{"id":79,"date":"2023-11-06T17:42:31","date_gmt":"2023-11-06T17:42:31","guid":{"rendered":"https:\/\/blog.dataplatform.lt\/?p=79"},"modified":"2023-11-06T17:42:31","modified_gmt":"2023-11-06T17:42:31","slug":"keep-original-data","status":"publish","type":"post","link":"https:\/\/blog.dataplatform.lt\/?p=79","title":{"rendered":"Keep original data"},"content":{"rendered":"\n<p>In case you need to normalize data, write multiple pipelines: first, the one which scrapes original data unformatted. Then write extra pipeline which normalizes data from previous pipeline.&nbsp;<\/p>\n\n\n\n<p>This way you can always fix problems ar adjust normalization for older datasets (no data is lost)<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In case you need to normalize data, write multiple pipelines: first, the one which scrapes original data unformatted. Then write extra pipeline which normalizes data from previous pipeline.&nbsp; This way you can always fix problems ar adjust normalization for older datasets (no data is lost)<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-79","post","type-post","status-publish","format-standard","hentry","category-patterns-and-best-practises"],"_links":{"self":[{"href":"https:\/\/blog.dataplatform.lt\/index.php?rest_route=\/wp\/v2\/posts\/79","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blog.dataplatform.lt\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.dataplatform.lt\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.dataplatform.lt\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.dataplatform.lt\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=79"}],"version-history":[{"count":1,"href":"https:\/\/blog.dataplatform.lt\/index.php?rest_route=\/wp\/v2\/posts\/79\/revisions"}],"predecessor-version":[{"id":80,"href":"https:\/\/blog.dataplatform.lt\/index.php?rest_route=\/wp\/v2\/posts\/79\/revisions\/80"}],"wp:attachment":[{"href":"https:\/\/blog.dataplatform.lt\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=79"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.dataplatform.lt\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=79"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.dataplatform.lt\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=79"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}