebar-layout":"no-sidebar","site-content-layout":"page-builder","ast-site-content-layout":"full-width-container","site-content-style":"unboxed","site-sidebar-style":"unboxed","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"disabled","ast-breadcrumbs-content":"","ast-featured-img":"disabled","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"enabled","adv-header-id-meta":"","stick-header-meta":"default","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center 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