{"id":1157,"date":"2023-04-19T16:35:10","date_gmt":"2023-04-19T16:35:10","guid":{"rendered":"https:\/\/d3mlabs.de\/?p=1157"},"modified":"2023-04-19T19:00:56","modified_gmt":"2023-04-19T19:00:56","slug":"can-we-align-on-the-definition-of-self-service-analytics","status":"publish","type":"post","link":"https:\/\/d3mlabs.de\/?p=1157","title":{"rendered":"Can we align on the Definition of\u00a0SELF-SERVICE ANALYTICS?"},"content":{"rendered":"\n

Also published here <\/a>on Ashish’s Substack <\/p>\n\n\n\n

I have been reading about self-service analytics over LinkedIn from different Data Leaders for some time. I feel everyone has a different definition of Self-Service Analytics.<\/p>\n\n\n\n

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With this article, I want to give everyone\u2018s definition a perspective because most of them are not wrong. I am also looking for some people to challenge me if, in their organization, they have a different kind of self-service analytics.<\/em><\/p>\n<\/blockquote>\n\n\n\n

Gartner for High Tech<\/a> gave a good base for the definition of self-service analytics:
Self-Service Analytics is a form of business intelligence (BI) in which line-of-business professionals are enabled and encouraged to perform queries and generate reports on their own, with nominal IT support. Self-service analytics is often characterized by simple-to-use BI tools with basic analytic capabilities and an underlying data model that has been simplified or scaled down for ease of understanding and straightforward data access.<\/p>\n\n\n\n

What I consider here, there are different levels of self-service analytics.<\/strong><\/p>\n\n\n\n

Level 0 – No Enablement<\/strong> – The BI Team performs all the queries and generate reports for every use-case of the Line of Businesses (LOB).<\/p>\n\n\n\n

Level 1 – BI Assisted Enablement<\/strong> – The BI Team creates the reports or table visualisations with maximum number of dimensions so that the LOB explore the recent or future use-cases with minimum generation of new reports.<\/p>\n\n\n\n

Level 2 – Conditional Enablement<\/strong> – The BI Team\/Analytics Engineers create the data models and educate the LOB with easy-to-use BI tools (such as Tableau<\/a>, Metabase<\/a>). As a result, The LOB can explore the number of concerns.<\/p>\n\n\n\n

Level 3 – Full Enablement<\/strong> – The BI Team \/ Analytics Engineers create the data models and the organization has natural conversational tools (such as ThoughtSpot<\/a>, Microsoft Clarity<\/a>) so that anyone in the organization can ask anything.<\/p>\n\n\n\n

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In big organizations or big start-ups<\/strong>, all levels will exist because of different use cases, priorities, stakeholders being very technical etc. In small start-ups<\/strong>, it is better and more resource efficient to be on a specific level.<\/em><\/p>\n<\/blockquote>\n\n\n\n

Who is Ashish Kalra?<\/strong><\/p>\n\n\n\n

Ashish Kalra is an experienced data leader with 10+ years of experience in the industry with different business models such as Social Network, B2C, E-commerce etc. Conversion Rate Optimization, CLV\/Retention Optimization, Marketing Budgeting Analytics, Project Market Fit and Self-Service Analytics have been the key projects delivered under his portfolio.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Ashish Kalra is an experienced data leader who has been reading about self-service analytics over LinkedIn from different Data Leaders for some time. He has observed that everyone has their own definition of „Self-Service Analytics.“ In this article, Ashish publishes his own view on the topic and is open to peer and stakeholder feedback.<\/p>\n","protected":false},"author":8,"featured_media":1160,"comment_status":"open","ping_status":"open","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,"footnotes":""},"categories":[41,9,48],"tags":[],"class_list":["post-1157","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-analytics","category-data-products","category-self-service","wpcat-41-id","wpcat-9-id","wpcat-48-id"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/d3mlabs.de\/index.php?rest_route=\/wp\/v2\/posts\/1157","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/d3mlabs.de\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/d3mlabs.de\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/d3mlabs.de\/index.php?rest_route=\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/d3mlabs.de\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1157"}],"version-history":[{"count":4,"href":"https:\/\/d3mlabs.de\/index.php?rest_route=\/wp\/v2\/posts\/1157\/revisions"}],"predecessor-version":[{"id":1164,"href":"https:\/\/d3mlabs.de\/index.php?rest_route=\/wp\/v2\/posts\/1157\/revisions\/1164"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/d3mlabs.de\/index.php?rest_route=\/wp\/v2\/media\/1160"}],"wp:attachment":[{"href":"https:\/\/d3mlabs.de\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1157"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/d3mlabs.de\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1157"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/d3mlabs.de\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1157"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}