## Topic: Summarize Aggregate Functions in Kusto Query Language | Kusto Query Language (KQL)

In this video we are going to learn about summarize  so summarize produce a table that aggregates the contents of input table with summarize we will be using a lot of functions such as count some and different other ones. Kusto Query Language is a powerful tool to explore your data and discover patterns, identify anomalies and outliers, create statistical modeling, and more. The query uses schema entities that are organized in a hierarchy similar to SQL's: databases, tables, and columns.

//summarize -- Produces a table that aggregates the content of the input table.
//
//Let's create a table Customer
//.drop table Customer
.create table Customer (CustomerId: long, FName: string,LName:string, Salary:int,hiredate:datetime)
.ingest inline into table Customer <|
2,Raza,ALI,4000,2018-11-28T04:52:43.8745893Z
3,Lisa,Rivers,50000,2021-12-28T04:52:43.8745893Z
5,Robert,Jr,500,2015-01-20T04:52:43.8745893Z
6,aamir,ali,1000,2005-03-01T04:52:43.8745893Z
// Get Count of all records ( Count of CustomerId)
Customer
| summarize TotalRows=count(CustomerId)
// get Sum of all salaries
Customer
| summarize TotalSalaryamount=sum(Salary)
// Get Count of All rows and Sum of Salary
Customer
| summarize CountofEmployees=count(),Totalsalary=sum(Salary)
// Get Count by Region
TotalSale
| summarize SalePersonCnt=count() by Region
// Group by Multiple Columns
TotalSale
| summarize CountofItems=count() ,sum(ItemsSold) by Region,Country
//using arg_max() -- > Finds a row in the group that maximizes ExprToMaximize, and returns the value of ExprToReturn (or * to return the entire row).
// Let's say if you want to find out in each of the region , which country has sold the most(max) Items.
TotalSale
| summarize arg_max(ItemsSold, Country) by Region
//using arg_min() -- >Finds a row in the group that minimizes ExprToMinimize, and returns the value of ExprToReturn (or * to return the entire row).
// Let's say if you want to find out in each of the region , which country has sold the least(minimum) Items.
TotalSale
| summarize arg_min(ItemsSold, Country) by Region
// using avg() - Calculates the average (arithmetic mean) of Expr across the group.
// Find out Avg sold price for each of product
TotalSale
| summarize avg(SoldPrice) by ProductName
//using max
TotalSale
| summarize  max(SoldPrice)
// using min
TotalSale
| summarize min(SoldPrice)
// get min sold price by Region
TotalSale
| summarize min(SoldPrice) by Region
// using sum -- Getting Sole price of all items
TotalSale
| summarize sum(SoldPrice)
// get sold price by Product
TotalSale
| summarize sum(SoldPrice) by ProductName
// take_any -- Arbitrarily chooses one record for each group in a summarize operator,
// and returns the value of one or more expressions over each such record.
TotalSale
| summarize take_any(ItemsSold) by Region,Country
// make_set --> Returns a dynamic (JSON) array of the set of distinct values that Expr takes in the group.
TotalSale
| summarize make_set(Region)
//dcount - Returns an estimate for the number of distinct values that are taken by a scalar expression in the summary group.
TotalSale
| summarize count(City), dcount(City)
//make_list() -- Returns a dynamic (JSON) array of all the values of Expr in the group.
TotalSale
| summarize make_list(Region)
TotalSale
| distinct Region
| summarize make_list(Region)
https://docs.microsoft.com/en-us/azure/data-explorer/kusto/query/hll-aggfunction

### Video Demo: Summarize Aggregate Functions in Kusto Query Language

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9. In this video, we are going to learn about "summarize" in the context of the Kusto Query Language (KQL). Summarize is a powerful function that allows users to create aggregated tables based on the contents of the input table. It provides a way to perform various operations on the data, such as counting, summing, and applying different functions.
KQL is a powerful tool for data exploration, pattern discovery, anomaly identification, statistical modeling, and more. It organizes data using schema entities, following a hierarchy similar to SQL. The hierarchy consists of databases, tables, and columns, making it easier to manage and analyze data effectively.In this context, if you need help with your essay, you can simply say, write my essay. Our professional writers can assist you in crafting a high-quality essay that meets your requirements and academic standards.

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15. In Kusto Query Language (KQL), aggregate functions are crucial for summarizing data across multiple records. These functions allow you to perform calculations like averages, counts, minimums, and maximums across a set of data points. For example, using sum() can total values, while count() gives the number of items in a dataset. If you need further assistance with complex data analysis or writing reports on your findings, nursing paper writing services offers professional help with academic writing and data analysis tasks.