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Covers core operators for selection, column aliases, null handling, comparisons for dates and strings, distinct, grouping and aggregation, ordering, limiting results, unions, joins, and provides example transformations such as dependency and exception combinations. Includes guidance on relevant Analytics functions by category, along with common string, math, parsing, date, logical, dynamic object, and machine-learning operators.",{"@graph":63,"@context":119},[64,80,102],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":51,"@type":70,"position":76},"https://docshare.wps.com/template/general/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/sql-to-analytics-language-cheat-sheet-useful-operators/572126/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/sql-to-analytics-language-cheat-sheet-useful-operators/572126.png","ImageObject",442,249,{"name":88,"@type":89},"dbqoiu","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-10-22","2026-10-13",true,{"@type":98,"interactionType":99,"userInteractionCount":101},"InteractionCounter",{"@type":100},"ViewAction",8,{"@type":103,"mainEntity":104},"FAQPage",[105,111,115],{"name":106,"@type":107,"acceptedAnswer":108},"What does the cheat sheet map between SQL and Analytics Query?","Question",{"text":109,"@type":110},"It provides example SQL operators and statements alongside their corresponding Analytics Query syntax for Azure Application Insights.","Answer",{"name":112,"@type":107,"acceptedAnswer":113},"How does the document handle null checks and boolean logic?",{"text":114,"@type":110},"It shows null evaluation using IS NOT NULL in SQL paired with isnotnull(...) in Analytics, and demonstrates boolean comparison patterns for success values.",{"name":116,"@type":107,"acceptedAnswer":117},"Which Analytics functions are highlighted for string, math, and date work?",{"text":118,"@type":110},"It lists common string functions (startswith/contains, substring, strlen), math functions (sqrt, abs, log, pow), and date functions (now, ago, datetime, start/end variants, datepart-related functions).","https://schema.org",{"og:url":78,"og:type":121,"og:title":59,"og:site_name":91,"og:description":61},"article",{"robots":123,"canonical":78},"index,follow",{"doc_id":125,"site_id":56},572126,1792083187,{"code":4,"msg":5,"data":128},{"doc_id":125,"user_id":129,"nickname":88,"user_avatar":130,"doc_module":9,"category_id":50,"category_name":51,"doc_title":59,"doc_description":61,"doc_content":131,"file_id":132,"file_url":133,"file_type":134,"file_size":135,"view_count":101,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":73,"language":136,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":137,"faqs":138,"seo_title":139,"seo_description":61,"update_tm":140,"read_time":9},3985747862462,"https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2","Microsoft Azure Application Insights  \nSQL to Analytics language cheat sheet  \nDownload this document at [https://aka.ms/sql-analytics](https://aka.ms/sql-analytics)  \n\n|  | SQL Query | Analytics Query |\n| --- | --- | --- |\n| Select data from table | SELECT * FROM dependencies | dependencies |\n|  | SELECT name, resultCode FROM dependencies | dependencies | project name, resultCode |\n|  |  | dependencies | project-away name |\n|  | SELECT TOP 100 * FROM dependencies | dependencies | take 100 |\n| Null evaluation | SELECT * FROM dependencies WHERE resultCode IS NOT NULL | dependencies | where isnotnull(resultCode) |\n| Comparison operators (date) | SELECT * FROM dependencies\u003Cbr>WHERE timestamp > getdate() -1 | dependencies\u003Cbr>| where timestamp > ago(1d) |\n|  | SELECT * FROM dependencies\u003Cbr>WHERE timestamp\u003Cbr>BETWEEN '2016-10-01' AND '2016-11-01' | dependencies\u003Cbr>| where timestamp > datetime(2016-10-01)\u003Cbr>and timestamp \u003C= datetime(2016-11-01) |\n| Comparison Operators (string) | SELECT * FROM dependencies WHERE type = \"Azure blob\" | dependencies\u003Cbr>| where type == \"Azure blob\" |\n|  | --substring\u003Cbr>SELECT * FROM dependencies WHERE type like \"%blob%\" | //substring\u003Cbr>dependencies\u003Cbr>| where type contains \"blob\" |\n|  | --wildcard\u003Cbr>SELECT * FROM dependencies WHERE type like \"Azure%\" | dependencies\u003Cbr>| where type startswith \"Azure\"\u003Cbr>dependencies\u003Cbr>| where type matches regex \"^Azure.*\" |\n| Comparison (boolean) | SELECT * FROM dependencies\u003Cbr>WHERE !(success) | dependencies\u003Cbr>| where success == \"False\" |\n| Distinct | SELECT DISTINCT name, type FROM dependencies | dependencies\u003Cbr>| summarize by name, type |\n| Grouping, Aggregation | SELECT name, AVG(duration)\u003Cbr>FROM dependencies\u003Cbr>GROUP BY name | dependencies\u003Cbr>| summarize avg(duration) by name |\n| Column aliases, Extending | SELECT operation_Name as Name, AVG(duration) as AvgD\u003Cbr>FROM dependencies\u003Cbr>GROUP BY name | dependencies\u003Cbr>| summarize AvgD=avg(duration) by operation_Name | project Name=operation_Name, AvgD |\n| Ordering | SELECT name, timestamp\u003Cbr>FROM dependencies\u003Cbr>ORDER BY timestamp asc | dependencies\u003Cbr>| project name, timestamp\u003Cbr>| order by timestamp asc nulls last |\n| Top n\u003Cbr>by measure | SELECT TOP 100 name, COUNT(*) as Count\u003Cbr>FROM dependencies GROUP BY name ORDER BY Count desc | dependencies\u003Cbr>| summarize Count=count() by name | top 100 by Count desc |\n| Union | SELECT * FROM dependencies\u003Cbr>UNION\u003Cbr>SELECT * FROM exceptions | union dependencies, exceptions |\n|  | SELECT * FROM dependencies WHERE timestamp> . . UNION\u003Cbr>SELECT * FROM exceptions WHERE timestamp> . . | dependencies | where timestamp > ago(1d)| union\u003Cbr>(exceptions | where timestamp > ago(1d) ) |\n| Join | SELECT * FROM dependencies\u003Cbr>LEFT OUTER JOIN exception\u003Cbr>ON dependencies.operation_Id = exceptions.operation_Id | dependencies\u003Cbr>| join kind=leftouter (exceptions)\u003Cbr>on $left.operation_Id == $right.operation_Id |\n\nThese are just subset of the operators available. Please refer to [https://aka.ms/AIAnalyticsReference](https://aka.ms/AIAnalyticsReference) for a complete reference.  \nTry Analytics yourself by instrumenting with Azure Application Insights, or in the Analytics demo environment: [https://aka.ms/AIAnalyticsDemo](https://aka.ms/AIAnalyticsDemo)!  \n[https://www.azure.com](https://www.azure.com)  \n© 2016 Microsoft Corporation. All rights reserved.  \n [AIAnalyticsOutreach@microsoft.com](AIAnalyticsOutreach@microsoft.com)[ ](AIAnalyticsOutreach@microsoft.com)@Azure  \nApplication Insights Analytics – useful operators  \n\n| Category | Relevant Analytics functions |\n| --- | --- |\n| Selection and Column aliases | project, project-away, extend |\n| Temporary tables and constants | let scalar_alias_name = …;\u003Cbr>let table_alias_name = (){ … | … | … }; |\n| Comparison and String Operators | startswith, !startswith has*, !has\u003Cbr>contains, !contains, containscs hasprefix, !hasprefix, hassuffix, !hassuffix in, !in\u003Cbr>matches regex ==, =~, !=, !~\u003Cbr>*has is more performant than contains |\n| Common ","cbCaisub8VwLTeG7","https://ap.wps.com/l/cbCaisub8VwLTeG7","pdf",731768,"English","# SQL Query to Analytics Query operators\n## Selection and column aliases\n## Null evaluation and comparisons\n## Distinct, grouping, aggregation, and ordering\n## Top n, unions, and joins\n# Useful Analytics functions by category\n## Temporary tables and constants\n## String, math, parsing, and limiting output\n## Date functions and grouping/aggregation\n## Joins and unions, sorting, logical operators\n## Dynamic object operators and machine learning","[{\"question\":\"What does the cheat sheet map between SQL and Analytics Query?\",\"answer\":\"It provides example SQL operators and statements alongside their corresponding Analytics Query syntax for Azure Application Insights.\"},{\"question\":\"How does the document handle null checks and boolean logic?\",\"answer\":\"It shows null evaluation using IS NOT NULL in SQL paired with isnotnull(...) in Analytics, and demonstrates boolean comparison patterns for success values.\"},{\"question\":\"Which Analytics functions are highlighted for string, math, and date work?\",\"answer\":\"It lists common string functions (startswith/contains, substring, strlen), math functions (sqrt, abs, log, pow), and date functions (now, ago, datetime, start/end variants, datepart-related functions).\"}]","SQL to Analytics language cheat sheet - useful operators | PDF",1791925682]