{"id":1711942,"date":"2022-09-14T11:02:24","date_gmt":"2022-09-14T18:02:24","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=1711942"},"modified":"2022-09-21T22:21:30","modified_gmt":"2022-09-22T05:21:30","slug":"how-to-work-with-text-fields-in-data-engineering","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/how-to-work-with-text-fields-in-data-engineering","title":{"rendered":"How to work with text fields in Data Engineering"},"author":7101,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[23341],"tags":[24311,760452,31601,35661,25581],"industry":[],"product":[36561],"class_list":["post-1711942","blog","type-blog","status-publish","format-standard","hentry","category-analytics","tag-analysis","tag-data-engineering","tag-data-science","tag-machine-learning","tag-spatial-statistics","product-arcgis-pro"],"acf":{"authors":[{"ID":7101,"user_firstname":"Alberto","user_lastname":"Nieto","nickname":"Alberto Nieto","user_nicename":"albe9057esri-com_esrifederal","display_name":"Alberto Nieto","user_email":"ANieto@esri.com","user_url":"https:\/\/esriurl.com\/spatialstats","user_registered":"2018-03-02 00:19:18","user_description":"Alberto Nieto is a Product Engineer on Esri\u2019s Spatial Statistics team. In his role, he helps research, build, and maintain spatial data science capabilities in ArcGIS and works closely with government agencies to learn about the problems our software can help solve. Alberto\u2019s background includes fourteen years of experience, including previous roles as a GIS Developer at Capital One and NOAA's Climate Prediction Center, and as a GIS Analyst at the Census Bureau and the Alachua County Environmental Protection Department.","user_avatar":""},{"ID":10232,"user_firstname":"Lynne","user_lastname":"Buie","nickname":"Lynne Buie","user_nicename":"lbuie","display_name":"Lynne Buie","user_email":"lbuie@esri.com","user_url":"http:\/\/esriurl.com\/spatialstats","user_registered":"2019-11-22 19:46:25","user_description":"Lynne Buie is a Product Engineer on the Spatial Statistics team. She helps build spatial statistics tools and Data Engineering capabilities for ArcGIS Pro. She's passionate about using GIS to help make the world a better place.","user_avatar":""},{"ID":9862,"user_firstname":"Ankita","user_lastname":"Bakshi","nickname":"Ankita Bakshi","user_nicename":"abakshi","display_name":"Ankita Bakshi","user_email":"ABakshi@esri.com","user_url":"https:\/\/spatialstats.github.io\/","user_registered":"2019-08-13 18:45:44","user_description":"Ankita Bakshi is a Product Owner and a Senior Product Engineer on the Spatial Statistics Team at Esri. With a background in environmental engineering and computer science, she is passionate about solving social, economic, and environmental problems with Spatial Analysis and Data Science. In her role, Ankita enjoys researching, finding solutions to build software, and loves creating video and written content to make the software tools more approachable and applicable to real world challenges. Outside of work Ankita enjoys going on hikes and dancing to Bollywood music.","user_avatar":""}],"short_description":"Text fields... useful information in our data but sometimes gloriously messy and chaotic. Let's work with them in Data Engineering!","flexible_content":[{"acf_fc_layout":"content","content":"

Text fields. They often hold some of the most important information in our data; whether a text field contains addresses that kick off our spatial adventures with a dataset, or they hold unique IDs that make joins (and bringing even more data) possible, they are certainly some of the most important data we work with as analysts and GIS professionals.<\/p>\n

But text fields can also be some of the peskiest to work with: in some cases, they arrive in gloriously unstructured form, unleashing trains of thought from a survey form\u2019s open text entry. In others, they look like unique IDs until a join acts unexpectedly and you realize the field has no right to be used in a join. We can typically work around these problems and get through the needed data wrangling, but we can all use a little help and make the experience more enjoyable.<\/p>\n

In this blog and short video, we\u2019ll introduce how Data Engineering in ArcGIS Pro<\/a> helps you explore and prepare data with text fields. We\u2019ll introduce some of the key things you can do, including:<\/p>\n