{"id":6665,"date":"2025-09-08T07:00:48","date_gmt":"2025-09-08T07:00:48","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2025\/09\/08\/how_to_evaluate_data_transformations\/"},"modified":"2025-09-08T07:00:48","modified_gmt":"2025-09-08T07:00:48","slug":"how_to_evaluate_data_transformations","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2025\/09\/08\/how_to_evaluate_data_transformations\/","title":{"rendered":"How to evaluate data transformations?"},"content":{"rendered":"<p>    How to evaluate data transformations?<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>\n<!-- SC_OFF --><\/p>\n<div class=\"md\">\n<p>There are several well-established benchmarks for text-to-SQL tasks like BIRD, Spider, and WikiSQL. However, I&#8217;m working on a data transformation system that handles per-row transformations with contextual understanding of the input data.<\/p>\n<p>The challenge is that most existing benchmarks focus on either:<\/p>\n<ul>\n<li>Pure SQL generation (BIRD, Spider)<\/li>\n<li>Simple data cleaning tasks<\/li>\n<li>Basic ETL operations<\/li>\n<\/ul>\n<p>But what I&#8217;m looking for are benchmarks that test:<\/p>\n<ul>\n<li>Complex multi-step data transformations<\/li>\n<li>Context-aware operations (where the same instruction means different things based on data context)<\/li>\n<li>Cross-column reasoning and relationships<\/li>\n<li>Domain-specific transformations that require understanding the semantic meaning of data<\/li>\n<\/ul>\n<p>Has anyone come across benchmarks or datasets that test these more sophisticated data transformation capabilities?<\/p>\n<\/p><\/div>\n<p><!-- SC_ON -->   submitted by   <a href=\"https:\/\/www.reddit.com\/user\/metalvendetta\"> \/u\/metalvendetta <\/a> <br \/> <span><a href=\"https:\/\/www.reddit.com\/r\/datascience\/comments\/1nac35j\/how_to_evaluate_data_transformations\/\">[link]<\/a><\/span>   <span><a href=\"https:\/\/www.reddit.com\/r\/datascience\/comments\/1nac35j\/how_to_evaluate_data_transformations\/\">[comments]<\/a><\/span>\n<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><br \/>\n    \/u\/metalvendetta<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/www.reddit.com\/r\/datascience\/comments\/1nac35j\/how_to_evaluate_data_transformations\/\">Go to original source<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>How to evaluate data transformations? There are several well-established benchmarks for text-to-SQL tasks like BIRD, Spider, and WikiSQL. However, I&#8217;m working on a data transformation system that handles per-row transformations with contextual understanding of the input data. The challenge is that most existing benchmarks focus on either: Pure SQL generation (BIRD, Spider) Simple data cleaning [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[62,99],"tags":[1684,84,3722],"class_list":["post-6665","post","type-post","status-publish","format-standard","hentry","category-aimldsaimlds","category-datascience","tag-benchmarks","tag-data","tag-transformations"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/6665"}],"collection":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/comments?post=6665"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/6665\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=6665"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=6665"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=6665"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}