{"id":2943617,"date":"2025-11-05T13:30:48","date_gmt":"2025-11-05T21:30:48","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=2943617"},"modified":"2025-11-17T14:02:56","modified_gmt":"2025-11-17T22:02:56","slug":"best-practices-custom-data-creation","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/data-management\/best-practices-custom-data-creation","title":{"rendered":"Best practices for custom data creation and performance in ArcGIS Business Analyst Pro"},"author":78361,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[23851],"tags":[],"industry":[],"product":[36711,36561],"class_list":["post-2943617","blog","type-blog","status-publish","format-standard","hentry","category-data-management","product-bus-analyst","product-arcgis-pro"],"acf":{"authors":[{"ID":4101,"user_firstname":"Chris","user_lastname":"Distefano","nickname":"Chris Distefano","user_nicename":"onafetsid","display_name":"Chris Distefano","user_email":"cdistefano@esri.com","user_url":"","user_registered":"2018-03-02 00:15:41","user_description":"Chris is a Product Engineer on the Business Analyst team.","user_avatar":"<img alt='' src='https:\/\/secure.gravatar.com\/avatar\/3b2a0b6e4abee149984adf5414c25f63a24beccca4d1560be0b91a6b0d42cf36?s=96&#038;d=blank&#038;r=g' srcset='https:\/\/secure.gravatar.com\/avatar\/3b2a0b6e4abee149984adf5414c25f63a24beccca4d1560be0b91a6b0d42cf36?s=192&#038;d=blank&#038;r=g 2x' class='avatar avatar-96 photo' height='96' width='96' loading='lazy' decoding='async'\/>"},{"ID":78361,"user_firstname":"Gemma","user_lastname":"Goodale-Sussen","nickname":"Gemma Goodale-Sussen","user_nicename":"ggoodalesussen","display_name":"Gemma Goodale-Sussen","user_email":"ggoodalesussen@esri.com","user_url":"","user_registered":"2020-08-06 15:49:58","user_description":"Gemma is a writer at Esri, focusing on content for the ArcGIS Business Analyst team.","user_avatar":"<img data-del=\"avatar\" src='https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/08\/20180531_171833_2-e1596730690224-213x200.jpg' class='avatar pp-user-avatar avatar-96 photo ' height='96' width='96'\/>"}],"short_description":"Learn how to prepare, apportion, and manage large custom datasets for use in Business Analyst Pro.","flexible_content":[{"acf_fc_layout":"content","content":"<p>Many Business Analyst users take advantage of the <a href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/help\/analysis\/business-analyst\/custom-data.htm\" target=\"_blank\" rel=\"noopener\">custom data setup<\/a> workflow in ArcGIS Pro, which allows you to bring in data from outside the application and use it in analysis and reports. For example, the <a href=\"https:\/\/learn.arcgis.com\/en\/projects\/set-up-custom-data-for-infographics-in-arcgis-pro\/\" target=\"_blank\" rel=\"noopener\">Set up custom data for infographics in ArcGIS Pro<\/a> tutorial brings in <a href=\"https:\/\/hazards.fema.gov\/nri\/data-resources\" target=\"_blank\" rel=\"noopener\">National Risk Index data<\/a> from the Federal Emergency Management Agency (FEMA) as a statistical data collection, to evaluate climate risks in the state of California.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2943618,"id":2943618,"title":"Image 1 - screenshot from custom data lesson","filename":"Image-1-screenshot-from-custom-data-lesson.png","filesize":535579,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-1-screenshot-from-custom-data-lesson.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/data-management\/best-practices-custom-data-creation\/image-1-screenshot-from-custom-data-lesson","alt":"Tutorial results in Business Analyst Pro","author":"78361","description":"","caption":"","name":"image-1-screenshot-from-custom-data-lesson","status":"inherit","uploaded_to":2943617,"date":"2025-10-16 19:55:48","modified":"2025-10-16 19:56:04","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1224,"height":830,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-1-screenshot-from-custom-data-lesson-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-1-screenshot-from-custom-data-lesson.png","medium-width":385,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-1-screenshot-from-custom-data-lesson.png","medium_large-width":768,"medium_large-height":521,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-1-screenshot-from-custom-data-lesson.png","large-width":1224,"large-height":830,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-1-screenshot-from-custom-data-lesson.png","1536x1536-width":1224,"1536x1536-height":830,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-1-screenshot-from-custom-data-lesson.png","2048x2048-width":1224,"2048x2048-height":830,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-1-screenshot-from-custom-data-lesson-686x465.png","card_image-width":686,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-1-screenshot-from-custom-data-lesson.png","wide_image-width":1224,"wide_image-height":830}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p>When working with large geodatabases like FEMA\u2019s NRI data, which may contain hundreds of variables, creating a statistical data collection (also known as an SDCX) and generating analyses can be time-intensive due to index building and data processing. The best practices described in this article can optimize performance and streamline workflows.<\/p>\n"},{"acf_fc_layout":"sidebar","content":"<h4 style=\"text-align: center;\">Article contents<\/h4>\n<p style=\"text-align: center;\"><a href=\"#prefilter\">Prefilter fields in the input layer<\/a><\/p>\n<p style=\"text-align: center;\"><a href=\"#necessary-variables\">Select only necessary variables in the SDCX<\/a><\/p>\n<p style=\"text-align: center;\"><a href=\"#optimize-settings\">Optimize apportionment settings<\/a><\/p>\n<p style=\"text-align: center;\"><a href=\"#build-index\">Build and maintain the SDCX index<\/a><\/p>\n<p style=\"text-align: center;\"><a href=\"#hardware-storage\">Use efficient hardware and storage<\/a><\/p>\n<p style=\"text-align: center;\"><a href=\"#test-subset\">Test with a subset of the data first<\/a><\/p>\n<p style=\"text-align: center;\"><a href=\"#share-and-document\">Share and document<\/a><\/p>\n","image_reference":false,"layout":"standard","image_reference_figure":"","snippet":"","spotlight_name":"","section_title":"","position":"Center","spotlight_image":false},{"acf_fc_layout":"content","content":"<p>&nbsp;<\/p>\n<h2 id=\"prefilter\">Prefilter fields in the input layer<\/h2>\n<p>Did you know you\u2019re not obliged to use every single variable in a dataset? Many variables may not be relevant to your analysis, which can make editing the statistical data collection tedious, and slows down processing time when using the data. Use the following steps to winnow down the variables you\u2019re working with:<\/p>\n<ol>\n<li>Before creating the SDCX, add the source feature class\u2014for example, NRI_Counties, to a map in ArcGIS Pro.<\/li>\n<li>Right-click the layer in the <strong>Contents<\/strong> pane and select <strong>Data Design<\/strong> &gt; <strong>Fields<\/strong> to open the <strong>Fields <\/strong>view.<\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2943623,"id":2943623,"title":"Image 2 - opening Fields view","filename":"Image-2-opening-Fields-view.png","filesize":58121,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-2-opening-Fields-view.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/data-management\/best-practices-custom-data-creation\/image-2-opening-fields-view","alt":"Opening Fields view","author":"78361","description":"","caption":"","name":"image-2-opening-fields-view","status":"inherit","uploaded_to":2943617,"date":"2025-10-16 20:11:46","modified":"2025-10-16 20:11:54","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":608,"height":283,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-2-opening-Fields-view-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-2-opening-Fields-view.png","medium-width":464,"medium-height":216,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-2-opening-Fields-view.png","medium_large-width":608,"medium_large-height":283,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-2-opening-Fields-view.png","large-width":608,"large-height":283,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-2-opening-Fields-view.png","1536x1536-width":608,"1536x1536-height":283,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-2-opening-Fields-view.png","2048x2048-width":608,"2048x2048-height":283,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-2-opening-Fields-view.png","card_image-width":608,"card_image-height":283,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-2-opening-Fields-view.png","wide_image-width":608,"wide_image-height":283}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p>&nbsp;<\/p>\n<ol start=\"3\">\n<li>Uncheck the <strong>Visible<\/strong> check box for non-essential fields\u2014for example, OBJECTID, internal IDs, or irrelevant metrics, to exclude them from processing. Save your changes.<\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2943633,"id":2943633,"title":"Image 3_2 - Visible check boxes","filename":"Image-3_2-Visible-check-boxes.png","filesize":145912,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-3_2-Visible-check-boxes.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/data-management\/best-practices-custom-data-creation\/image-3_2-visible-check-boxes","alt":"Visible check boxes in Fields view","author":"78361","description":"","caption":"","name":"image-3_2-visible-check-boxes","status":"inherit","uploaded_to":2943617,"date":"2025-10-16 20:26:38","modified":"2025-10-16 20:26:44","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1248,"height":529,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-3_2-Visible-check-boxes-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-3_2-Visible-check-boxes.png","medium-width":464,"medium-height":197,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-3_2-Visible-check-boxes.png","medium_large-width":768,"medium_large-height":326,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-3_2-Visible-check-boxes.png","large-width":1248,"large-height":529,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-3_2-Visible-check-boxes.png","1536x1536-width":1248,"1536x1536-height":529,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-3_2-Visible-check-boxes.png","2048x2048-width":1248,"2048x2048-height":529,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-3_2-Visible-check-boxes-826x350.png","card_image-width":826,"card_image-height":350,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-3_2-Visible-check-boxes.png","wide_image-width":1248,"wide_image-height":529}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p>&nbsp;<\/p>\n<p>This reduces the number of variables loaded into the SDCX, significantly speeding up index creation and analysis.<\/p>\n<p>&nbsp;<\/p>\n<h2 id=\"necessary-variables\">Select only necessary variables in the SDCX<\/h2>\n<p>Sometimes, even with prefiltering, you wind up with more variables than you need for a particular analysis. Follow these steps to select only the variables pertinent to your work within an SDCX you&#8217;ve created:<\/p>\n<ol>\n<li>Browse to the SDCX in the <strong>Catalog<\/strong> pane, right-click it, and select <strong>Edit<\/strong>.<\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2943638,"id":2943638,"title":"Image 4 - Opening SDCX from Catalog pane","filename":"Image-4-Opening-SDCX-from-Catalog-pane.png","filesize":253662,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-4-Opening-SDCX-from-Catalog-pane.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/data-management\/best-practices-custom-data-creation\/image-4-opening-sdcx-from-catalog-pane","alt":"Opening SDCX from Catalog pane","author":"78361","description":"","caption":"","name":"image-4-opening-sdcx-from-catalog-pane","status":"inherit","uploaded_to":2943617,"date":"2025-10-16 20:41:38","modified":"2025-10-16 20:41:50","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":723,"height":623,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-4-Opening-SDCX-from-Catalog-pane-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-4-Opening-SDCX-from-Catalog-pane.png","medium-width":303,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-4-Opening-SDCX-from-Catalog-pane.png","medium_large-width":723,"medium_large-height":623,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-4-Opening-SDCX-from-Catalog-pane.png","large-width":723,"large-height":623,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-4-Opening-SDCX-from-Catalog-pane.png","1536x1536-width":723,"1536x1536-height":623,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-4-Opening-SDCX-from-Catalog-pane.png","2048x2048-width":723,"2048x2048-height":623,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-4-Opening-SDCX-from-Catalog-pane-540x465.png","card_image-width":540,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-4-Opening-SDCX-from-Catalog-pane.png","wide_image-width":723,"wide_image-height":623}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p>&nbsp;<\/p>\n<ol start=\"2\">\n<li>On the SDCX editor\u2019s <strong>Variables<\/strong> tab, use the <strong>Search<\/strong> box to filter and select only the variables needed for your analysis\u2014for example, you could search for risk variables associated only with the word &#8220;drought.&#8221;<\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2945648,"id":2945648,"title":"Image 5 - searching variables","filename":"Image-5-searching-variables.gif","filesize":923403,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-5-searching-variables.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/data-management\/best-practices-custom-data-creation\/image-5-searching-variables","alt":"Searching variables in SDCX","author":"78361","description":"","caption":"","name":"image-5-searching-variables","status":"inherit","uploaded_to":2943617,"date":"2025-10-27 20:07:08","modified":"2025-10-27 20:07:22","menu_order":0,"mime_type":"image\/gif","type":"image","subtype":"gif","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1212,"height":672,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-5-searching-variables-213x200.gif","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-5-searching-variables.gif","medium-width":464,"medium-height":257,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-5-searching-variables.gif","medium_large-width":768,"medium_large-height":426,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-5-searching-variables.gif","large-width":1212,"large-height":672,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-5-searching-variables.gif","1536x1536-width":1212,"1536x1536-height":672,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-5-searching-variables.gif","2048x2048-width":1212,"2048x2048-height":672,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-5-searching-variables-826x458.gif","card_image-width":826,"card_image-height":458,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-5-searching-variables.gif","wide_image-width":1212,"wide_image-height":672}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<ol start=\"3\">\n<li>Avoid including all variables by default. Use <strong>Ctrl+A<\/strong> to select all, uncheck to deselect, then check only essential fields to minimize processing overhead.<\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n<p>This narrows the variables down to just the ones you picked.<\/p>\n<p>&nbsp;<\/p>\n<h2 id=\"optimize-settings\">Optimize apportionment settings<\/h2>\n<p>Apportionment defines the calculations used for estimating amounts of a variable geographically. For example, you may have mapped custom data in neat little block group polygons\u2014but what if you then draw a drive-time area and want to know how much of a custom variable lies in that shape? Follow these guidelines for apportionment settings:<\/p>\n<ul>\n<li>Choose an appropriate <strong>Apportionment Method<\/strong> parameter\u2014for example, <strong>Population 2025<\/strong> apportionment for demographic data, or <strong>Land Area 2025<\/strong> apportionment for spatial metrics\u2014to align with your analysis goals. Incorrect methods can increase processing time and produce garbled, unhelpful results.<\/li>\n<\/ul>\n"},{"acf_fc_layout":"image","image":{"ID":2945660,"id":2945660,"title":"Image 6 - apportionment methods","filename":"Image-6-apportionment-methods.png","filesize":71610,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-6-apportionment-methods.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/data-management\/best-practices-custom-data-creation\/image-6-apportionment-methods","alt":"Choosing an apportionment method","author":"78361","description":"","caption":"","name":"image-6-apportionment-methods","status":"inherit","uploaded_to":2943617,"date":"2025-10-27 20:16:56","modified":"2025-10-27 20:17:08","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":420,"height":435,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-6-apportionment-methods-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-6-apportionment-methods.png","medium-width":252,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-6-apportionment-methods.png","medium_large-width":420,"medium_large-height":435,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-6-apportionment-methods.png","large-width":420,"large-height":435,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-6-apportionment-methods.png","1536x1536-width":420,"1536x1536-height":435,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-6-apportionment-methods.png","2048x2048-width":420,"2048x2048-height":435,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-6-apportionment-methods.png","card_image-width":420,"card_image-height":435,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-6-apportionment-methods.png","wide_image-width":420,"wide_image-height":435}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<ul>\n<li>Set <strong>Weight<\/strong> fields, such as <strong>POPULATION<\/strong>, only when necessary. Weighted calculations add computational load.<\/li>\n<\/ul>\n<p>For more information on data apportionment in Business Analyst Pro, visit <a href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/help\/analysis\/business-analyst\/data-apportionment-and-layers.htm\" target=\"_blank\" rel=\"noopener\">Understand data apportionment<\/a> in the product documentation.<\/p>\n<p>&nbsp;<\/p>\n<h2 id=\"build-index\">Build and maintain the SDCX index<\/h2>\n<p>An SDCX index improves the performance of your custom data in analyses. But it\u2019s not just a matter of clicking the <strong>Build Index<\/strong> button one time; there\u2019s more to it than that. Read on for guidelines:<\/p>\n<ul>\n<li>Always build the index after creating or modifying the SDCX to ensure optimal performance in tools like <a href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/help\/analysis\/business-analyst\/enrich-layer.htm\" target=\"_blank\" rel=\"noopener\">Enrich Layer<\/a>.<\/li>\n<\/ul>\n"},{"acf_fc_layout":"image","image":{"ID":2945674,"id":2945674,"title":"Image 7 - building index","filename":"Image-7-building-index.gif","filesize":81192,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-7-building-index.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/data-management\/best-practices-custom-data-creation\/image-7-building-index","alt":"SDCX performance index being built","author":"78361","description":"","caption":"","name":"image-7-building-index","status":"inherit","uploaded_to":2943617,"date":"2025-10-27 20:23:56","modified":"2025-10-27 20:24:09","menu_order":0,"mime_type":"image\/gif","type":"image","subtype":"gif","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":174,"height":120,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-7-building-index.gif","thumbnail-width":174,"thumbnail-height":120,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-7-building-index.gif","medium-width":174,"medium-height":120,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-7-building-index.gif","medium_large-width":174,"medium_large-height":120,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-7-building-index.gif","large-width":174,"large-height":120,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-7-building-index.gif","1536x1536-width":174,"1536x1536-height":120,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-7-building-index.gif","2048x2048-width":174,"2048x2048-height":120,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-7-building-index.gif","card_image-width":174,"card_image-height":120,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-7-building-index.gif","wide_image-width":174,"wide_image-height":120}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<ul>\n<li>If variables or apportionment methods change, rebuild the index to avoid performance degradation.<\/li>\n<\/ul>\n<p>Some users skip the important step of rebuilding the index. Don\u2019t be that user!<\/p>\n<p>&nbsp;<\/p>\n<h2 id=\"hardware-storage\">Use efficient hardware and storage<\/h2>\n<p>Custom data in Business Analyst Pro, like local datasets, exists in physical space and consequently relies on the quality of your hardware for optimal performance. Here are a couple of best practices:<\/p>\n<ul>\n<li>Store the input layer (GDB) and SDCX on a fast, local SSD to reduce read\/write times, especially for large datasets.<\/li>\n<li>Ensure your system has sufficient RAM\u2014for example, 16GB or more\u2014and a multi-core processor to handle processing hundreds of variables.<\/li>\n<\/ul>\n<p>It\u2019s not uncommon for users to store their data on external drives to provide plenty of space.<\/p>\n<p>&nbsp;<\/p>\n<h2 id=\"test-subset\">Test with a subset of the data first<\/h2>\n<p>Though they&#8217;re supremely useful, large datasets do require more energy from your computer to process. Keep the following in mind:<\/p>\n<ul>\n<li>For very large datasets, create a test SDCX with a small subset of variables or a smaller geographic area\u2014for example, a single state from the NRI data\u2014to verify settings before processing the full dataset.<\/li>\n<\/ul>\n"},{"acf_fc_layout":"image","image":{"ID":2945681,"id":2945681,"title":"Image 8 - data at different scales","filename":"Image-8-data-at-different-scales.png","filesize":751182,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-8-data-at-different-scales.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/data-management\/best-practices-custom-data-creation\/image-8-data-at-different-scales","alt":"Large amount of data versus smaller amount of data","author":"78361","description":"","caption":"","name":"image-8-data-at-different-scales","status":"inherit","uploaded_to":2943617,"date":"2025-10-27 20:39:08","modified":"2025-10-27 20:39:28","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1920,"height":662,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-8-data-at-different-scales-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-8-data-at-different-scales.png","medium-width":464,"medium-height":160,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-8-data-at-different-scales.png","medium_large-width":768,"medium_large-height":265,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-8-data-at-different-scales.png","large-width":1920,"large-height":662,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-8-data-at-different-scales-1536x530.png","1536x1536-width":1536,"1536x1536-height":530,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-8-data-at-different-scales.png","2048x2048-width":1920,"2048x2048-height":662,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-8-data-at-different-scales-826x285.png","card_image-width":826,"card_image-height":285,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-8-data-at-different-scales.png","wide_image-width":1920,"wide_image-height":662}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<ul>\n<li>Use the <a href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/tool-reference\/analysis\/clip.htm\" target=\"_blank\" rel=\"noopener\"><strong>Clip <\/strong>geoprocessing tool<\/a> to extract a subset of the data if needed.<\/li>\n<\/ul>\n<p>Have fun experimenting with the best visualizations and analyses of your data at different scales!<\/p>\n<p>&nbsp;<\/p>\n<h2 id=\"share-and-document\">Share and document<\/h2>\n<p>Once you&#8217;ve created custom data in Business Analyst Pro, you can save and <a href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/help\/analysis\/business-analyst\/sharing-custom-data.htm\" target=\"_blank\" rel=\"noopener\">share the statistical data collection<\/a> with other users in your organization. You can even use the data across products by sharing to your portal and then opening the data in Business Analyst Web App.<\/p>\n<ul>\n<li>When sharing the SDCX via ArcGIS Online or ArcGIS Enterprise, include clear metadata\u2014for example, <strong>Title<\/strong>, <strong>Tags<\/strong>, <strong>Description<\/strong>\u2014to help team members understand the dataset\u2019s scope and variables.<\/li>\n<\/ul>\n"},{"acf_fc_layout":"image","image":{"ID":2945683,"id":2945683,"title":"Image 9 - metadata","filename":"Image-9-metadata.png","filesize":22630,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-9-metadata.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/bus-analyst\/data-management\/best-practices-custom-data-creation\/image-9-metadata","alt":"Metadata fields in SDCX editor window","author":"78361","description":"","caption":"","name":"image-9-metadata","status":"inherit","uploaded_to":2943617,"date":"2025-10-27 20:43:16","modified":"2025-10-27 20:43:28","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1023,"height":587,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-9-metadata-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-9-metadata.png","medium-width":455,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-9-metadata.png","medium_large-width":768,"medium_large-height":441,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-9-metadata.png","large-width":1023,"large-height":587,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-9-metadata.png","1536x1536-width":1023,"1536x1536-height":587,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-9-metadata.png","2048x2048-width":1023,"2048x2048-height":587,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-9-metadata-810x465.png","card_image-width":810,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/Image-9-metadata.png","wide_image-width":1023,"wide_image-height":587}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<ul>\n<li>Document which fields were excluded in the <strong>Fields View<\/strong> to ensure reproducibility and transparency.<\/li>\n<\/ul>\n<p>To learn more about using your custom data in Business Analyst Web App, visit <a href=\"https:\/\/doc.arcgis.com\/en\/business-analyst\/web\/data-browser.htm#ESRI_SECTION1_D7E2956EB1434C6E827DB9947FE6A43C\" target=\"_blank\" rel=\"noopener\">Use custom and shared data<\/a>.<\/p>\n<p>&nbsp;<\/p>\n<h2>Resources<\/h2>\n<p>Now that you\u2019ve learned about custom data best practices in Business Analyst Pro, we hope you\u2019ll explore its use in all the analysis, mapping, and reporting capabilities the software has to offer. To continue your Business Analyst journey, visit the following resources:<\/p>\n<ul>\n<li><a href=\"https:\/\/www.esri.com\/en-us\/arcgis\/products\/arcgis-business-analyst\/overview\" target=\"_blank\" rel=\"noopener\">Business Analyst product overview page<\/a><\/li>\n<li><a href=\"https:\/\/www.esri.com\/en-us\/arcgis\/products\/arcgis-business-analyst\/buy\" target=\"_blank\" rel=\"noopener\">Review pricing and purchase Business Analyst<\/a><\/li>\n<li><a href=\"https:\/\/go.esri.com\/ba\/resources\" target=\"_blank\" rel=\"noopener\">Business Analyst resources page<\/a><\/li>\n<li><a href=\"https:\/\/go.esri.com\/ba\/linkedin\" target=\"_blank\" rel=\"noopener\">LinkedIn user group<\/a><\/li>\n<li><a href=\"https:\/\/mediaspace.esri.com\/channel\/ArcGIS%2BBusiness%2BAnalyst%2BWeb%2BApp\/238781273\" target=\"_blank\" rel=\"noopener\">Business Analyst Web App video channel<\/a><\/li>\n<li><a href=\"https:\/\/mediaspace.esri.com\/channel\/ArcGIS%2BBusiness%2BAnalyst%2BPro\/238781243\" target=\"_blank\" rel=\"noopener\">Business Analyst Pro video channel<\/a><\/li>\n<li><a href=\"https:\/\/community.esri.com\/groups\/business-analyst\" target=\"_blank\" rel=\"noopener\">Business Analyst on Esri Community<\/a><\/li>\n<li><a href=\"https:\/\/bao.arcgis.com\/esriBAO\/login\/\" target=\"_blank\" rel=\"noopener\">Business Analyst Web App login page<\/a><\/li>\n<li>Email the team:\u00a0<a href=\"mailto:businessanalyst@esri.com\" target=\"_blank\" rel=\"noopener\">businessanalyst@esri.com<\/a><\/li>\n<\/ul>\n"}],"related_articles":[{"ID":2889682,"post_author":"10262","post_date":"2025-07-15 07:40:31","post_date_gmt":"2025-07-15 14:40:31","post_content":"","post_title":"An introduction to custom data in ArcGIS Business Analyst Pro","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"introduction-to-custom-data-business-analyst-pro","to_ping":"","pinged":"","post_modified":"2025-07-28 16:02:39","post_modified_gmt":"2025-07-28 23:02:39","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=2889682","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":1991222,"post_author":"7181","post_date":"2023-06-22 11:53:27","post_date_gmt":"2023-06-22 18:53:27","post_content":"","post_title":"Best practices for using frequently changing geographies in Business Analyst custom data","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"best-practices-for-using-frequently-changing-geographies-in-business-analyst-custom-data","to_ping":"","pinged":"","post_modified":"2023-06-26 08:57:34","post_modified_gmt":"2023-06-26 15:57:34","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=1991222","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":2365682,"post_author":"78361","post_date":"2024-06-06 07:10:06","post_date_gmt":"2024-06-06 14:10:06","post_content":"","post_title":"An introduction to the new color-coded layers in ArcGIS Business Analyst Pro","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"color-coded-layers-arcgis-business-analyst-pro-3-3","to_ping":"","pinged":"","post_modified":"2024-06-06 07:18:38","post_modified_gmt":"2024-06-06 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13:24:14","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=2798812","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"4","filter":"raw"}],"show_article_image":false,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/10\/card-image-custom-data.png","wide_image":false},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.9 (Yoast SEO v25.9) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Best practices for custom data creation and performance in ArcGIS Business Analyst Pro<\/title>\n<meta name=\"description\" content=\"Learn how to prepare, apportion, and manage large custom datasets for use in Business Analyst Pro.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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