{"id":1685432,"date":"2022-08-15T10:16:10","date_gmt":"2022-08-15T17:16:10","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=1685432"},"modified":"2022-09-21T22:21:42","modified_gmt":"2022-09-22T05:21:42","slug":"how-to-get-started-with-data-engineering","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/how-to-get-started-with-data-engineering","title":{"rendered":"How to get started with 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-1685432","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":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":""},{"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":""}],"short_description":"The first in our series of \"How to... in Data Engineering\" articles introduces you to the Data Engineering view.","flexible_content":[{"acf_fc_layout":"content","content":"

We all work with data. Whether our roles have \u201cGIS\u201d, \u201ccartographer\u201d, \u201canalyst\u201d, \u201cdata scientist\u201d, or \u201cdeveloper\u201d in the name, data is likely fundamental to what we do.<\/p>\n

And while we often see examples of work that has perfectly curated data ready to be beautifully mapped, intricately analyzed, or turned into the perfect app, the truth is that there\u2019s a messy part of our jobs that takes the most time: Exploring and preparing the data.<\/p>\n

So\u2026 what if instead of hiding this messy part of our jobs, we highlighted it, made more tools for it, and made it productive and more fun?<\/p>\n

Introducing the Data Engineering view in ArcGIS Pro. An experience that makes exploration and preparation of your data much more productive and intuitive. It is a view that focuses on the fields in your data, giving options to see data quality metrics and see information about the attributes you\u2019re working with. The following video shows you how to get started:<\/p>\n"},{"acf_fc_layout":"kaltura","video_id":"1_tr5o5c5w","time":false,"start":0,"stop":""},{"acf_fc_layout":"content","content":"

 <\/p>\n

There\u2019s also a ribbon that provides easy access to geoprocessing tools in four categories: clean, construct, integrate, and format.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1685512,"id":1685512,"title":"ribbon","filename":"ribbon.png","filesize":15632,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/08\/ribbon.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/how-to-get-started-with-data-engineering\/ribbon-5","alt":"Data Engineering ribbon","author":"7101","description":"","caption":"","name":"ribbon-5","status":"inherit","uploaded_to":1685432,"date":"2022-08-15 16:20:31","modified":"2022-08-15 16:20:42","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":600,"height":108,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/08\/ribbon-213x108.png","thumbnail-width":213,"thumbnail-height":108,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/08\/ribbon.png","medium-width":464,"medium-height":84,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/08\/ribbon.png","medium_large-width":600,"medium_large-height":108,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/08\/ribbon.png","large-width":600,"large-height":108,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/08\/ribbon.png","1536x1536-width":600,"1536x1536-height":108,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/08\/ribbon.png","2048x2048-width":600,"2048x2048-height":108,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/08\/ribbon.png","card_image-width":600,"card_image-height":108,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/08\/ribbon.png","wide_image-width":600,"wide_image-height":108}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

It\u2019s for every GIS user.<\/h2>\n

The data engineering view is not just for experienced data scientists: anyone that needs to work with data in ArcGIS Pro can use it. We designed it to work well in conjunction with your attribute table, fields view, and map views.<\/p>\n

No additional licenses required.<\/h2>\n

You can access it in ArcGIS Pro 2.8 or later; no additional licenses required.<\/p>\n

What\u2019s next? A season of content.<\/h2>\n

Over the next few months, you\u2019ll see a variety of videos and blog posts that will help you learn how to improve your data exploration and preparation workflows in the Data Engineering View. We hope you enjoy and learn a lot with us. Stay tuned for our next video!<\/p>\n

View more resources about how to use Data Engineering<\/a><\/p>\n

 <\/p>\n"},{"acf_fc_layout":"sidebar","content":"

Check out the other articles in our Data Engineering how to series:<\/strong><\/p>\n

    \n
  1. How to get started<\/a><\/li>\n
  2. How to explore fields<\/a><\/li>\n
  3. How to convert field types<\/a><\/li>\n
  4. How to join data<\/a><\/li>\n
  5. How to work with numeric data<\/a><\/li>\n
  6. How to work with text data<\/a><\/li>\n
  7. How to work with date data<\/a><\/li>\n
  8. How to work with missing data (coming soon)<\/li>\n<\/ol>\n

    \u2026and more to follow<\/p>\n","image_reference":false,"layout":"standard","image_reference_figure":"","snippet":"","spotlight_name":"","section_title":"","position":"Center","spotlight_image":false}],"related_articles":[{"ID":1685192,"post_author":"9862","post_date":"2022-08-15 11:16:03","post_date_gmt":"2022-08-15 18:16:03","post_content":"","post_title":"How to explore fields with Data Engineering","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"how-to-explore-fields-with-data-engineering","to_ping":"","pinged":"","post_modified":"2024-11-27 13:48:52","post_modified_gmt":"2024-11-27 21:48:52","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=1685192","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":1186302,"post_author":"207622","post_date":"2021-04-07 09:09:30","post_date_gmt":"2021-04-07 16:09:30","post_content":"","post_title":"Dev Summit 2021: Data Engineering in ArcGIS Pro","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"data-engineering-in-arcgis-pro","to_ping":"","pinged":"","post_modified":"2021-08-20 15:19:13","post_modified_gmt":"2021-08-20 22:19:13","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=1186302","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":1235582,"post_author":"10232","post_date":"2021-05-20 09:38:34","post_date_gmt":"2021-05-20 16:38:34","post_content":"","post_title":"Introducing Data Engineering in ArcGIS Pro","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"introducing-data-engineering-in-arcgis-pro","to_ping":"","pinged":"","post_modified":"2022-03-30 15:09:05","post_modified_gmt":"2022-03-30 22:09:05","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=1235582","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"1","filter":"raw"},{"ID":1285422,"post_author":"9862","post_date":"2021-07-07 11:32:39","post_date_gmt":"2021-07-07 18:32:39","post_content":"","post_title":"What\u2019s new for Spatial Statistics in ArcGIS Pro 2.8? Data Engineering and more!","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"whats-new-for-spatial-statistics-in-arcgis-pro-2-8-data-engineering-and-more","to_ping":"","pinged":"","post_modified":"2021-07-10 09:59:47","post_modified_gmt":"2021-07-10 16:59:47","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=1285422","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"}],"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/08\/DE_card_826x465_v3.png","wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/08\/DE_banner_1920x1080_v6.png"},"yoast_head":"\nHow to get started with Data Engineering<\/title>\n<meta name=\"description\" content=\"Get started with the Data Engineering in ArcGIS Pro: an experience that makes exploration and preparation of your data productive and intuitive.\" 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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.","sameAs":["https:\/\/esriurl.com\/spatialstats","https:\/\/www.linkedin.com\/in\/alberto-nieto-56ab6a39\/"],"url":"https:\/\/www.esri.com\/arcgis-blog\/author\/albe9057esri-com_esrifederal"}]}},"text_date":"August 15, 2022","author_name":"Multiple Authors","author_page":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/how-to-get-started-with-data-engineering","custom_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2022\/08\/DE_banner_1920x1080_v6.png","primary_product":"ArcGIS Pro","tag_data":[{"term_id":24311,"name":"Analysis","slug":"analysis","term_group":0,"term_taxonomy_id":24311,"taxonomy":"post_tag","description":"","parent":0,"count":96,"filter":"raw"},{"term_id":760452,"name":"Data Engineering","slug":"data-engineering","term_group":0,"term_taxonomy_id":760452,"taxonomy":"post_tag","description":"","parent":0,"count":34,"filter":"raw"},{"term_id":31601,"name":"Data Science","slug":"data-science","term_group":0,"term_taxonomy_id":31601,"taxonomy":"post_tag","description":"","parent":0,"count":46,"filter":"raw"},{"term_id":35661,"name":"machine learning","slug":"machine-learning","term_group":0,"term_taxonomy_id":35661,"taxonomy":"post_tag","description":"","parent":0,"count":41,"filter":"raw"},{"term_id":25581,"name":"spatial statistics","slug":"spatial-statistics","term_group":0,"term_taxonomy_id":25581,"taxonomy":"post_tag","description":"","parent":0,"count":128,"filter":"raw"}],"category_data":[{"term_id":23341,"name":"Analytics","slug":"analytics","term_group":0,"term_taxonomy_id":23341,"taxonomy":"category","description":"","parent":0,"count":1328,"filter":"raw"}],"product_data":[{"term_id":36561,"name":"ArcGIS Pro","slug":"arcgis-pro","term_group":0,"term_taxonomy_id":36561,"taxonomy":"product","description":"","parent":0,"count":2036,"filter":"raw"}],"primary_product_link":"https:\/\/www.esri.com\/arcgis-blog\/?s=#&products=arcgis-pro","_links":{"self":[{"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/blog\/1685432","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/blog"}],"about":[{"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/types\/blog"}],"author":[{"embeddable":true,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/users\/7101"}],"replies":[{"embeddable":true,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/comments?post=1685432"}],"version-history":[{"count":0,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/blog\/1685432\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/media?parent=1685432"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/categories?post=1685432"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/tags?post=1685432"},{"taxonomy":"industry","embeddable":true,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/industry?post=1685432"},{"taxonomy":"product","embeddable":true,"href":"https:\/\/www.esri.com\/arcgis-blog\/wp-json\/wp\/v2\/product?post=1685432"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}