{"id":"https://openalex.org/W7168124992","doi":"https://doi.org/10.21203/rs.3.rs-10307988/v1","title":"Intelligent Root Cause Analysis and Incident Diagnostics for Microsoft Fabric and Power BI through Telemetry Correlation and Kusto Query Language","display_name":"Intelligent Root Cause Analysis and Incident Diagnostics for Microsoft Fabric and Power BI through Telemetry Correlation and Kusto Query Language","publication_year":2026,"publication_date":"2026-07-13","ids":{"openalex":"https://openalex.org/W7168124992","doi":"https://doi.org/10.21203/rs.3.rs-10307988/v1"},"language":"en","primary_location":{"id":"doi:10.21203/rs.3.rs-10307988/v1","doi":"https://doi.org/10.21203/rs.3.rs-10307988/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-10307988/v1","pdf_url":"https://www.researchsquare.com/article/rs-10307988/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Research Square","raw_type":"posted-content"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.researchsquare.com/article/rs-10307988/latest.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133223811","display_name":"Shujath Baig Mirza","orcid":"https://orcid.org/0009-0000-2063-0518","observed_orcids":["https://orcid.org/0009-0000-2063-0518"]},"institutions":[{"id":"https://openalex.org/I143115733","display_name":"Saint Martin's University","ror":"https://ror.org/01awd1q38","country_code":"US","type":"education","lineage":["https://openalex.org/I143115733"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shujath Baig Mirza","raw_affiliation_strings":["Saint Martin's University, Lacey, Washington"],"raw_orcid":"https://orcid.org/0009-0000-2063-0518","affiliations":[{"raw_affiliation_string":"Saint Martin's University, Lacey, Washington","institution_ids":["https://openalex.org/I143115733"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5133223811"],"corresponding_institution_ids":["https://openalex.org/I143115733"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.00039999998989515007,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11891","display_name":"Big Data and Business Intelligence","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/root-cause-analysis","display_name":"root cause analysis","score":0.9909999966621399},{"id":"https://openalex.org/keywords/microsoft-fabric","display_name":"Microsoft Fabric","score":0.9800000190734863},{"id":"https://openalex.org/keywords/power-bi","display_name":"Power BI","score":1.0},{"id":"https://openalex.org/keywords/data-analytics-platform","display_name":"data analysis platform","score":0.8560000061988831}],"concepts":[{"id":"https://openalex.org/C130963320","wikidata":"https://www.wikidata.org/wiki/Q1401207","display_name":"Root cause analysis","level":2,"score":0.8166999816894531},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7603999972343445},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.664900004863739},{"id":"https://openalex.org/C84945661","wikidata":"https://www.wikidata.org/wiki/Q7366567","display_name":"Root cause","level":2,"score":0.6209999918937683},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.5946000218391418},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5285000205039978},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4564000070095062},{"id":"https://openalex.org/C183121708","wikidata":"https://www.wikidata.org/wiki/Q209867","display_name":"Telemetry","level":2,"score":0.44339999556541443},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.43220001459121704},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4221999943256378},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.41339999437332153},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3416999876499176},{"id":"https://openalex.org/C96608239","wikidata":"https://www.wikidata.org/wiki/Q1199823","display_name":"Statistical power","level":2,"score":0.3402000069618225},{"id":"https://openalex.org/C171078966","wikidata":"https://www.wikidata.org/wiki/Q111029","display_name":"Root (linguistics)","level":2,"score":0.33000001311302185},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3188999891281128},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.314300000667572},{"id":"https://openalex.org/C2909164965","wikidata":"https://www.wikidata.org/wiki/Q6014597","display_name":"Incident report","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.2605000138282776}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21203/rs.3.rs-10307988/v1","doi":"https://doi.org/10.21203/rs.3.rs-10307988/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-10307988/v1","pdf_url":"https://www.researchsquare.com/article/rs-10307988/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Research Square","raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.21203/rs.3.rs-10307988/v1","doi":"https://doi.org/10.21203/rs.3.rs-10307988/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-10307988/v1","pdf_url":"https://www.researchsquare.com/article/rs-10307988/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Research Square","raw_type":"posted-content"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7168124992.pdf","grobid_xml":"https://content.openalex.org/works/W7168124992.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W4414365780","https://openalex.org/W4414396065","https://openalex.org/W4414396146","https://openalex.org/W4414397505","https://openalex.org/W4414397814","https://openalex.org/W4414424750","https://openalex.org/W4414904273","https://openalex.org/W4415135808","https://openalex.org/W4415171612","https://openalex.org/W4415224127","https://openalex.org/W4417189297","https://openalex.org/W4417411462","https://openalex.org/W4417412351","https://openalex.org/W4417511482","https://openalex.org/W7081275173","https://openalex.org/W7081624004","https://openalex.org/W7083176096","https://openalex.org/W7083314014","https://openalex.org/W7084397140","https://openalex.org/W7084429017","https://openalex.org/W7090276454","https://openalex.org/W7103992170","https://openalex.org/W7104040353","https://openalex.org/W7104672606","https://openalex.org/W7104706728","https://openalex.org/W7108071895","https://openalex.org/W7108072575","https://openalex.org/W7114913001","https://openalex.org/W7115176349","https://openalex.org/W7115179174","https://openalex.org/W7115180264","https://openalex.org/W7115190312","https://openalex.org/W7115597163","https://openalex.org/W7117968127","https://openalex.org/W7118627350","https://openalex.org/W7119639862","https://openalex.org/W7124529790","https://openalex.org/W7124554197","https://openalex.org/W7124600317","https://openalex.org/W7124600441","https://openalex.org/W7125116382","https://openalex.org/W7125203925","https://openalex.org/W7125416908","https://openalex.org/W7125498378","https://openalex.org/W7133197655"],"related_works":["https://openalex.org/W7164302211","https://openalex.org/W7167953347","https://openalex.org/W4416553765","https://openalex.org/W7142265279","https://openalex.org/W7118724276","https://openalex.org/W7222150586","https://openalex.org/W7171728728","https://openalex.org/W7222925272","https://openalex.org/W7134234447","https://openalex.org/W7128806013"],"abstract_inverted_index":{"Abstract":[0],"Large-scale":[1],"analytics":[2,151,211],"platforms":[3,36],"such":[4],"as":[5],"Microsoft":[6,224],"Fabric":[7,225],"and":[8,20,28,44,59,70,79,92,101,113,121,146,170,220,226],"Power":[9,227],"BI":[10],"play":[11],"a":[12,117,185,214],"critical":[13],"role":[14],"in":[15,34,75,209,223],"enterprise":[16],"decision-making,":[17],"making":[18],"rapid":[19],"accurate":[21,148],"incident":[22,32,93,157,207],"diagnostics":[23,94,208],"essential":[24],"for":[25,217],"maintaining":[26],"reliability":[27,191],"user":[29],"trust.":[30],"However,":[31],"investigation":[33],"these":[35,193],"remains":[37],"challenging":[38],"due":[39],"to":[40,128,174,177,205],"the":[41,161,190,198],"volume,":[42],"heterogeneity,":[43],"siloed":[45],"nature":[46],"of":[47,150,192,200],"telemetry":[48,99,142,203],"generated":[49],"across":[50],"data":[51],"ingestion":[52],"pipelines,":[53],"semantic":[54],"models,":[55],"query":[56],"execution":[57],"engines,":[58],"shared":[60],"capacity":[61],"layers.":[62],"Existing":[63],"approaches":[64],"rely":[65],"heavily":[66],"on":[67,140],"manual":[68,179],"analysis":[69,91,183],"ad":[71],"hoc":[72],"querying,":[73],"resulting":[74],"prolonged":[76],"diagnostic":[77,126],"times":[78],"inconsistent":[80],"root":[81,89,137,166],"cause":[82,90,167],"identification.":[83],"This":[84],"paper":[85],"presents":[86],"an":[87],"intelligent":[88],"framework":[95,163],"that":[96,160],"leverages":[97],"multi-layer":[98],"correlation":[100,204],"Kusto":[102],"Query":[103],"Language\u2013driven":[104],"analysis.":[105],"The":[106,195],"proposed":[107,162],"approach":[108],"unifies":[109],"logs,":[110],"metrics,":[111],"traces,":[112],"platform-specific":[114],"signals":[115],"into":[116],"coherent":[118],"analytical":[119],"model":[120],"operationalizes":[122],"reusable,":[123],"dependency-aware":[124],"KQL":[125],"templates":[127],"guide":[129],"systematic":[130],"investigation.":[131],"An":[132],"inference":[133],"layer":[134],"ranks":[135],"probable":[136],"causes":[138],"based":[139],"correlated":[141],"patterns,":[143],"enabling":[144],"faster":[145],"more":[147,218],"diagnosis":[149,175],"incidents.":[152],"Experimental":[153],"evaluation":[154],"using":[155],"controlled":[156],"simulations":[158],"demonstrates":[159],"significantly":[164],"improves":[165],"identification":[168],"accuracy":[169],"reduces":[171],"mean":[172],"time":[173],"compared":[176],"traditional":[178],"RCA":[180],"workflows.":[181],"Statistical":[182],"at":[184],"95%":[186],"confidence":[187],"level":[188],"confirms":[189],"improvements.":[194],"results":[196],"highlight":[197],"potential":[199],"intelligent,":[201],"query-driven":[202],"transform":[206],"modern":[210],"platforms,":[212],"offering":[213],"practical":[215],"foundation":[216],"reliable":[219],"scalable":[221],"operations":[222],"BI-like":[228],"environments.":[229]},"counts_by_year":[{"year":2026,"cited_by_count":13}],"updated_date":"2026-11-09T13:22:03.289127","created_date":"2026-07-14T00:00:00"}
