Factor analysis entails taking a large data set and shrinking it to a smaller data set. Regression analysis entails analyzing the relationship between dependent variables to determine how a change in one may affect the change in another.This information can then be used to optimize processes to increase the overall efficiency of a business or system. Data analytics techniques can reveal trends and metrics that would otherwise be lost in the mass of information. Any type of information can be subjected to data analytics techniques to get insight that can be used to improve things. Data analytics relies on a variety of software tools ranging from spreadsheets, data visualization, and reporting tools, data mining programs, or open-source languages for the greatest data manipulation.ĭata analytics is a broad term that encompasses many diverse types of data analysis.Various approaches to data analytics include looking at what happened (descriptive analytics), why something happened (diagnostic analytics), what is going to happen (predictive analytics), or what should be done next (prescriptive analytics).The techniques and processes of data analytics have been automated into mechanical processes and algorithms that work over raw data for human consumption.Data analytics help a business optimize its performance, perform more efficiently, maximize profit, or make more strategically-guided decisions.Data analytics is the science of analyzing raw data to make conclusions about that information.Runs the function on the table that it receives as input.Įvaluates query language extensions (plugins) Let Name = ScalarExpression | TabularExpression | FunctionDefinitionExpression Use let to create expressions over tables whose results look like a new table. Values can be lambda expressions to create query-defined functions as part of the query. T | make-series Aggregation on AxisColumn from start to end step step GroupExpression ]īinds a name to expressions that can refer to its bound value. T | parse |simple|relaxed] Expression with * (StringConstant ColumnName ) *.Ĭreates series of specified aggregated values along a specified axis Turns dynamic arrays into rows (multi-value expansion)Įvaluates a string expression and parses its value into one or more calculated columns. Restructure the data to output in a useful wayĮxtends the columns of a fact table with values looked-up in a dimension table Range columnName from start to stop step step Generates a table with an arithmetic series of values Takes two or more tables and returns all their rows LeftTable | join ( RightTable ) on Attributes Supports a full range of join types: flouter, inner, innerunique, leftanti, leftantisemi, leftouter, leftsemi, rightanti, rightantisemi, rightouter, rightsemi Merges the rows of two tables to form a new table by matching values of the specified column(s) from each table. This operator is shorthand for summarize count() T | summarize Aggregation ] GroupExpression ]Ĭounts records in the input table (for example, T) Groups the rows according to the by group columns, and calculates aggregations over each group Returns the first N rows of the dataset when the dataset is sorted using by T | sort by expression1, expression2, … Sort the rows of the input table by one or more columns in ascending or descending order Restructure the data by sorting or grouping them in meaningful ways T | project-rename new_column_name = column_nameĬreates a calculated column and adds it to the result set Selects the columns to keep in the output Selects the columns to exclude from the output Selects the columns to include in the order specified Outputs a single row with one or more scalar expressions Rounds all values in a timeframe and groups them For example, ago(1h) is one hour before the current clock's reading. Returns the time offset relative to the time the query executes. Operations that use date and time functions Produces a table with the distinct combination of the provided columns of the input table Use to test a queryĪdds a condition statement, similar to if/then/elseif in other systems.Ĭase(predicate_1, then_1, predicate_2, then_2, predicate_3, then_3, else) Searches all columns in the table for the value Has: Looks for a specific word (better performance) Operator/Functionįind relevant data by filtering or searching This article shows you a list of functions and their descriptions to help get you started using Kusto Query Language.
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