Analyzing Data using KQL
KQL stands for Kusto Query Language and is used to analyze tabular data available through Azure Monitor and Azure Application Insights. KQL is fairly simple and resembles SQL in many ways.
A Kusto query is a read-only request to process data and return results. Kusto queries are made of one or more query statements. The most common statements include the Tabular statements, which comprise of one or many operators. These operators are separated by pipe (|) operators.
Every KQL query results in a Tabular output which can then be converted into visuals depending upon your choices.
Some of the visuals present at the explorer are: Pie Chart, Donut Chart, Bar Graphs, Area and Line Charts.
These visuals can also be obtained using the KQL query using the “render” operator followed by the type of graph needed, viz. bar, line, area.
Visualize Data using Azure Dashboard
The main purpose of Data Visualization is to convey the hidden information in the underlying data.
The more you hammer the data the more it will yield the result, showing the never seen before results.
The interactive dashboards allow the end-users to explore the data and understand certain areas that might help drive the business and also identify those areas that need special attention. There are a lot of different visualizer tools that meet the demand of the business needs. One such tool is the Azure Dashboards.
The tabular data that forms the result of the analysis using KQL can be converted into visuals for storytelling. Azure Dashboards provide lots of different customization and allow the addition of different types of visuals. Some of these visuals include:
- Markdown Cells
- Alerts Metrics
- Resource Counters
- KQL Visuals
Once the tabular data is generated, it can easily be converted into visuals, and then it can be pinned to the Azure Dashboard.
Every account in azure has a default private dashboard, which has some default visuals in it. Once the visuals from the KQL explorer are pinned to the dashboard, the dashboard can be shared with any specific resource group and the members of the resource group will then have the access to it.
Azure Dashboards offer some customizations to their visuals, including fonts sizing, labeling, and adding links to different dashboards. Currently, navigation through dashboards is not possible in Azure Dashboards unlike PowerBI and Tableau, but we can achieve this by adding a markdown cell.
The markdown cell is a simple visual to represent any form of HTML text. Add the link to the destination dashboards and you are good to go. The markdown link opens the dashboard on a new page by default.
Filters in Azure Dashboards as similar to any other BI tools filter, with visual level customization. The filter at the tile level can overwrite the filter at the level of the dashboard. Some of the filters include time filters, text filters, category filters.
Azure Dashboards are a really powerful tool for any business to track its productivity. KQL offers far more Data handling capabilities as compared to SQL and is often preferred over SQL for Big Data Analysis on Azure.
Overall Data Analysis with KQL is simple and easy and Data Visualization with Azure Dashboards offers lots of flexibility.
For more info follow these links:
