{"id":3554,"date":"2022-04-26T06:51:53","date_gmt":"2022-04-26T14:51:53","guid":{"rendered":"https:\/\/www.gudusoft.com\/?p=3554"},"modified":"2026-07-11T22:56:12","modified_gmt":"2026-07-12T06:56:12","slug":"amazon-redshift-data-lineage-gudu-sqlflow","status":"publish","type":"post","link":"https:\/\/www.gudusoft.com\/fr\/amazon-redshift-data-lineage-gudu-sqlflow\/","title":{"rendered":"Lign\u00e9e de donn\u00e9es Amazon Redshift | Gudu SQLFlow"},"content":{"rendered":"<p><\/p>\r\n<h2><strong>Lign\u00e9e de donn\u00e9es Amazon Redshift | Gudu SQLFlow<\/strong><\/h2>\r\n\r\n<p>Dans votre environnement d&#039;entrep\u00f4t Amazon, utilisez <strong><a class=\"rank-math-link\" href=\"https:\/\/docs.aws.amazon.com\/redshift\/latest\/dg\/c-getting-started-using-spectrum.html\">Spectre Redshift d&#039;Amazon<\/a><\/strong> Pour interroger directement des donn\u00e9es \u00e0 partir de fichiers sur Amazon S3, les enregistrer dans des bases de donn\u00e9es Redshift et utiliser des outils de Business Intelligence tels que Tableau, Power BI, Looker, Qlik et Superset afin de g\u00e9n\u00e9rer des rapports, les donn\u00e9es proviennent de votre syst\u00e8me source et sont stock\u00e9es sur Amazon S3. Un outil ETL comme DBT permet ensuite de les transf\u00e9rer et de les stocker dans une base de donn\u00e9es Redshift pour une utilisation ult\u00e9rieure.<\/p>\r\n\r\n<figure id=\"attachment_3581\" aria-describedby=\"caption-attachment-3581\" style=\"width: 577px\" class=\"wp-caption aligncenter\"><img decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-3581\" src=\"https:\/\/www.gudusoft.com\/wp-content\/uploads\/2022\/04\/Amazon_Redshift_Data_Lineage.png\" alt=\"Lign\u00e9e de donn\u00e9es Amazon Redshift\" width=\"577\" height=\"402\" srcset=\"https:\/\/www.gudusoft.com\/wp-content\/uploads\/2022\/04\/Amazon_Redshift_Data_Lineage.png 577w, https:\/\/www.gudusoft.com\/wp-content\/uploads\/2022\/04\/Amazon_Redshift_Data_Lineage-300x209.png 300w, https:\/\/www.gudusoft.com\/wp-content\/uploads\/2022\/04\/Amazon_Redshift_Data_Lineage-200x139.png 200w, https:\/\/www.gudusoft.com\/wp-content\/uploads\/2022\/04\/Amazon_Redshift_Data_Lineage-400x279.png 400w\" sizes=\"(max-width: 577px) 100vw, 577px\" \/><figcaption id=\"caption-attachment-3581\" class=\"wp-caption-text\">Lign\u00e9e de donn\u00e9es Amazon Redshift<\/figcaption><\/figure>\r\n\r\n<p>Pour avoir une vue d&#039;ensemble du flux de donn\u00e9es dans votre syst\u00e8me d&#039;entrep\u00f4t Amazon, vous avez besoin d&#039;un <strong>outil de lign\u00e9e de donn\u00e9es<\/strong> pour vous aider \u00e0 comprendre comment les donn\u00e9es sont arriv\u00e9es \u00e0 un emplacement particulier, ainsi que les \u00e9tapes interm\u00e9diaires et les transformations qui se produisent lorsque les donn\u00e9es circulent dans le syst\u00e8me d&#039;information.<\/p>\r\n\r\n\r\n\r\n<p>Une fa\u00e7on d&#039;obtenir <strong><a class=\"rank-math-link\" href=\"https:\/\/www.gudusoft.com\/fr\/whats-data-lineage-why-important\/\">la lign\u00e9e des donn\u00e9es<\/a><\/strong> L&#039;analyse automatique, depuis l&#039;environnement d&#039;entrep\u00f4t Amazon, de toutes les requ\u00eates SQL utilis\u00e9es lors du chargement, de la transformation et de l&#039;analyse des donn\u00e9es est une fonctionnalit\u00e9 essentielle. Bonne nouvelle\u00a0: toutes ces instructions SQL sont stock\u00e9es dans\u2026 <strong><a class=\"rank-math-link\" href=\"https:\/\/docs.aws.amazon.com\/redshift\/latest\/mgmt\/db-auditing.html#db-auditing-logs\">journal d&#039;activit\u00e9 des utilisateurs de Redshift<\/a><\/strong> et <strong>Gudu<\/strong><strong> SQLFlow<\/strong> peut analyser ces fichiers journaux pour d\u00e9couvrir automatiquement la provenance des donn\u00e9es.<\/p>\r\n\r\n\r\n\r\n<h3 class=\"wp-block-heading\">Journal d&#039;activit\u00e9 utilisateur de Redshift<\/h3>\r\n\r\n\r\n\r\n<p>Le journal d&#039;activit\u00e9 utilisateur est principalement utile pour le d\u00e9pannage\u00a0; ici, nous l&#039;utilisons pour retracer la provenance des donn\u00e9es. Il enregistre les informations relatives aux types de requ\u00eates effectu\u00e9es par les utilisateurs et le syst\u00e8me dans la base de donn\u00e9es.<\/p>\r\n\r\n\r\n\r\n<p><strong>Enregistre chaque requ\u00eate avant son ex\u00e9cution sur la base de donn\u00e9es.<\/strong><\/p>\r\n\r\n\r\n\r\n<figure id=\"w251aac30c24c10b9c18b4\" class=\"wp-block-table\">\r\n<table>\r\n<thead>\r\n<tr>\r\n<th>Nom de la colonne<\/th>\r\n<th>Description<\/th>\r\n<\/tr>\r\n<\/thead>\r\n<tbody>\r\n<tr>\r\n<td>temps record<\/td>\r\n<td>L&#039;heure \u00e0 laquelle l&#039;\u00e9v\u00e9nement s&#039;est produit.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>base de donn\u00e9es<\/td>\r\n<td>Nom de la base de donn\u00e9es.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>utilisateur<\/td>\r\n<td>Nom d&#039;utilisateur.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>pid<\/td>\r\n<td>ID du processus associ\u00e9 \u00e0 l&#039;instruction.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>ID de l&#039;utilisateur<\/td>\r\n<td>ID de l&#039;utilisateur.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>xid<\/td>\r\n<td>ID de transaction.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>requ\u00eate<\/td>\r\n<td>Un pr\u00e9fixe LOG\u00a0: suivi du texte de la requ\u00eate, y compris les sauts de ligne.<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n<figcaption>Redshift user activity log<\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n<p>V\u00e9rifiez s&#039;il vous pla\u00eet <a class=\"rank-math-link\" href=\"https:\/\/docs.aws.amazon.com\/redshift\/latest\/mgmt\/db-auditing.html#db-auditing-logs\">cet article<\/a> pour savoir comment activer la journalisation.<\/p>\r\n<p>\r\n\r\n<\/p>\r\n<h5 class=\"wp-block-heading\">Exemple de journal d&#039;audit d&#039;activit\u00e9 utilisateur Amazon Redshift<\/h5>\r\n<p>\r\n\r\n<\/p>\r\n<pre class=\"wp-block-code\"><code>&#039;2018-05-21T06:00:09Z UTC [ db=prod_sales user=duc pid=99753 userid=95 xid=6728324 ]&#039; LOG: create table SumoProdbackUp.organization as (select * from SumoProd.simpleuser) &#039;2018-05-21T06:00:09Z UTC [ db=vendor user=ankit pid=36616 userid=53 xid=2956702 ]&#039; LOG: DELETE FROM SumoProd.employee WHERE id = 38; &#039;2018-05-21T06:20:09Z UTC [ db=dev user=himanshu pid=64458 userid=35 xid=5143208 ]&#039; LOG: drop user testuser3<\/code><\/pre>\r\n<p>\r\n\r\n<\/p>\r\n<p>&nbsp;<\/p>\r\n<p>\r\n\r\n<\/p>\r\n<h3 class=\"wp-block-heading\">Analyse automatique de la lign\u00e9e des donn\u00e9es<\/h3>\r\n<p>\r\n\r\n<\/p>\r\n<p><strong><a class=\"rank-math-link\" href=\"https:\/\/sqlflow.gudusoft.com\">Gudu SQLFlow<\/a><\/strong> Cet outil automatise l&#039;analyse de la tra\u00e7abilit\u00e9 des donn\u00e9es SQL dans les environnements de bases de donn\u00e9es, ETL, Business Intelligence, Cloud et Hadoop en analysant les scripts SQL et les proc\u00e9dures stock\u00e9es. Il peut \u00e9galement analyser les fichiers journaux d&#039;activit\u00e9 des utilisateurs Redshift pour retracer la tra\u00e7abilit\u00e9 des donn\u00e9es et repr\u00e9senter graphiquement tous leurs mouvements.<\/p>\r\n<p>\r\n\r\n<\/p>\r\n<p>Voici un extrait d&#039;un sch\u00e9ma de tra\u00e7abilit\u00e9 des donn\u00e9es g\u00e9n\u00e9r\u00e9 apr\u00e8s l&#039;analyse des fichiers journaux d&#039;activit\u00e9 des utilisateurs d&#039;Amazon Redshift\u00a0:<\/p>\r\n<p>\r\n\r\n<\/p>\r\n<figure class=\"wp-block-image size-large\"><\/figure>\r\n<p>\r\n\r\n<\/p>\r\n<figure class=\"wp-block-image alignnone wp-image-3564\"><a href=\"https:\/\/sqlflow.gudusoft.com\"><img decoding=\"async\" loading=\"lazy\" width=\"1024\" height=\"300\" class=\"wp-image-3564\" src=\"https:\/\/www.gudusoft.com\/wp-content\/uploads\/2022\/04\/amazon-redshift-user-activity-log-data-lineage-1024x300.png\" alt=\"Lign\u00e9e de donn\u00e9es Amazon Redshift\u00a0\" srcset=\"https:\/\/www.gudusoft.com\/wp-content\/uploads\/2022\/04\/amazon-redshift-user-activity-log-data-lineage-1024x300.png 1024w, https:\/\/www.gudusoft.com\/wp-content\/uploads\/2022\/04\/amazon-redshift-user-activity-log-data-lineage-300x88.png 300w, https:\/\/www.gudusoft.com\/wp-content\/uploads\/2022\/04\/amazon-redshift-user-activity-log-data-lineage-768x225.png 768w, https:\/\/www.gudusoft.com\/wp-content\/uploads\/2022\/04\/amazon-redshift-user-activity-log-data-lineage-1536x450.png 1536w, https:\/\/www.gudusoft.com\/wp-content\/uploads\/2022\/04\/amazon-redshift-user-activity-log-data-lineage-200x59.png 200w, https:\/\/www.gudusoft.com\/wp-content\/uploads\/2022\/04\/amazon-redshift-user-activity-log-data-lineage-400x117.png 400w, https:\/\/www.gudusoft.com\/wp-content\/uploads\/2022\/04\/amazon-redshift-user-activity-log-data-lineage-600x176.png 600w, https:\/\/www.gudusoft.com\/wp-content\/uploads\/2022\/04\/amazon-redshift-user-activity-log-data-lineage-800x234.png 800w, https:\/\/www.gudusoft.com\/wp-content\/uploads\/2022\/04\/amazon-redshift-user-activity-log-data-lineage-1200x352.png 1200w, https:\/\/www.gudusoft.com\/wp-content\/uploads\/2022\/04\/amazon-redshift-user-activity-log-data-lineage.png 1778w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/a>\r\n<figcaption>Lign\u00e9e de donn\u00e9es Amazon Redshift<\/figcaption>\r\n<\/figure>\r\n<p>\r\n\r\n\r\n\r\n<\/p>\r\n<p>&nbsp;<\/p>\r\n<p><\/p>\r\n<h3><strong>Conclusion<\/strong>\u00a0<\/h3>\r\n<p>Merci d&#039;avoir lu notre article et nous esp\u00e9rons qu&#039;il pourra vous aider \u00e0 mieux comprendre <strong>Lign\u00e9e de donn\u00e9es Amazon Redshift<\/strong>. Si vous souhaitez en savoir plus sur <strong>Lign\u00e9e de donn\u00e9es Amazon Redshift<\/strong>Nous vous conseillons de visiter notre site web. <a href=\"https:\/\/sqlflow.gudusoft.com\"><strong>Gudu SQLFlow<\/strong><\/a> Pour plus d&#039;informations. Gudu SQLFlow, en tant qu&#039;outil d&#039;analyse de la lign\u00e9e des donn\u00e9es, permet non seulement d&#039;analyser les fichiers de scripts SQL, d&#039;obtenir la lign\u00e9e des donn\u00e9es et de les visualiser, mais aussi de fournir cette lign\u00e9e au format CSV et de l&#039;afficher visuellement. Merci encore\u00a0! <strong>(Modifi\u00e9 par Ryan le 26 avril 2022)<\/strong><\/p>\r\n<p><\/p>","protected":false},"excerpt":{"rendered":"<p>Amazon Redshift Data Lineage | Gudu SQLFlow In your Amazon warehouse environment, use Amazon Redshift Spectrum to query data directly from files on Amazon S3, save data in Redshift databases, and use Business Intelligence tools such as Tableau, PowerBI, Looker, Qlik, Superset to generate reports from the data. The data originates from your business source system and lands on Amazon S3, then using an ETL tool such as DBT to transfer and store it in Redshift Database for later uses. In order to have an overview of the data flow in your Amazon warehouse system, you need a data lineage\u2026<\/p>","protected":false},"author":27,"featured_media":3583,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[14],"tags":[89,90,91,75,92],"blocksy_meta":{"styles_descriptor":{"styles":{"desktop":"","tablet":"","mobile":""},"google_fonts":[],"version":5}},"_links":{"self":[{"href":"https:\/\/www.gudusoft.com\/fr\/wp-json\/wp\/v2\/posts\/3554"}],"collection":[{"href":"https:\/\/www.gudusoft.com\/fr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.gudusoft.com\/fr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.gudusoft.com\/fr\/wp-json\/wp\/v2\/users\/27"}],"replies":[{"embeddable":true,"href":"https:\/\/www.gudusoft.com\/fr\/wp-json\/wp\/v2\/comments?post=3554"}],"version-history":[{"count":32,"href":"https:\/\/www.gudusoft.com\/fr\/wp-json\/wp\/v2\/posts\/3554\/revisions"}],"predecessor-version":[{"id":6616,"href":"https:\/\/www.gudusoft.com\/fr\/wp-json\/wp\/v2\/posts\/3554\/revisions\/6616"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.gudusoft.com\/fr\/wp-json\/wp\/v2\/media\/3583"}],"wp:attachment":[{"href":"https:\/\/www.gudusoft.com\/fr\/wp-json\/wp\/v2\/media?parent=3554"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.gudusoft.com\/fr\/wp-json\/wp\/v2\/categories?post=3554"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.gudusoft.com\/fr\/wp-json\/wp\/v2\/tags?post=3554"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}