{"id":10250,"date":"2016-07-22T14:00:26","date_gmt":"2016-07-22T18:00:26","guid":{"rendered":"http:\/\/www.iri.com\/blog\/?p=10250"},"modified":"2017-11-03T14:50:36","modified_gmt":"2017-11-03T18:50:36","slug":"using-the-voracity-pivotunpivot-wizard","status":"publish","type":"post","link":"https:\/\/www.iri.com\/blog\/iri\/iri-workbench\/using-the-voracity-pivotunpivot-wizard\/","title":{"rendered":"Using the Voracity Pivot \/ Unpivot Wizard"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">A new wizard in the IRI Workbench <\/span><a href=\"http:\/\/www.iri.com\/products\/workbench\/voracity-gui\"><span style=\"font-weight: 400;\">GUI for Voracity<\/span><\/a><span style=\"font-weight: 400;\"> can <\/span><a href=\"http:\/\/www.iri.com\/solutions\/data-transformation\/pivot\"><span style=\"font-weight: 400;\">pivot or unpivot<\/span><\/a><span style=\"font-weight: 400;\"> relational data. A pivot transformation converts rows to columns and is helpful when dealing with denormalized tables. Unpivot converts columns to rows and can be used to create reports based on normalized tables. Because the wizard front-ends the CoSort <\/span><a href=\"http:\/\/www.iri.com\/products\/cosort\/sortcl\"><span style=\"font-weight: 400;\">SortCL<\/span><\/a><span style=\"font-weight: 400;\"> program in <\/span><a href=\"http:\/\/www.iri.com\/products\/voracity\"><span style=\"font-weight: 400;\">Voracity<\/span><\/a><span style=\"font-weight: 400;\">, it will also work on data in flat files and other ODBC <\/span><a href=\"http:\/\/www.iri.com\/products\/workbench\/data-sources\"><span style=\"font-weight: 400;\">sources<\/span><\/a><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In this example, the table YEAR_DEPT_AMT is denormalized because both the year and department have repeating data. I can use the Pivot Job wizard to pivot on either YEAR or DEPT depending on my desired output. A sample of the source data is shown below:<\/span><\/p>\n<p><a href=\"http:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/1-YEAR_DEPT_AMT.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-10262\" src=\"http:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/1-YEAR_DEPT_AMT.png\" alt=\"YEAR_DEPT_AMT\" width=\"409\" height=\"417\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/1-YEAR_DEPT_AMT.png 409w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/1-YEAR_DEPT_AMT-294x300.png 294w\" sizes=\"(max-width: 409px) 100vw, 409px\" \/><\/a><\/p>\n<h3><b>Pivot<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">When starting the wizard, I enter the name, location, and format of my output, and the pivot type. In this first run, I will leave Pivot selected. <\/span><\/p>\n<p><a href=\"http:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/2-New-Pivot-Job.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-10263\" src=\"http:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/2-New-Pivot-Job.png\" alt=\"New Pivot Job\" width=\"525\" height=\"522\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/2-New-Pivot-Job.png 525w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/2-New-Pivot-Job-150x150.png 150w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/2-New-Pivot-Job-300x298.png 300w\" sizes=\"(max-width: 525px) 100vw, 525px\" \/><\/a><\/p>\n<p><span style=\"font-weight: 400;\">On the second wizard page, I select the source, format, and metadata of my input data. In the drop-downs below this, I select the key (YEAR), which will be the field that I combine and sort my data on, the pivot (DEPT), which is the row that will become the column, and the values (AMT) field, which contains data that will be moved. <\/span><\/p>\n<p><a href=\"http:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/3-New-Pivot-Job-Data-Source.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-10265\" src=\"http:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/3-New-Pivot-Job-Data-Source.png\" alt=\"New Pivot Job-Data Source\" width=\"525\" height=\"522\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/3-New-Pivot-Job-Data-Source.png 525w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/3-New-Pivot-Job-Data-Source-150x150.png 150w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/3-New-Pivot-Job-Data-Source-300x298.png 300w\" sizes=\"(max-width: 525px) 100vw, 525px\" \/><\/a><\/p>\n<p><span style=\"font-weight: 400;\">Executing the script this wizard made produces the following output:<\/span><\/p>\n<p><a href=\"http:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/4-Pivot-out-script.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-10266\" src=\"http:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/4-Pivot-out-script.png\" alt=\"Pivot out script\" width=\"583\" height=\"178\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/4-Pivot-out-script.png 583w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/4-Pivot-out-script-300x92.png 300w\" sizes=\"(max-width: 583px) 100vw, 583px\" \/><\/a><\/p>\n<p><span style=\"font-weight: 400;\">The script also produced a header row from the name of the key field and the data in the pivot field so the user can clearly see how their data was reformatted. The YEAR and DEPT fields are no longer displayed repeatedly. The values have been moved to a grid format rather than a list.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">I could have, instead, chosen to pivot on the YEAR using DEPT as the key producing this output:<\/span><\/p>\n<p><a href=\"http:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/5-year.out_.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-10267\" src=\"http:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/5-year.out_.png\" alt=\"year.out\" width=\"654\" height=\"151\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/5-year.out_.png 654w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/5-year.out_-300x69.png 300w\" sizes=\"(max-width: 654px) 100vw, 654px\" \/><\/a><\/p>\n<h3><b>Unpivot<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">If I want to unpivot the above Pivot.out file, I first remove the header row so it does not become part of my data. Then, in the wizard, I select Unpivot as the transformation type in the setup screen. The second page will have different fields to fill out after entering the source options. <\/span><\/p>\n<p><a href=\"http:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/6-New-Pivot-Job-unpivot.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-10268\" src=\"http:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/6-New-Pivot-Job-unpivot.png\" alt=\"New Pivot Job-unpivot\" width=\"525\" height=\"522\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/6-New-Pivot-Job-unpivot.png 525w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/6-New-Pivot-Job-unpivot-150x150.png 150w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/6-New-Pivot-Job-unpivot-300x298.png 300w\" sizes=\"(max-width: 525px) 100vw, 525px\" \/><\/a><\/p>\n<p><span style=\"font-weight: 400;\">On this page, I select the key (YEAR), which is where the data will be expanded, and the pivot fields where the values reside. Using Unpivot will take the name of the metadata field and use it as the new data in the new column. Above, you can see that the metadata uses the names \u201cDEPT100\u201d, \u201cDEPT150\u201d, etc to define the fields.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Here is a sample of the unpivot results: <\/span><\/p>\n<p><a href=\"http:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/7-Unpivot.out_.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-10269\" src=\"http:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/7-Unpivot.out_.png\" alt=\"Unpivot.out\" width=\"278\" height=\"353\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/7-Unpivot.out_.png 278w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2016\/07\/7-Unpivot.out_-236x300.png 236w\" sizes=\"(max-width: 278px) 100vw, 278px\" \/><\/a><\/p>\n<p><span style=\"font-weight: 400;\">If I had named my fields \u201c100\u201d, \u201c150\u201d, etc., in the metadata file, I would have produced the same output as in the table shown at the beginning of this article.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The pivot options in this new wizard assist in either normalizing your tables or creating more concise reports. Using unpivot can expand your data, which is useful if you need to extract portions of it to feed it into different reports.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For more information on pivot and unpivot transformations, see <\/span><a href=\"http:\/\/www.iri.com\/blog\/data-transformation2\/pivoting-transformations\/\"><span style=\"font-weight: 400;\">this article<\/span><\/a><span style=\"font-weight: 400;\">. If you need help using the wizard, contact <\/span><a href=\"mailto:voracity@iri.com\"><span style=\"font-weight: 400;\">voracity@iri.com<\/span><\/a><span style=\"font-weight: 400;\">.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A new wizard in the IRI Workbench GUI for Voracity can pivot or unpivot relational data. A pivot transformation converts rows to columns and is helpful when dealing with denormalized tables. Unpivot converts columns to rows and can be used to create reports based on normalized tables. Because the wizard front-ends the CoSort SortCL program<\/p>\n<div><a class=\"btn-filled btn\" href=\"https:\/\/www.iri.com\/blog\/iri\/iri-workbench\/using-the-voracity-pivotunpivot-wizard\/\" title=\"Using the Voracity Pivot \/ Unpivot Wizard\">Read More<\/a><\/div>\n","protected":false},"author":43,"featured_media":10268,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"categories":[776,91],"tags":[632,1133,1093,546,789,221,1134,1132,75,1129,1131,1119,68,653,1130],"class_list":["post-10250","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-etl","category-iri-workbench","tag-data-source","tag-denormalized","tag-flow","tag-iri-cosort","tag-iri-voracity","tag-iri-workbench-gui","tag-job-specification-file","tag-normalized","tag-odbc","tag-pivot","tag-relational-data","tag-script","tag-sortcl","tag-tables","tag-unpivot"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v23.4 (Yoast SEO v23.4) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Using the Voracity Pivot \/ Unpivot Wizard - IRI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.iri.com\/blog\/iri\/iri-workbench\/using-the-voracity-pivotunpivot-wizard\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Using the Voracity Pivot \/ Unpivot Wizard\" \/>\n<meta property=\"og:description\" content=\"A new wizard in the IRI Workbench GUI for Voracity can pivot or unpivot relational data. A pivot transformation converts rows to columns and is helpful when dealing with denormalized tables. Unpivot converts columns to rows and can be used to create reports based on normalized tables. 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