| 1 - Introduction.mp4 | 52.4 MB | ||
| 10 - Ingesting Data.mp4 | 124.7 MB | ||
| 11 - KQL Management Commands.mp4 | 127.8 MB | ||
| 12 - Introduction.mp4 | 72.6 MB | ||
| 13 - MakeSeries Operator.mp4 | 153.9 MB | ||
| 13 - make-series.Kql | 1.3 KB | ||
| 14 - Calculating a Moving Average with seriesfir.mp4 | 79.1 MB | ||
| 14 - series-fir.Kql | 1 KB | ||
| 15 - series-fir-More.Kql | 921.6 B | ||
| 15 - seriesfir A Bit More.mp4 | 27.7 MB | ||
| 16 - Trend Analysis Linear Regression Part 1.mp4 | 83.2 MB | ||
| 16 - Trend-Lines.Kql | 307.2 B | ||
| 17 - Trend Analysis Linear Regression Part 2.mp4 | 38.9 MB | ||
| 17 - Trend-Lines-Part-2.Kql | 102.4 B | ||
| 18 - Trend Analysis seriesdecompose.mp4 | 77 MB | ||
| 18 - series-decompose.Kql | 409.6 B | ||
| 19 - Anomaly Detection Forecasting.mp4 | 52.7 MB | ||
| 19 - Anomolies-Forecasting.Kql | 1.2 KB | ||
| 2 - Kusto Explorer.mp4 | 26.6 MB | ||
| 20 - Other Functions in the Series Family.mp4 | 23.5 MB | ||
| 20 - Other-Series-Functions.Kql | 409.6 B | ||
| 21 - Basket Analysis.mp4 | 53.7 MB | ||
| 21 - Basket-Analysis.Kql | 1.2 KB | ||
| 22 - Autoclustering.Kql | 1.1 KB | ||
| 22 - Clustering.mp4 | 43.6 MB | ||
| 23 - Reduce.mp4 | 21.4 MB | ||
| 24 - Geospatial Analysis using KQL.mp4 | 84.5 MB | ||
| 24 - Geospatial.Kql | 1.5 KB | ||
| 25 - Accessing Azure Data Explorer from Microsoft Excel and Power BI.mp4 | 91 MB | ||
| 26 - Row-Rank.Kql | 409.6 B | ||
| 26 - RowRank.mp4 | 31.1 MB | ||
| 27 - RowCumSum.mp4 | 27 MB | ||
| 27 - row-cumsum.Kql | 204.8 B | ||
| 28 - Pivot.Kql | 307.2 B | ||
| 28 - Pivot.mp4 | 50.8 MB | ||
| 29 - Sequence-Detect.Kql | 204.8 B | ||
| 29 - SequenceDetect.mp4 | 24.1 MB | ||
| 3 - Overview.mp4 | 140.2 MB | ||
| 30 - Narrow.mp4 | 14.5 MB | ||
| 31 - SlidingWindow.mp4 | 30.8 MB | ||
| 31 - sliding-window.Kql | 204.8 B | ||
| 32 - KQL-Changes.Sql | 307.2 B | ||
| 32 - September 2022 New KQL Functions.mp4 | 26.1 MB | ||
| 33 - August 2022 Azure Data Explorer Enhancements.mp4 | 38.7 MB | ||
| 34 - Test Your Knowledge.mp4 | 157 MB | ||
| 4 - Azure Data Explorer Web UI.mp4 | 29.3 MB | ||
| 5 - A Little More About Architecture.mp4 | 142.2 MB | ||
| 6 - Visualizing Data Dashboards Part 1.mp4 | 71.3 MB | ||
| 7 - Visualizing Data Dashboards Part 2.mp4 | 123.2 MB | ||
| 8 - Visualizing Data Dashboards Part 3.mp4 | 48.9 MB | ||
| 9 - Fruit.csv | 4.9 KB | ||
| 9 - Render.Kql | 1.8 KB | ||
| 9 - Rendering Data.mp4 | 87.9 MB | ||
| AllstarFull.csv | 213.6 KB | ||
| Appearances.csv | 6.4 MB | ||
| Batting.csv | 6.5 MB | ||
| BattingPost.csv | 944.3 KB | ||
| Bonus Resources.txt | 409.6 B | ||
| Fielding.csv | 6.9 MB | ||
| FieldingOF.csv | 279.7 KB | ||
| FieldingOFsplit.csv | 1.6 MB | ||
| FieldingPost.csv | 727.5 KB | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| HomeGames.csv | 164.3 KB | ||
| Managers.csv | 134.8 KB | ||
| ManagersHalf.csv | 3.4 KB | ||
| Parks.csv | 11.4 KB | ||
| People.csv | 2.6 MB | ||
| Pitching.csv | 4.2 MB | ||
| PitchingPost.csv | 524.3 KB | ||
| SeriesPost.csv | 10.7 KB | ||
| Teams.csv | 577.5 KB | ||
| TeamsFranchises.csv | 3.2 KB | ||
| TeamsHalf.csv | 1.5 KB | ||
| part-r-00000-ddaee723-f3f6-4f25-a34b-3312172aa6d7.snappy.parquet | 16.6 KB | ||
| ▲ 75 total files | |||
Kusto Query Language (Kql) - Part 2
https://DevCourseWeb.com
Published 10/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.23 GB | Duration: 4h 53m
A Deeper dive into Azure Data Explorer (ADX) and the Kusto Query Language (KQL)
What you'll learn
A Deeper Dive into Azure Data Explorer over Part 1 of this Series
More coverage of the amazing Kusto Query Language (KQL)
Visualizing Data using Dashboards with Azure Data Explorer
Rendering Data with Azure Data Explorer and KQL
Ingesting Data into Azure Data Explorer
Time Series Analysis with KQL
Trend Analysis with KQL
Anomaly Detection and Forecasting with KQL
Machine Learning with KQL
And More...
Requirements
No knowledge of Azure required. Some knowledge of SQL would be helpful.
A Microsoft account will be required to use the Log Analytics site. There is no cost involved.
Description
As mentioned in the course description for Part 1, there is a good chance you have already used Azure Data Explorer (ADX) to some degree without knowing it. If you have used Azure Security Center, Azure Sentinel, Application Insights, Resource Graph Explorer, or enabled diagnostics on your Azure resources, then you have used ADX. All these services rely on Log Analytics, which is built on top of ADX and is queried using KQL.Like many other tools and products, ADX was started by a small group of engineers in Israel around 2015. They needed to solve a problem. A group of developers from Microsoft's Power BI team needed a high-performing big data solution to ingest and analyze their logging and telemetry data. So, of course, they built their own because they could not find a service that met all their needs. This resulted in the Azure Data Explorer, also known as Kusto.So, what is ADX? It is a fully managed, append-only columnar store big data service capable of elastic scaling and ingesting literally hundreds of billions of rows daily. ADX offers:Low-latency ingestion and elastic scalingSecurityCost-efficient (pay as you consume)High availabilityTime Series AnalysisSuper fast query performance via KQLCustom built solutionsPart 2 of this series of courses on Azure Data Explorer and KQL goes more deeply into ADX and covers more use cases for the Kusto Query Language. The more deeply you get into KQL the more you realize what an amazing query language it is. And, you will probably start wondering why SQL doesn't implement many of the features we covered in Part 1 and will cover in Part 2.Will there be a Part 3? That is up to you. Tell us what you would like to see that we haven't yet already covered.
Overview
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