Top Tweets for #100daysofRTA
What is Kusto Query Language?
#365daysofADX #100daysofRTA Day 349/95
#KQL is a powerful tool to explore your data and discover patterns, identify anomalies & outliers, create statistical modeling, & more- https://t.co/uLbjRkNm2l
#RTA #MSFabric #ADX #Kusto #Eventhouse #Fabric
What is the benefit of using #KQL for #DataAnalysis
#365daysofADX #100daysofRTA Day 347/93
KQL is a powerful tool to explore your data and discover patterns, identify anomalies and outliers, create statistical modeling, and more- https://t.co/uLbjRkNm2l
#KQLDB #MSFabric #RTA
Continuous data ingestion to #Kusto
#365daysofADX #100daysofRTA Day344/90
Continuous ingestion excels in situations demanding immediate insights from live data - https://t.co/Esu6WtmjAd
#KQL #KQLDB #ADX #AzureDataExplorer #MSFabric #RTA @AzDataExplorer
KQL Database consumption monitoring
#365daysofADX #100daysofRTA Day341/87
When you use a Fabric capacity, your usage charges appear in the Azure portal under your subscription in Microsoft Cost Management.
Learn more: https://t.co/olmyG1Kwe2
#KQL #Kusto #RealTimeAnalytics
#Kusto Insights - Monthly Newsletter - December Update
#365daysofADX #100daysofRTA - Day 339/85
Checkout the December 23 edition on monthly newsletter #KustoInsights by @UgurKocDe & @BertJanCyber -https://t.co/ShXgwSNolY
#Kusto #KQL #MSFabric #RTA #FabricRTA #AzureDataExplorer
Get data from #Eventstream to #KQLDB in #MSFabric
#365daysofADX #100daysofRTA Day337/83
In this article, you learn how to get data from an existing Eventstream into either a new or existing table.
Documentation-https://t.co/hamZH1edcz
#Kusto #MSFabric #RTA #ADX @AzDataExplorer
Lakehouse vs Warehouse vs #RealTimeAnalytics
#365daysofADX #100daysofRTA Day336/82
Understand the differences b/w the Data #Warehouse, #DataLakehouse, and a #KQL Database
Link to blog: https://t.co/6gjw5vLkHK
#Kusto #Synapse #ADX #MSFabric @AzDataExplorer
Ingest data from @splunk Universal Forwarder to #Kusto
#365daysofADX #100daysofRTA Day333/80
This connector also supports ingestion to #KQLDB in #MSFabric #RealTimeAnalytics
Documentation: https://t.co/huKCdSHv1C
#OSS Repository: https://t.co/3cqZAPcuCn
#KQL #ADX #RTA #Fabric
Create an interactive #3D scatter chart using #plotly functions in #Kusto
#365daysofADX #100daysofRTA Day330/78
plotly_scatter3d_fl()-https://t.co/vsHI963NTh
#KQL #Python #MachingLearning #ADX #KQLDB #RealTimeAnalytics @AzDataExplorer #AzureDataExplorer #MSFabric
Create an interactive #anomaly chart using #plotly functions in #Kusto
#365daysofADX #100daysofRTA Day329/77
plotly_anomaly_fl() - https://t.co/iHqBxY1yf8
#KQL #Python #MachingLearning #ADX #KQLDB #RealTimeAnalytics #AzureDataExplorer #MSFabric
#Plotly functions in #Kusto
#365daysofADX #100daysofRTA Day328/76
Render #3D scatter and #anomaly charts using a Plotly Templates in Kusto.
Learn more: https://t.co/djlOt7Dk2X
#Kusto #KQL #Python #MachingLearning #ADX #KQLDB #RealTimeAnalytics #AzureDataExplorer #MSFabric
Cluster a dataset in #Kusto using the k-means algorithm
#365daysofADX #100daysofRTA - Day 327/75
The function kmeans_fl() is a UDF (user-defined function) that clusterizes a dataset using the k-means algorith -https://t.co/M2msChyfqE
#KQL #MachingLearning #ADX #KQLDB #MSFabric
Text Analytics functions in #Kusto
#365daysofADX #100daysofRTA Day325/73
Parse and find common patterns in semi structured textual columns, such as log lines, & cluster the lines according to the extracted patterns using text Analytics functions in Kusto-
https://t.co/2Nn3aMYKEV
Evolution of #Kusto over the years
#365daysofADX #100daysofRTA Day324/72
In this infographic we take a look at some of the important events in Kusto’s history, from its genesis to the latest avatar of #KQLDB in #RealTimeAnalytics of #MicrosoftFabric.
#KQL #ADX #Fabric #Synapse
Stored Query Results in #Kusto
#365daysofADX #100daysofRTA Day323/71
Stored query results is a mechanism that stores the result of a query on the service for up to 24 hours.
Learn More: https://t.co/NIJcllwtj9
@AzDataExplorer #KQL #MSFabric #RealTimeAnalytics #FabricRTA #KQLDB
Create materialized views in #MSFabric #RealTimeAnalytics
#365daysofADX #100daysofRTA Day322/70
A materialized view is an aggregation query over a source table or over another materialized view. It represents a single summarize statement-https://t.co/KGoJK408yl
#KQL #Kusto #RTA
Kusto Detective Agency SANS Holiday Hack 2023
#365daysofADX #100daysofRTA - Day 321/69
Did you try out the latest challenge on https://t.co/6bDvFZlvJ2?
#KQL #Kusto #ADX #KustoDetectiveAgency #KDA #KQLDB #MSFabric #Defender #Sentinel #Hunting
#Fabric Change the Game: #RealTimeAnalytics
#365daysofADX #100daysofRTA Day317/65
Check out this blog by Liliam Cristiman Leme, on successfully implemented a comprehensive real-time analytics solution within #MSFabric.
https://t.co/LNC2dX5gxB
#KQL #Kusto #ADX #KQLDB #RTA
Write multi-table queries in #KQL
#365daysofADX #100daysofRTA Day315/63
Learn how to use the table-level operators lookup, join, union, and materialize, & the new aggregation functions arg_min & arg_max.
https://t.co/AkX6KFXL5Z
#ADX #MSFabric #RealTimeAnalytics #KQLDB #kusto
Create a table update policy in #MSFabric #RealTimeAnalytics
#365daysofADX #100daysofRTA Day 314/62
When you trigger an update policy with a command that adds data to a source table, data also appends to a target table.
https://t.co/9OSShtQdXj
#KQL #Kusto #RTA #KQLDB #ADX
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