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Azure Data Explorer is a fast and highly scalable data exploration service for log and telemetry data. Azure Data Explorer provides a web application that enables you to run queries and build dashboards. Dashboards are available in the stand-alone web application, the Azure Data Explorer web UI. Azure Data Explorer is also integrated with other dashboard services like Power BI and Grafana.
Azure Data Explorer dashboards provide three main advantages:
- Natively export queries from the Azure Data Explorer web UI to Azure Data Explorer dashboards.
- Explore the data in the Azure Data Explorer web UI.
- Optimized dashboard rendering performance.
The following image depicts an Azure Data Explorer dashboard.
Important
Your data is secure. Dashboards and dashboard-related metadata about users is encrypted at rest using Microsoft-managed keys.
Prerequisites
- A Microsoft account or an Azure Active Directory user identity. An Azure subscription isn't required.
- Create an Azure Data Explorer cluster and database.
- Sign in to the Azure Data Explorer web UI and add a connection to your cluster.
Create a dashboard
You can create a dashboard in the Azure Data Explorer web UI using the following steps. Alternatively, you can create a dashboard by importing a dashboard file.
In the navigation bar, select Dashboards (Preview) and then select New dashboard.
Enter a dashboard name and then select Create.
Add data source
Add a data source for the dashboard.
Select Data sources.
(Video) Create An Azure Data Explorer Cluster, Ingest Data and VisualizeIn the Data sources pane, select New data source.
In the Create new data source pane:
- Enter a Data source name.
- Enter the Cluster URI region and then select Connect.
- Select the Database from the drop-down list.
- Enter a value for Query results cache max age to enable query results cache on all queries of this data source. The max age can be in units of seconds, hours, or days.
- Select Apply.
Use Parameters
Parameters significantly improve dashboard rendering performance, and enable you to use filter values as early as possible in the query. Filtering is enabled when the parameter is included in the query associated with your tile(s). For more information about how to set up and use different kinds of parameters, see Use parameters in Azure Data Explorer dashboards.
Select Parameters on the top bar.
Select the + New parameter button in the Parameters pane.
Enter values for all the mandatory fields and select Done. In this example, we're using a query-based parameter that allows you to select one or more states and see events associated with this selection.
| Field | Description |
|---|---|
| Parameter type | One of the following: - Single Selection: Only one value can be selected in the filter as input for the parameter. - Multiple Selection: One or more values can be selected in the filter as input(s) for the parameter. - Time Range: Allows creating additional parameters to filter the queries and dashboards based on time. Every dashboard has a time range picker by default. - The parameter type you select will affect the way you write any query that's based on this parameter. |
| Variable name | The name of the parameter to be used in the query. |
| Data type | The data type of the parameter values. |
| Pin as dashboard filter | The option to pin the parameter-based filter to the dashboard. |
| Source | The source of the parameter values: - Fixed values: Manually introduced static filter values. - Query: Dynamically introduced values using a KQL query. |
| Value column | Results column to be used as parameter values. Only applicable for query-based parameters. |
| Label column | Results column to be used for parameter labels. Only applicable for query-based parameters. |
| Add empty "Select all" value | Applicable only to single selection and multiple selection parameter types. Used to retrieve data for all the parameter values. |
| Display name | The name of the parameter shown on the dashboard or the edit card. |
| Default value | The default parameter value. |
Parameter query
The following is an example of a query using the parameter defined in Use parameters.
Select the source data from the drop-down bar.
Enter your query and then select Run.
Select Apply changes.
Note
The parameter query is used to generate dynamically introduced values as parameters using a KQL query. It's not the query used for generating the dashboard visual.
For more information about generating parameter queries, see Create a parameter.
Add tile
Add tile uses Kusto Query Language snippets to retrieve data and render visuals. Each tile/query can support a single visual.
Select Add tile from the dashboard canvas or the top menu bar.
In the Query pane,
Select the data source from the drop-down menu.
Type the query, and the select Run. For more information about generating queries that use parameters, see Use parameters in your query.
Select + Add visual.
In the Visual formatting pane, select Visual type to choose the type of visual.
Select Apply changes to pin the visual to the dashboard.
You can resize the visual and then Save changes to save the dashboard.
(Video) ADX Dashboards
Use the share menu to grant permissions for an Azure Active Directory (Azure AD) user or Azure AD group to access the dashboard, change a user's permission level, and share the dashboard link.
Important
To access the dashboard, a dashboard viewer needs the following:
- Dashboard link for access
- Dashboard permissions
- Access to the underlying database in the Azure Data Explorer cluster
Manage permissions
Select the Share menu item in the top bar of the dashboard.
Select Manage permissions from the drop-down.
Grant permissions
To grant permissions to a user in the Dashboard permissions pane:
- Write the user's name or email in Add new members box.
- In the Permission level, select one of the following values: Can view or Can edit.
- Select Add.
Change a user permission level
To change a user permission level in the Dashboard permissions pane:
- Either use the search box or scroll the user list to find the user.
- Change the Permission level as needed.
To share the dashboard link, do one of the following:
- Select Share and then select Copy link
- In the Dashboard permissions window, select Copy link.
Export dashboards
Use the file menu to export a dashboard to a JSON file. Exporting dashboard can be useful in the following scenarios:
- Version control: You can use the file to restore the dashboard to a previous version.
- Dashboard template: You can use the file as template for creating new dashboards.
- Manual editing: You can edit the file to modify the dashboard. The file can be imported back to the dashboard.
To export a dashboard, in the dashboard, select File > Export to file.
The file contains the dashboard data in JSON format, an outline of which is shown in the following snippet.
{ "id": "{GUID}", "eTag": "{TAG}", "title": "Dashboard title", "tiles": [ { "id": "{GUID}", "title": "Tile title", "query": "{QUERY}", "layout": { "x": 0, "y": 7, "width": 6, "height": 5 }, "pageId": "{GUID}", "visualType": "line", "dataSourceId": "{GUID}", "visualOptions": { "xColumn": { "type": "infer" }, "yColumns": { "type": "infer" }, "yAxisMinimumValue": { "type": "infer" }, "yAxisMaximumValue": { "type": "infer" }, "seriesColumns": { "type": "infer" }, "hideLegend": false, "xColumnTitle": "", "yColumnTitle": "", "horizontalLine": "", "verticalLine": "", "xAxisScale": "linear", "yAxisScale": "linear", "crossFilterDisabled": false, "crossFilter": { "dimensionId": "dragX-timeRange", "parameterId": "{GUID}" }, "multipleYAxes": { "base": { "id": "-1", "columns": [], "label": "", "yAxisMinimumValue": null, "yAxisMaximumValue": null, "yAxisScale": "linear", "horizontalLines": [] }, "additional": [] }, "hideTileTitle": false }, "usedParamVariables": [ "{PARAM}" ] } ], "dataSources": [ {} ], "$schema": "https://dataexplorer.azure.com/static/d/schema/20/dashboard.json", "autoRefresh": { "enabled": true, "defaultInterval": "15m", "minInterval": "5m" }, "parameters": [ {} ], "pages": [ { "name": "Primary", "id": "{GUID}" } ], "schema_version": "20"}To create new dashboard from a file
You can use a dashboard file to create a new dashboard, as follows:
In the main dashboard page, select New dashboard > Import from file.
Select the file to import.
Enter a dashboard name, and then select Create.
To update or restore an existing dashboard from a file
You can update an existing dashboard, or restore a previous version, as follows:
In the dashboard, select File > Replace with file.
Select the file to update the dashboard.
Select Save changes.
Enable auto refresh
Select Edit in dashboard menu to switch to edit mode.
Select Auto refresh.
Toggle the option so auto refresh is Enabled.
Select values for Minimum time interval and Default refresh rate.
Select Apply and then Save the dashboard.
(Video) Azure Data Explorer L300 workshop – Time Series analytics, high concurrency apps and visualization
Note
- Select the smallest minimum time interval to reduce unnecessary load on the cluster.
- A dashboard viewer:
- Can change the minimum time intervals for personal use only.
- Can't select a value which is smaller than the Minimum time interval specified by the editor.
Next Steps
- Use parameters in Azure Data Explorer dashboards
- Customize dashboard visuals
- Query data in Azure Data Explorer
FAQs
How do I visualize data in Azure? ›
You can create a dashboard in the Azure Data Explorer web UI using the following steps. Alternatively, you can create a dashboard by importing a dashboard file. In the navigation bar, select Dashboards (Preview) and then select New dashboard. Enter a dashboard name and then select Create.
Which tool can you use to visualize Azure data in the form of interactive dashboards? ›You can use Redash to build dashboards and visualize data. Set up Azure Data Explorer as a data source for Redash, and then visualize the data.
What kind of information can you see using Azure dashboards? ›Dashboards are a focused and organized view of your cloud resources in the Azure portal. Use dashboards as a workspace where you can monitor resources and quickly launch tasks for day-to-day operations. Build custom dashboards based on projects, tasks, or user roles, for example.
How do I read data from Azure Data Explorer? ›- Create database: Create a cluster and then create one or more databases in that cluster. ...
- Ingest data: Load data into database tables so that you can run queries against it.
- Develop your research question.
- Get or create your data.
- Clean your data.
- Choose a chart type.
- Choose your tool.
- Prepare data.
- Create chart.
The two most common formats for visualizing data are dashboards and reports. This allows you to showcase several different images to paint a more compelling story. In fact, the average dashboard, according to our experts, contains 3-5 charts or graphs.
What is the best dashboard visualization tool and why? ›- Microsoft Power BI: Best for Business Intelligence.
- Tableau: Best for Interactive Charts.
- Qlik Sense: Best for Artificial Intelligence.
- Klipfolio: Best for Custom Dashboards.
- Looker: Best for Visualization Options.
- Zoho Analytics: Best for Zoho Users.
- Domo: Best for Custom Apps.
To add Power BI visualizations to personal dashboards in your model-driven app, you must: Enable Power BI visualizations for your organization in Settings > Administration > System Settings > Reporting tab > Allow Power BI visualization embedding.
What information does a dashboard provide? ›Dashboard uses
The main use of a dashboard is to show a comprehensive overview of data from different sources. Dashboards are useful for monitoring, measuring, and analyzing relevant data in key areas.
Azure Service Dashboard is a online platform where Azure Cloud Services users / subscribers can view and monitor status of current services provisioned. Microsoft Azure Services Dashboard primarily allows Azure subscribers to view the health and operational status of each overall Azure service separately.
What is Azure Data Explorer used for? ›
Overview. Azure Data Explorer is a fast, fully managed data analytics service for real-time analysis on large volumes of data streaming from applications, websites, IoT devices, and more.
Is Azure Data Explorer a database? ›Azure Data Explorer is a distributed database running on a cluster of compute nodes in Microsoft Azure. It is based on relational database management systems (RDBMS), supporting entities such as databases, tables, functions, and columns.
How do I extract data from an Azure database? ›- To export a database using the Azure portal, open the page for your database and select Export on the toolbar.
- Specify the BACPAC filename, select an existing Azure storage account and container for the export, and then provide the appropriate credentials for access to the source database. ...
- Select OK.
...
Data storage
- It allows multiple Compute nodes in the cluster to cache the data shard, without complex change management coordination between them.
- It allows multiple Compute clusters to refer to the same data shard.
The utility of data visualization can be divided into three main goals: to explore, to monitor, and to explain. While some visualizations can span more than one of these, most focus on a single goal.
What are the 7 stages of visualizing data? ›- 1 6.
- Step 1: Define a clear purpose.
- Step 2: Know your audience.
- Step 3: Keep visualizations simple.
- Step 4: Choose the right visual.
- Step 5: Make sure your visualizations are inclusive.
- Step 6: Provide context.
- Step 7: Make it actionable.
Data Visualization Guide
Form follows function. Focus on how your audience needs to use the data, and let that determine the presentation style. Provide the necessary context for data to be interpreted and acted upon appropriately. Keep it simple.
In Big Data applications, it is difficult to conduct data visualization because of the large size and high dimension of big data. Most of current Big Data visualization tools have poor performances in scalability, functionalities, and response time.
What is the purpose of using a dashboard for data visualization? ›The purpose of using dashboards for data visualization is for users to get a bird's-eye view of the data from each of these platforms in one centralized location, with the ability to quickly understand what it means for the business.
What is the difference between data visualization and dashboard? ›To recap, Data Visualization is the process of presenting information in a visual form. Its purpose is to promote quick and easy understanding of the information. A Dashboard is a snapshot, or summary, of a large set of information. Data Visualization and a Dashboard are often used together.
What is the easiest data visualization tool to use? ›
Some of the best data visualization tools include Google Charts, Tableau, Grafana, Chartist, FusionCharts, Datawrapper, Infogram, and ChartBlocks etc. These tools support a variety of visual styles, be simple and easy to use, and be capable of handling a large volume of data.
What are the three types of dashboards? ›Types of dashboards (and how to choose the right one for you) There are three types of dashboards: operational, strategic, and analytical.
How do you visualize data in dashboard? ›A data visualization dashboard is an interactive dashboard that allows you to track key metrics across multiple marketing channels, visualize the data points, and create reports for your clients that outline all your hard work.
What 5 key metrics would you want to display on a data dashboard? ›...
- Lead Conversion Ratio. ...
- Customer Acquisition Cost (CAC) ...
- Customer Churn Rate. ...
- Customer Lifetime Value (LTV) ...
- Number of Sales Opportunities. ...
- Sales Target. ...
- Sales Growth.
- Understand your audience. When you're creating a data visualization, remember – it's not about you. ...
- Communicate to a specific audience. ...
- Choose the best visual(s) ...
- Use proper design principles. ...
- Provide context for visualizations.
- Choose the right charts and graphs for the job. ...
- Use predictable patterns for layouts. ...
- Tell data stories quickly with clear color cues. ...
- Incorporate contextual clues with shapes and designs. ...
- Strategically use size to visualize values.
Dashboard Tab contains "Analysis View" and "Dashboard View" enabling user to analyze and display ALM data in various formats. Let us understand the importance of each one of them in detail.
Which feature do you find most important in a dashboard? ›Dynamic Filters
Also, known as dashboard filters or chart filters, dynamic filters is one of the most important dashboard features. Dynamic filters allow users to dynamically filter the data used in one or more dashboard widgets, enabling users to slice & dice data on the fly.
- Step 1: Planning. During the Planning phase, you and your team will determine key factors to guide the discovery and design phases.
- Step 2: Data Discovery. ...
- Step 3: Design. ...
- Step 4: Implementation.
Great dashboards are clear, interactive, and user-friendly. They need to communicate information at a glance through efficient data visualizations that will enable users to extract actionable insights, identify trends and patterns, and find improvement opportunities through a friendly online data analysis process.
Why do you need a dashboard? ›
Dashboards offer a method of consolidating company data into one unified location with secure data storage. Dashboards are designed to offer a comprehensive overview of company performance, and do so through the use of data visualization tools like charts and graphs.
What are the 3 types of data that can be stored in Azure? ›Azure storage types include objects, managed files and managed disks. Customers should understand their often-specific uses before implementation. Each storage type has different pricing tiers -- usually based on performance and availability -- to make each one accessible to companies of every size and type.
Why do we need Azure storage explorer? ›Additional resources. Azure Storage Explorer allows you to quickly view all the storage services under your account. You can browse through, read, and edit data stored in those services through a user-friendly graphical interface.
What are the 4 types of database? ›...
The other three include:
- hierarchical database systems.
- network database systems.
- object-oriented database systems.
ADX contains native support for creation, manipulation, and analysis of multiple time series. In this topic, learn how Azure Data Explorer is used to create and analyze thousands of time series in seconds, enabling near real-time monitoring solutions and workflows.
Which language is Azure Data Explorer? ›Azure Data Explorer language extensions that are currently supported are Python and R.
How do you pull data from a database? ›- Load your phpMyAdmin.
- Select the database to export.
- Click on the Export tab.
- Select the Custom option to have complete control of the data your export.
- Specify the destination file on your computer.
...
Save as Excel from Azure Data Studio
- Click the 'Save As Excel' icon.
- Choose folder to save file to.
- Name file.
- Save.
In SQL, to retrieve data stored in our tables, we use the SELECT statement. The result of this statement is always in the form of a table that we can view with our database client software or use with programming languages to build dynamic web pages or desktop applications.
How do I ingest data into Azure Data Explorer? ›- Set batching policy (optional) The batching manager batches ingestion data based on the ingestion batching policy. ...
- Set retention policy. ...
- Create a table. ...
- Create schema mapping. ...
- Set update policy (optional) ...
- Ingest data.
What is the advantage of using storage Explorer? ›
Azure Storage Explorer Preview is a standalone app that allows you to easily work with Azure Storage data - from any platform, anywhere. It creates and manages blobs, tables, queues, generate SAS keys, and more.
Is Azure data visualization tool? ›Power BI allows you to visualize your data and gain deeper insight by creating interactive and immersive dashboards and reports. In this course, you'll learn how to use Microsoft Power BI to optimize data, load datasets, and create dashboards.
Does Azure have a graph database? ›Azure Cosmos DB supports horizontally scalable graph databases that can have an unlimited size in terms of storage and provisioned throughput. As the graph database scale grows, the data will be automatically distributed using graph partitioning.
Does Azure have a data modeling tool? ›Data Modeling in Azure is a new preview service in Microsoft Azure where semantic Data Models can be hosted. Users in your organization can then connect to your Data Models via tools such as Excel, Power BI, and others to generate reports and perform ad-hoc data analysis.
Does Microsoft have a data visualization tool? ›Data visualization – Microsoft Visio.
What are data visualization tools used for? ›Data visualization tools are software applications that render information in a visual format such as a graph, chart, or heat map for data analysis purposes. Such tools make it easier to understand and work with massive amounts of data.
What is the best graph database? ›- Neo4j.
- ArangoDB.
- Dgraph.
- Stardog.
- Tigergraph.
- FaunaDB.
- GraphDB.
- RDFox.
Or, from the dashboard, you can add a Chart for work items widget and choose a shared query and set the chart parameters. Chart types include status—pie, bar, column, stacked bar, and pivot—and trend—stacked area, line, and area—charts.
Why is graph database not popular? ›Additionally, they were considered to be “academic” databases, designed to build logical analysis systems, and not necessarily useful for business purposes. Though graph databases could provide useful results, in general they were complicated, time-consuming, and not terribly user-friendly.
What are the 3 types of data Modelling? ›What are the types of data modeling? The three primary data model types are relational, dimensional, and entity-relationship (E-R). There are also several others that are not in general use, including hierarchical, network, object-oriented, and multi-value.
Does Azure have an ETL tool? ›
With Azure Data Factory, it's fast and easy to build code-free or code-centric ETL and ELT processes.
What are the four types of data visualizations? ›The main types of data visualization include charts, graphs and maps in the form of line charts, bar graphs, tree charts, dual-axis charts, mind maps, funnel charts and heatmaps.
Is Excel enough for data visualization? ›Excel is one of the best data visualization tools for businesses and professionals. However, this freemium spreadsheet tool comes with very basic charts and graphs, such as Pareto and Grouped Bar Charts.
What is Microsoft data visualization? ›An interactive data visualization tool for your business
Microsoft Power BI is a cloud-based business intelligence platform that empowers you to aggregate, analyze, visualize, and share data.