{"id":1173479,"date":"2026-05-28T09:00:00","date_gmt":"2026-05-28T16:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?p=1173479"},"modified":"2026-05-28T06:46:16","modified_gmt":"2026-05-28T13:46:16","slug":"data-formulator-0-7-ai-powered-data-analytics-for-enterprise-data","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/en-us\/research\/blog\/data-formulator-0-7-ai-powered-data-analytics-for-enterprise-data\/","title":{"rendered":"Data Formulator 0.7: AI-powered data analytics for enterprise data"},"content":{"rendered":"\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"2560\" height=\"1441\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-scaled.jpg\" alt=\"Three minimalist white line icons on a textured blue\u2011green gradient background: a rising bar chart on the left, a central hub\u2011and\u2011spoke network diagram in the middle, and a checkmark inside a circle on the right.\" class=\"wp-image-1173551\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-scaled.jpg 2560w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-300x169.jpg 300w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-1024x576.jpg 1024w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-768x432.jpg 768w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-1536x865.jpg 1536w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-2048x1153.jpg 2048w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-1066x600.jpg 1066w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-655x368.jpg 655w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-240x135.jpg 240w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-640x360.jpg 640w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-960x540.jpg 960w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-1280x720.jpg 1280w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-1920x1080.jpg 1920w\" sizes=\"auto, (max-width: 2560px) 100vw, 2560px\" \/><\/figure>\n\n\n\n<div style=\"padding-bottom:0; padding-top:0\" class=\"wp-block-msr-immersive-section alignfull row wp-block-msr-immersive-section\">\n\t\n\t<div class=\"container\">\n\t\t<div class=\"wp-block-msr-immersive-section__inner wp-block-msr-immersive-section__inner--narrow\">\n\t\t\t<div class=\"wp-block-columns mb-10 pb-1 pr-1 is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\" style=\"box-shadow:var(--wp--preset--shadow--outlined)\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\">\n<h2 class=\"wp-block-heading h3\" id=\"at-a-glance\">At a glance<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Data Formulator 0.7 is an open-source AI-powered system for enterprise data analytics that combines data connectivity, agent-guided exploration, and visualization refinement in a shared workspace.<\/li>\n\n\n\n<li>It includes a Data Connectors feature, which supports governed, reusable connections across databases, warehouses, BI systems, object stores, and local files, reducing integration work for platform teams.<\/li>\n\n\n\n<li>Context-aware agents help users prepare data, explore analyses, generate visualizations, and navigate long-running and branching analytical workflows.<\/li>\n\n\n\n<li>An interactive, multimodal interface allows teams to iteratively explore and refine analyses across fragmented data sources, with no SQL or programming expertise required.<\/li>\n<\/ul>\n<\/div>\n<\/div>\t\t<\/div>\n\t<\/div>\n\n\t<\/div>\n\n\n\n<p>Enterprise teams increasingly rely on AI systems for analytics, but enterprise data workflows are often fragmented across storage systems and tools. Before analysis can begin, teams often need to establish governed connections, prepare metadata, manage permissions, and build workflows for combining and reshaping data across multiple systems.<\/p>\n\n\n\n<p>Beyond data connection, analysis itself remains challenging for analysts and domain experts, many of whom lack deep coding expertise. They frequently need to compute new metrics, compare different ways of organizing data, inspect intermediate outputs, and refine visualizations as needs evolve. These workflows are difficult to reproduce inside isolated chat interactions that lack persistent access to enterprise data, workflow history, and visualization context.<\/p>\n\n\n\n<p>Our new release, <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/github.com\/microsoft\/data-formulator\" target=\"_blank\" rel=\"noopener noreferrer\">Data Formulator 0.7<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>, is designed to address these challenges. It is an open-source AI-powered data analysis system that connects fragmented enterprise data and iterative analytical workflows. It provides a lightweight way to connect across a variety of data sources, context-aware agents that assist with data preparation, exploration, and visualization, and an interactive workspace where users can iteratively refine and share their analyses.<\/p>\n\n\n\n\t<div class=\"border-bottom border-top border-gray-300 mt-5 mb-5 msr-promo text-center text-md-left alignwide\" data-bi-aN=\"promo\" data-bi-id=\"670821\">\n\t\t\n\n\t\t<p class=\"msr-promo__label text-gray-800 text-center text-uppercase\">\n\t\t<span class=\"px-4 bg-white display-inline-block font-weight-semibold small\">Spotlight: Microsoft research newsletter<\/span>\n\t<\/p>\n\t\n\t<div class=\"row pt-3 pb-4 align-items-center\">\n\t\t\t\t\t\t<div class=\"msr-promo__media col-12 col-md-5\">\n\t\t\t\t<a class=\"bg-gray-300 display-block\" href=\"https:\/\/info.microsoft.com\/ww-landing-microsoft-research-newsletter.html\" aria-label=\"Microsoft Research Newsletter\" data-bi-cN=\"Microsoft Research Newsletter\" target=\"_blank\">\n\t\t\t\t\t<img decoding=\"async\" class=\"w-100 display-block\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2019\/09\/Newsletter_Banner_08_2019_v1_1920x1080.png\" alt=\"\" \/>\n\t\t\t\t<\/a>\n\t\t\t<\/div>\n\t\t\t\n\t\t\t<div class=\"msr-promo__content p-3 px-5 col-12 col-md\">\n\n\t\t\t\t\t\t\t\t\t<h2 class=\"h4\">Microsoft Research Newsletter<\/h2>\n\t\t\t\t\n\t\t\t\t\t\t\t\t<p id=\"microsoft-research-newsletter\" class=\"large\">Stay connected to the research community at Microsoft.<\/p>\n\t\t\t\t\n\t\t\t\t\t\t\t\t<div class=\"wp-block-buttons justify-content-center justify-content-md-start\">\n\t\t\t\t\t<div class=\"wp-block-button is-style-fill-chevron\">\n\t\t\t\t\t\t<a href=\"https:\/\/info.microsoft.com\/ww-landing-microsoft-research-newsletter.html\" aria-describedby=\"microsoft-research-newsletter\" class=\"btn btn-brand glyph-append glyph-append-chevron-right\" data-bi-cN=\"Microsoft Research Newsletter\" target=\"_blank\">\n\t\t\t\t\t\t\tSubscribe today\t\t\t\t\t\t<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div><!--\/.msr-promo__content-->\n\t<\/div><!--\/.msr-promo__inner-wrap-->\n\t<\/div><!--\/.msr-promo-->\n\t\n\n\n<h2 class=\"wp-block-heading\" id=\"connecting-enterprise-data-with-data-connectors\">Connecting enterprise data with Data Connectors<\/h2>\n\n\n\n<p>Data Formulator helps teams bring enterprise data into an AI-ready workspace without\u00a0needing to\u00a0rebuild\u00a0the same connections\u00a0for every source\u00a0of data.\u00a0The\u00a0Data Connectors\u00a0feature\u00a0supports\u00a0authentication, persistent connections, previews, metadata, and a unified workspace model across databases, warehouses, BI systems, object stores, and local files.\u00a0This\u00a0reduces\u00a0integration\u00a0work for platform teams and\u00a0allows\u00a0users\u00a0to\u00a0work from centrally managed,\u00a0reusable\u00a0data\u00a0connections\u00a0rather than\u00a0relying on repeated manual file\u00a0uploads, as\u00a0shown in Figure\u00a01.\u00a0<\/p>\n\n\n\n<figure class=\"wp-block-image aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"2560\" height=\"1059\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-1_New-scaled.jpg\" alt=\"Figure 1. Data Connectors provide persistent connections between enterprise data sources and Data Formulator, allowing analysts and AI agents to load, query, and visualize shared data.\" class=\"wp-image-1173869\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-1_New-scaled.jpg 2560w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-1_New-300x124.jpg 300w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-1_New-1024x424.jpg 1024w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-1_New-768x318.jpg 768w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-1_New-1536x636.jpg 1536w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-1_New-2048x848.jpg 2048w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-1_New-240x99.jpg 240w\" sizes=\"auto, (max-width: 2560px) 100vw, 2560px\" \/><figcaption class=\"wp-element-caption\">Figure 1. Data Connectors provide persistent connections between enterprise data sources and Data Formulator, allowing analysts and AI agents to load, query, and visualize shared data.<\/figcaption><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"context-aware-agents-for-data-analysis\">Context-aware agents for data analysis<\/h2>\n\n\n\n<p>Context-aware AI agents form the core of Data Formulator. Unlike a single prompt, Data Formulator gives agents access to the full analysis workspace, including connected data sources, loaded tables, prior charts, and the user&#8217;s objective. Agents reason and act through tools rather than text alone. In a single interaction, an agent can inspect data, write and run code in an isolated environment, generate chart specifications, and explain its results while showing intermediate steps.<\/p>\n\n\n\n<p>When a request is ambiguous, the agent asks clarifying questions before proceeding. This allows agents to carry out more complex analytical workflows: aligning analyses with the user&#8217;s goal, preparing and transforming data, suggesting follow-up questions, generating tables and charts in batch, and creating verifiable, reproducible code for every result.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"a-workspace-for-iterative-data-analysis\">A workspace for iterative data analysis<\/h2>\n\n\n\n<p>Data Formulator pairs these agents with a multimodal interface designed for open-ended analysis workflows. Users work with agents through the Data Thread, a structured chat that records every question, intermediate finding, and chart throughout the analysis process. Long sessions stay navigable: users can revisit earlier steps, branch into alternative analyses, and compare them side by side without losing context.<\/p>\n\n\n\n<p>As illustrated in Figure 2, the interactive canvas complements Data Thread by allowing users to directly edit visualizations. When users shift from exploration to communication, they can refine charts directly on the canvas or describe changes in natural language and let the agent adjust labels, annotations, layout, color, and emphasis. Analysts can also generate reports and share their findings with others.<\/p>\n\n\n\n<figure class=\"wp-block-image aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"2560\" height=\"1440\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-2-scaled.png\" alt=\"Figure 2. (Left) Data Thread allows users to interact with AI agents by asking questions, requesting data visualizations, and exploring follow-up analyses. Threads preserve the history of long analysis sessions, making it possible to revisit, reuse, and build on earlier work. (Right) The interactive canvas allows users to refine visualizations directly by adjusting settings, redesigning charts, and inspecting the underlying data and code side by side.\" class=\"wp-image-1173492\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-2-scaled.png 2560w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-2-300x169.png 300w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-2-1024x576.png 1024w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-2-768x432.png 768w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-2-1536x864.png 1536w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-2-2048x1152.png 2048w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-2-1066x600.png 1066w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-2-655x368.png 655w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-2-240x135.png 240w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-2-640x360.png 640w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-2-960x540.png 960w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-2-1280x720.png 1280w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/df-blog-figure-2-1920x1080.png 1920w\" sizes=\"auto, (max-width: 2560px) 100vw, 2560px\" \/><figcaption class=\"wp-element-caption\">Figure 2. (Left) Data Thread allows users to interact with AI agents by asking questions, requesting data visualizations, and exploring follow-up analyses. Threads preserve the history of long analysis sessions, making it possible to revisit, reuse, and build on earlier work. (Right) The interactive canvas allows users to refine visualizations directly by adjusting settings, redesigning charts, and inspecting the underlying data and code side by side.<\/figcaption><\/figure>\n\n\n\n<p>View the Data Formulator demo <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/data-formulator.ai\" target=\"_blank\" rel=\"noopener noreferrer\">here<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>, or explore the Data Formulator <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/github.com\/microsoft\/data-formulator\" target=\"_blank\" rel=\"noopener noreferrer\">GitHub repository<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>. Teams developing analytics workflows for enterprise data can use the project as a foundation for adapting these capabilities to their own systems and requirements.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Data Formulator introduces AI-powered analytics for enterprise data workflows. Data teams can easily bring enterprise data into an AI-ready workspace where users can explore, analyze, and visualize data with AI agents to turn raw data into actionable insights.<\/p>\n","protected":false},"author":44124,"featured_media":1173551,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":[{"type":"user_nicename","value":"Chenglong Wang","user_id":"41251"},{"type":"user_nicename","value":"Scott Tsukamaki","user_id":"44167"},{"type":"user_nicename","value":"Michel Galley","user_id":"32887"},{"type":"user_nicename","value":"Jianfeng Gao","user_id":"32246"}],"msr_hide_image_in_river":0,"footnotes":""},"categories":[1],"tags":[],"research-area":[13556,13554],"msr-region":[],"msr-event-type":[],"msr-locale":[268875],"msr-post-option":[243984],"msr-impact-theme":[],"msr-promo-type":[],"msr-podcast-series":[],"class_list":["post-1173479","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-research-blog","msr-research-area-artificial-intelligence","msr-research-area-human-computer-interaction","msr-locale-en_us","msr-post-option-blog-homepage-featured"],"msr_event_details":{"start":"","end":"","location":""},"podcast_url":"","podcast_episode":"","msr_research_lab":[199565],"msr_impact_theme":[],"related-publications":[],"related-downloads":[],"related-videos":[],"related-academic-programs":[],"related-groups":[1105932],"related-projects":[],"related-events":[],"related-researchers":[{"type":"user_nicename","value":"Chenglong Wang","user_id":41251,"display_name":"Chenglong Wang","author_link":"<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/chenwang\/\" aria-label=\"Visit the profile page for Chenglong Wang\">Chenglong Wang<\/a>","is_active":false,"last_first":"Wang, Chenglong","people_section":0,"alias":"chenwang"},{"type":"user_nicename","value":"Scott Tsukamaki","user_id":44167,"display_name":"Scott Tsukamaki","author_link":"<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/stsukamaki\/\" aria-label=\"Visit the profile page for Scott Tsukamaki\">Scott Tsukamaki<\/a>","is_active":false,"last_first":"Tsukamaki, Scott","people_section":0,"alias":"stsukamaki"},{"type":"user_nicename","value":"Michel Galley","user_id":32887,"display_name":"Michel Galley","author_link":"<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/mgalley\/\" aria-label=\"Visit the profile page for Michel Galley\">Michel Galley<\/a>","is_active":false,"last_first":"Galley, Michel","people_section":0,"alias":"mgalley"},{"type":"user_nicename","value":"Jianfeng Gao","user_id":32246,"display_name":"Jianfeng Gao","author_link":"<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/jfgao\/\" aria-label=\"Visit the profile page for Jianfeng Gao\">Jianfeng Gao<\/a>","is_active":false,"last_first":"Gao, Jianfeng","people_section":0,"alias":"jfgao"}],"msr_type":"Post","featured_image_thumbnail":"<img width=\"960\" height=\"540\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-960x540.jpg\" class=\"img-object-cover\" alt=\"Three minimalist white line icons on a textured blue\u2011green gradient background: a rising bar chart on the left, a central hub\u2011and\u2011spoke network diagram in the middle, and a checkmark inside a circle on the right.\" decoding=\"async\" loading=\"lazy\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-960x540.jpg 960w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-300x169.jpg 300w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-1024x576.jpg 1024w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-768x432.jpg 768w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-1536x865.jpg 1536w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-2048x1153.jpg 2048w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-1066x600.jpg 1066w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-655x368.jpg 655w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-240x135.jpg 240w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-640x360.jpg 640w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-1280x720.jpg 1280w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2026\/05\/DataFormulator-BlogHeroFeature-1400x788-1-1920x1080.jpg 1920w\" sizes=\"auto, (max-width: 960px) 100vw, 960px\" \/>","byline":"<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/chenwang\/\" title=\"Go to researcher profile for Chenglong Wang\" aria-label=\"Go to researcher profile for Chenglong Wang\" data-bi-type=\"byline author\" data-bi-cN=\"Chenglong Wang\">Chenglong Wang<\/a>, <a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/stsukamaki\/\" title=\"Go to researcher profile for Scott Tsukamaki\" aria-label=\"Go to researcher profile for Scott Tsukamaki\" data-bi-type=\"byline author\" data-bi-cN=\"Scott Tsukamaki\">Scott Tsukamaki<\/a>, <a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/mgalley\/\" title=\"Go to researcher profile for Michel Galley\" aria-label=\"Go to researcher profile for Michel Galley\" data-bi-type=\"byline author\" data-bi-cN=\"Michel Galley\">Michel Galley<\/a>, and <a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/jfgao\/\" title=\"Go to researcher profile for Jianfeng Gao\" aria-label=\"Go to researcher profile for Jianfeng Gao\" data-bi-type=\"byline author\" data-bi-cN=\"Jianfeng Gao\">Jianfeng Gao<\/a>","formattedDate":"May 28, 2026","formattedExcerpt":"Data Formulator introduces AI-powered analytics for enterprise data workflows. Data teams can easily bring enterprise data into an AI-ready workspace where users can explore, analyze, and visualize data with AI agents to turn raw data into actionable insights.","locale":{"slug":"en_us","name":"English","native":"","english":"English"},"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/posts\/1173479","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/users\/44124"}],"replies":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/comments?post=1173479"}],"version-history":[{"count":9,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/posts\/1173479\/revisions"}],"predecessor-version":[{"id":1173873,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/posts\/1173479\/revisions\/1173873"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/1173551"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=1173479"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/categories?post=1173479"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/tags?post=1173479"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=1173479"},{"taxonomy":"msr-region","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-region?post=1173479"},{"taxonomy":"msr-event-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event-type?post=1173479"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=1173479"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=1173479"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=1173479"},{"taxonomy":"msr-promo-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-promo-type?post=1173479"},{"taxonomy":"msr-podcast-series","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-podcast-series?post=1173479"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}