{"id":15951,"date":"2016-11-04T17:35:15","date_gmt":"2016-11-04T17:35:15","guid":{"rendered":"https:\/\/thedatascientist.com\/?p=15951"},"modified":"2023-11-21T07:02:44","modified_gmt":"2023-11-21T07:02:44","slug":"team-data-science-processes","status":"publish","type":"post","link":"https:\/\/thedatascientist.com\/team-data-science-processes\/","title":{"rendered":"Team data science processes"},"content":{"rendered":"\n
\n
\n

Team Data Science Process<\/h2>\n\n\n\n

I have talked in the past in this blog about the need for standardisation of data science<\/a> and data science processes<\/strong>. Microsoft has made progress on that front. It has released a particular methodology called TDSP<\/strong><\/a> (Team Data Science Process). This is an attempt to formalise the way that data scientists work and collaborate.<\/p>\n\n\n\n

In order to further support this methodology Microsoft recently released two very valuable tools for TDSP which you can find at this repository<\/a>. The Modeling<\/a> tool allows for automated test of different algorithms and IDEAR<\/a> aids with exploration and reporting.<\/p>\n\n\n\n

\n
\n

Both of the tools are in R. The modelling tool uses YAML to specify experiments, which makes it pretty convenient. The cases covered now are binary classification and regression, but I would expect more things to see coming up in the future.  From the description of the documentation of TDSP<\/a>, it is clear that Microsoft wants to create something like Agile, but for data science.<\/p>\n\n\n

\n
\"data<\/a><\/figure><\/div>\n\n\n

While I am not suggesting that everyone should follow the methodology created by Microsoft, I do believe it is a step towards the right direction. I expect methodologies to show up in the near future.<\/p>\n\n\n\n

The importance of data science processes<\/h2>\n\n\n\n

I believe that data science<\/a> processes is an important step that data science needs to undertake in order to improve faster adoption in more industries. Right now the field is very dispersed, largely due to the fact that\u00a0data science<\/a>\u00a0is a combination of many disciplines: statistics, machine learning, AI and other fields (such as data mining). I have written in the past about the differences between\u00a0AI and machine learning<\/a>, and\u00a0machine learning with statistics<\/a>. There is a fragmentation in terms of training (how one becomes a\u00a0data scientist), methods, and languages (e.g<\/a>.\u00a0R vs Python).<\/p>\n\n\n\n

There have been some efforts to unify languages in the past through PMML<\/a> (Predictive Model Markup Language), but this was never widely adopted. Furthermore, the work done by Microsoft is in the right direction, because it provides a more abstract framework of<\/a> approaching data science problems. I don\u2019t believe unification of tools will ever happen, since there are so many software libraries coming out every year. However, the overall process itself through which we define problems and collaborate to solve them can be unified, and could help in the adoption of best practices in analytics throughout all industries.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Team Data Science Process I have talked in the past in this blog about the need for standardisation of data science and data science processes. Microsoft has made progress on that front. It has released a particular methodology called TDSP (Team Data Science Process). This is an attempt to formalise the way that data scientists work and collaborate. In order to… Read More »Team data science processes<\/span><\/a><\/p>\n","protected":false},"author":7,"featured_media":15956,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"neve_meta_sidebar":"","neve_meta_container":"","neve_meta_enable_content_width":"","neve_meta_content_width":0,"neve_meta_title_alignment":"","neve_meta_author_avatar":"","neve_post_elements_order":"","neve_meta_disable_header":"","neve_meta_disable_footer":"","neve_meta_disable_title":"","_ti_tpc_template_sync":false,"_ti_tpc_template_id":"","_jetpack_memberships_contains_paid_content":false,"footnotes":"","_wpscppro_custom_social_share_image":0,"_facebook_share_type":"","_twitter_share_type":"","_linkedin_share_type":"","_pinterest_share_type":"","_linkedin_share_type_page":"","_selected_social_profile":[]},"categories":[5,18,16],"tags":[],"yoast_head":"\nTeam data science processes - The Data Scientist<\/title>\n<meta name=\"description\" content=\"I have talked in the past in this blog about the need for data science processes that standardise data analysis. Microsoft has made progress on that front.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/thedatascientist.com\/team-data-science-processes\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Team data science processes - The Data Scientist\" \/>\n<meta property=\"og:description\" content=\"I have talked in the past in this blog about the need for data science processes that standardise data analysis. Microsoft has made progress on that front.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/thedatascientist.com\/team-data-science-processes\/\" \/>\n<meta property=\"og:site_name\" content=\"The Data Scientist\" \/>\n<meta property=\"article:published_time\" content=\"2016-11-04T17:35:15+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-11-21T07:02:44+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/thedatascientist.com\/wp-content\/uploads\/2023\/07\/azure_tdsp.png\" \/>\n\t<meta property=\"og:image:width\" content=\"742\" \/>\n\t<meta property=\"og:image:height\" content=\"506\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Dr. Stylianos (Stelios) Kampakis\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@s_kampakis\" \/>\n<meta name=\"twitter:site\" content=\"@s_kampakis\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Dr. Stylianos (Stelios) Kampakis\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/thedatascientist.com\/team-data-science-processes\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/thedatascientist.com\/team-data-science-processes\/\"},\"author\":{\"name\":\"Dr. Stylianos (Stelios) Kampakis\",\"@id\":\"https:\/\/thedatascientist.com\/#\/schema\/person\/787881a641bab92a8a46fcb198f9f6ba\"},\"headline\":\"Team data science processes\",\"datePublished\":\"2016-11-04T17:35:15+00:00\",\"dateModified\":\"2023-11-21T07:02:44+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/thedatascientist.com\/team-data-science-processes\/\"},\"wordCount\":422,\"publisher\":{\"@id\":\"https:\/\/thedatascientist.com\/#organization\"},\"image\":{\"@id\":\"https:\/\/thedatascientist.com\/team-data-science-processes\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/thedatascientist.com\/wp-content\/uploads\/2023\/07\/azure_tdsp.png\",\"articleSection\":[\"Data science\",\"Data science and AI for decision makers\",\"Technical Posts\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/thedatascientist.com\/team-data-science-processes\/\",\"url\":\"https:\/\/thedatascientist.com\/team-data-science-processes\/\",\"name\":\"Team data science processes - The Data Scientist\",\"isPartOf\":{\"@id\":\"https:\/\/thedatascientist.com\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/thedatascientist.com\/team-data-science-processes\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/thedatascientist.com\/team-data-science-processes\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/thedatascientist.com\/wp-content\/uploads\/2023\/07\/azure_tdsp.png\",\"datePublished\":\"2016-11-04T17:35:15+00:00\",\"dateModified\":\"2023-11-21T07:02:44+00:00\",\"description\":\"I have talked in the past in this blog about the need for data science processes that standardise data analysis. Microsoft has made progress on that front.\",\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/thedatascientist.com\/team-data-science-processes\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/thedatascientist.com\/team-data-science-processes\/#primaryimage\",\"url\":\"https:\/\/thedatascientist.com\/wp-content\/uploads\/2023\/07\/azure_tdsp.png\",\"contentUrl\":\"https:\/\/thedatascientist.com\/wp-content\/uploads\/2023\/07\/azure_tdsp.png\",\"width\":742,\"height\":506},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/thedatascientist.com\/#website\",\"url\":\"https:\/\/thedatascientist.com\/\",\"name\":\"The Data Scientist\",\"description\":\"data science courses, data science services, tokenomics consulting\",\"publisher\":{\"@id\":\"https:\/\/thedatascientist.com\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/thedatascientist.com\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/thedatascientist.com\/#organization\",\"name\":\"The Data Scientist\",\"url\":\"https:\/\/thedatascientist.com\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/thedatascientist.com\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/thedatascientist.com\/wp-content\/uploads\/2023\/05\/logo-TDS-white-text.webp\",\"contentUrl\":\"https:\/\/thedatascientist.com\/wp-content\/uploads\/2023\/05\/logo-TDS-white-text.webp\",\"width\":797,\"height\":249,\"caption\":\"The Data Scientist\"},\"image\":{\"@id\":\"https:\/\/thedatascientist.com\/#\/schema\/logo\/image\/\"},\"sameAs\":[\"https:\/\/x.com\/s_kampakis\",\"https:\/\/www.linkedin.com\/in\/dr-stylianos-kampakis\/\",\"https:\/\/www.youtube.com\/channel\/UClyTBR1b0ZEcZgWEhFf2POg\"]},{\"@type\":\"Person\",\"@id\":\"https:\/\/thedatascientist.com\/#\/schema\/person\/787881a641bab92a8a46fcb198f9f6ba\",\"name\":\"Dr. Stylianos (Stelios) Kampakis\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/thedatascientist.com\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/37d2748daf20ea5aa764cf8726fa34d1?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/37d2748daf20ea5aa764cf8726fa34d1?s=96&d=mm&r=g\",\"caption\":\"Dr. Stylianos (Stelios) Kampakis\"}}]}<\/script>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"Team data science processes - The Data Scientist","description":"I have talked in the past in this blog about the need for data science processes that standardise data analysis. Microsoft has made progress on that front.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/thedatascientist.com\/team-data-science-processes\/","og_locale":"en_US","og_type":"article","og_title":"Team data science processes - The Data Scientist","og_description":"I have talked in the past in this blog about the need for data science processes that standardise data analysis. Microsoft has made progress on that front.","og_url":"https:\/\/thedatascientist.com\/team-data-science-processes\/","og_site_name":"The Data Scientist","article_published_time":"2016-11-04T17:35:15+00:00","article_modified_time":"2023-11-21T07:02:44+00:00","og_image":[{"width":742,"height":506,"url":"https:\/\/thedatascientist.com\/wp-content\/uploads\/2023\/07\/azure_tdsp.png","type":"image\/png"}],"author":"Dr. Stylianos (Stelios) Kampakis","twitter_card":"summary_large_image","twitter_creator":"@s_kampakis","twitter_site":"@s_kampakis","twitter_misc":{"Written by":"Dr. Stylianos (Stelios) Kampakis","Est. reading time":"2 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/thedatascientist.com\/team-data-science-processes\/#article","isPartOf":{"@id":"https:\/\/thedatascientist.com\/team-data-science-processes\/"},"author":{"name":"Dr. Stylianos (Stelios) Kampakis","@id":"https:\/\/thedatascientist.com\/#\/schema\/person\/787881a641bab92a8a46fcb198f9f6ba"},"headline":"Team data science processes","datePublished":"2016-11-04T17:35:15+00:00","dateModified":"2023-11-21T07:02:44+00:00","mainEntityOfPage":{"@id":"https:\/\/thedatascientist.com\/team-data-science-processes\/"},"wordCount":422,"publisher":{"@id":"https:\/\/thedatascientist.com\/#organization"},"image":{"@id":"https:\/\/thedatascientist.com\/team-data-science-processes\/#primaryimage"},"thumbnailUrl":"https:\/\/thedatascientist.com\/wp-content\/uploads\/2023\/07\/azure_tdsp.png","articleSection":["Data science","Data science and AI for decision makers","Technical Posts"],"inLanguage":"en-US"},{"@type":"WebPage","@id":"https:\/\/thedatascientist.com\/team-data-science-processes\/","url":"https:\/\/thedatascientist.com\/team-data-science-processes\/","name":"Team data science processes - The Data Scientist","isPartOf":{"@id":"https:\/\/thedatascientist.com\/#website"},"primaryImageOfPage":{"@id":"https:\/\/thedatascientist.com\/team-data-science-processes\/#primaryimage"},"image":{"@id":"https:\/\/thedatascientist.com\/team-data-science-processes\/#primaryimage"},"thumbnailUrl":"https:\/\/thedatascientist.com\/wp-content\/uploads\/2023\/07\/azure_tdsp.png","datePublished":"2016-11-04T17:35:15+00:00","dateModified":"2023-11-21T07:02:44+00:00","description":"I have talked in the past in this blog about the need for data science processes that standardise data analysis. Microsoft has made progress on that front.","inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/thedatascientist.com\/team-data-science-processes\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/thedatascientist.com\/team-data-science-processes\/#primaryimage","url":"https:\/\/thedatascientist.com\/wp-content\/uploads\/2023\/07\/azure_tdsp.png","contentUrl":"https:\/\/thedatascientist.com\/wp-content\/uploads\/2023\/07\/azure_tdsp.png","width":742,"height":506},{"@type":"WebSite","@id":"https:\/\/thedatascientist.com\/#website","url":"https:\/\/thedatascientist.com\/","name":"The Data Scientist","description":"data science courses, data science services, tokenomics consulting","publisher":{"@id":"https:\/\/thedatascientist.com\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/thedatascientist.com\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/thedatascientist.com\/#organization","name":"The Data Scientist","url":"https:\/\/thedatascientist.com\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/thedatascientist.com\/#\/schema\/logo\/image\/","url":"https:\/\/thedatascientist.com\/wp-content\/uploads\/2023\/05\/logo-TDS-white-text.webp","contentUrl":"https:\/\/thedatascientist.com\/wp-content\/uploads\/2023\/05\/logo-TDS-white-text.webp","width":797,"height":249,"caption":"The Data Scientist"},"image":{"@id":"https:\/\/thedatascientist.com\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/x.com\/s_kampakis","https:\/\/www.linkedin.com\/in\/dr-stylianos-kampakis\/","https:\/\/www.youtube.com\/channel\/UClyTBR1b0ZEcZgWEhFf2POg"]},{"@type":"Person","@id":"https:\/\/thedatascientist.com\/#\/schema\/person\/787881a641bab92a8a46fcb198f9f6ba","name":"Dr. Stylianos (Stelios) Kampakis","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/thedatascientist.com\/#\/schema\/person\/image\/","url":"https:\/\/secure.gravatar.com\/avatar\/37d2748daf20ea5aa764cf8726fa34d1?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/37d2748daf20ea5aa764cf8726fa34d1?s=96&d=mm&r=g","caption":"Dr. Stylianos (Stelios) Kampakis"}}]}},"jetpack_sharing_enabled":true,"jetpack_featured_media_url":"https:\/\/thedatascientist.com\/wp-content\/uploads\/2023\/07\/azure_tdsp.png","_links":{"self":[{"href":"https:\/\/thedatascientist.com\/wp-json\/wp\/v2\/posts\/15951"}],"collection":[{"href":"https:\/\/thedatascientist.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/thedatascientist.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/thedatascientist.com\/wp-json\/wp\/v2\/users\/7"}],"replies":[{"embeddable":true,"href":"https:\/\/thedatascientist.com\/wp-json\/wp\/v2\/comments?post=15951"}],"version-history":[{"count":10,"href":"https:\/\/thedatascientist.com\/wp-json\/wp\/v2\/posts\/15951\/revisions"}],"predecessor-version":[{"id":22196,"href":"https:\/\/thedatascientist.com\/wp-json\/wp\/v2\/posts\/15951\/revisions\/22196"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/thedatascientist.com\/wp-json\/wp\/v2\/media\/15956"}],"wp:attachment":[{"href":"https:\/\/thedatascientist.com\/wp-json\/wp\/v2\/media?parent=15951"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/thedatascientist.com\/wp-json\/wp\/v2\/categories?post=15951"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/thedatascientist.com\/wp-json\/wp\/v2\/tags?post=15951"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}