{"id":15841,"date":"2021-11-23T00:00:00","date_gmt":"2021-11-23T00:00:00","guid":{"rendered":"https:\/\/members.dataiq.global\/report\/dataiq100-using-data-for-good\/"},"modified":"2024-05-30T16:23:28","modified_gmt":"2024-05-30T15:23:28","slug":"dataiq100-using-data-for-good","status":"publish","type":"report","link":"https:\/\/www.dataiq.global\/devstage\/report\/dataiq100-using-data-for-good\/","title":{"rendered":"Using data for good"},"content":{"rendered":"<p>Data has been integral to the successful navigation of the turbulence brought about by the pandemic, both at a national and a business level. As we slowly head out of the pandemic, data practitioners are considering how best to use their skills to shape a positive new normal.<\/p>\n<p>Earlier this year we asked the DataIQ 100 to share their approach towards data for good, and the philanthropic initiatives they are planning to embark on in the near future.<\/p>\n<p>Download this eBook by DataIQ and Tableau to explore:<\/p>\n<ul>\n<li>Key insights from industry leaders including JLL, Zurich Insurance, Unilever, Pets at Home, GSK and NHS England on how their organisations are using data for good<\/li>\n<li>Tableau explores case studies from organisations using data to drive measurable, positive impact in society<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Earlier this year we asked the DataIQ 100 to share their approach towards data for good, and the philanthropic initiatives they are planning to embark on in the near future.<\/p>\n","protected":false},"author":3,"featured_media":15842,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","_searchwp_excluded":"","footnotes":""},"categories":[129,133],"tags":[173,752,85],"pillar":[],"class_list":["post-15841","report","type-report","status-publish","format-standard","has-post-thumbnail","hentry","category-editorial","category-reports","tag-data-management","tag-market-insight","tag-strategy"],"acf":[],"publishpress_future_action":{"enabled":false,"date":"2026-05-21 03:46:45","action":"change-status","newStatus":"draft","terms":[],"taxonomy":"category","extraData":[]},"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/report\/15841","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/report"}],"about":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/types\/report"}],"author":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/comments?post=15841"}],"version-history":[{"count":0,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/report\/15841\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media\/15842"}],"wp:attachment":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media?parent=15841"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/categories?post=15841"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/tags?post=15841"},{"taxonomy":"pillar","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/pillar?post=15841"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}