Application Insights Stats-1

August 16, 2015

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This model consumes Application Insights data about Page View Performances to produce various statistics.
<h1>Application Insights Stats-1</h1> <h3>Summary</h3> This Azure ML experiment consumes Application Insights data about Page View Performances. It summarizes that data by Day, Page name and Country; and then produces statistics like Min, Max, Mean, Median, Standard Deviation and Percentile. Application Insights data used in this experiment is read from .CSV file stored in Azure Blob. Azure Application Insights enable <a href="https://azure.microsoft.com/en-in/documentation/articles/app-insights-code-sample-export-telemetry-sql-database/#start-continuous-export-to-azure-storage">Continuous Data Export </a>that can be consumed for further use. <h3>Input Dataset</h3> Data source utilized in this experiment (available as .CSV file) is comprised of following selected items from Application Insights Page View Performances data: <br><li>Date <br><li>Pagename <br><li>Country <br><li>clientProcess_value <br><li>networkConnection_value <br><li>receiveRequest_value <br><li>sendRequest_value <br><li>total_value <h3>Experiment Flow</h3> This experiment performs the following steps to produce the required statistics: <br><br><strong>Step-1:</strong> Read the source data <br><br><strong>Step-2:</strong> Define metadata for the given dataset, i.e. <br><li><strong>group_by_cols</strong>: Number of columns to be used for grouping. These columns must be starting columns in the data set <br><li><strong>metric_cols</strong>: Number of metric columns, these columns will follow group_by_cols in the data <br><li><strong>fn_list</strong>: List of functions to be executed on each of the metric column <br><li><strong>fn_args</strong>: Arguments cooresponding to the functions in the fn_list <br><li><strong>stats_col_names</strong>: Name of each column produced by executing various function on the metric data <br><br><strong>Step-3:</strong> Loop through each of the metric column and function list. With this each function is executed on every metric column. Data is collated to produce the output result dataset. <h3>Output Dataset-1</h3> Summarized statistics produced by Day, Page name, Country and Metric name are stored into a .CSV file. This dataset contains following values: <br><li>Date <br><li>Pagename <br><li>Country <br><li>Metric_Name <br><li>Min.by.Day <br><li>Max.by.Day <br><li>Mean.by.Day <br><li>Median.by.Day <br><li>Standard Deviation.by.Day <br><li>Percentile_10.by.Day <br><li>Percentile_90.by.Day <h3>Output Dataset-2</h3> It is produced by normalizing Output Dataset-1 for consumption in UI reports