Data explorer quick start

You're in the right place if you want to see what Data explorer can do and learn a little about writing your own queries.

You have two options here:

• Start with a template—An easy intro
• Start from scratch—A little harder

Start with a template

Starting with Dynatrace version 1.251, Data explorer opens with a Start with a template section. This is the fastest and easiest way to get up and running with Data explorer.

To get started with a template

1. In the Dynatrace menu, go to Data explorer.

2. In the Start with a template section, select a template.

   When you select a template, Dynatrace automatically fills in the query definition, configures the visualization settings, and runs the query.

3. Hover over visualization elements to see tooltips.

4. Select visualization elements to access drilldown actions.

5. Experiment with the query definition on the Build or Code tab. After you make a change, select Run query to see what happens.

6. Experiment with the Settings panel on the right. Tweak some settings and see what happens.

7. When you come up with something you like, select Pin to dashboard to add the query to a dashboard.

   • If you don't have a dashboard, just select Create new dashboard when the Where do you want to pin to? message pops up.
   • You can pin multiple versions of your work to your dashboard so you can them side by side.

If you're ready to start exploring a little more, try starting from scratch.

Start from scratch

Use this procedure to get hands-on experience with the Data explorer.

In this walkthrough, you'll:

• Create a simple metric visualization from scratch
• Use the visualization directly in Data explorer
• Pin the visualization to a dashboard as a tile

Create a visualization from scratch

1. In the Dynatrace menu, go to Data explorer.

2. On the Build tab, add a metric to your query.

   • Select a metric such as CPU usage % (builtin:host.cpu.usage).

     When you browse the list of metrics, an overview of the highlighted metric is displayed. To see details about that metric, select View all metric information. This opens the Metrics browser in a new tab (so you don't lose your work in the Data explorer) with lots of useful details about the selected metric.

     

     Metric details available in the 'Metrics browser'

     Field	Description
     Metric name	The name of the metric in the user interface.
     Metric key	The fully qualified key of the metric. If a transformation has been used, it is reflected in the metric key.
     Entity type	Entity type for this metric.
     Description	A short description of the metric.
     Tags	Tags allow further grouping of metrics.
     Created	The timestamp when the metric was created.
     Last written	The timestamp when the metric was last written.
     DDU billing	Whether the metric is subject to Davis data unit (DDU) consumption.
     Unit	The unit of the metric.
     Minimum value	The known lower boundary value for the metric.
     Maximum value	The known upper boundary value for the metric.
     Default aggregation	The default aggregation for this metric.
     Aggregations	The list of allowed aggregations for this metric.
     Dimensions	The fine metric division (for example, process group and process ID for a process-related metric).
     Transformations	Possible transform operators.

   • Choose an aggregation (for example, Average, Minimum, or Maximum)

   • Select Split by dimensions. In this example (CPU usage %), we split by host to see CPU usage per host.

   • Specify Filter by criteria as needed. In this example, we leave it empty.

   For details on building a query, see Query components and concepts and Examples.

3. optional To review or edit the code for your query, switch to the Code tab, which is the advanced query editor.

4. Add and delete metrics as needed.

   • A query can have up to 10 rows.

   • To add a new empty row, select Add metric and then repeat the previous step to define that row.

   • To make a copy of a metric that you have already added to the query, select > Duplicate and then edit the copy as needed.

     

   • To delete a metric, select > Delete.

5. optional To add or remove metric transformations for a row, select the transformations (+) button and then select or clear checkboxes as needed.

   

6. Select Run query to take a first look at the visualization.

7. Use the Settings panel to configure your visualization.

   • The visualization is updated with each change.
   • Choose from several visualization types:
     • Graph
     • Stacked column
     • Stacked area
     • Pie
     • Single value
     • Table
     • Top list
     • Heatmap
     • Honeycomb

When you are satisfied with your visualization, you can use it within Data explorer immediately or pin it to a dashboard for future use.

Use the visualization in Data explorer

Visualization elements are active. For example:

• To see details in tooltips, hover over visualization elements
• To drill down from a problematic (red) element, select it.
• To hide or show a visualization element, select the corresponding label in the visualization legend

When you're done using your visualization (for now, anyway), you need to decide whether to discard it or save it.

• To discard your visualization (and the query that generated it), just navigate away from Data explorer.
• To save your visualization and query for future use, you need to pin the visualization to a dashboard. See below.

Pin the visualization to a dashboard

To save the visualization as a dashboard tile, select Pin to dashboard.

To return from the dashboard to Data explorer with the visualization open for viewing and editing, open the menu in the upper-right corner of the tile and select Configure tile in Data Explorer. Now two buttons are displayed in the Results section of the Data explorer:

• Save changes to dashboard—saves the visualization to the same tile and dashboard you used to open the Data explorer. If you have made any changes, they will update the tile on your dashboard.
• Pin to dashboard—saves the visualization as a tile on a different dashboard. You might want to pin the same visualization (perhaps with filtering differences) to various dashboards.

For details about pinning tiles to dashboards, see Pin tiles to your dashboard.

What's next?

If you're ready for the technical details, see:

• Data explorer—learn the details of query construction
• Data explorer Code tab (advanced query editor)—learn how to edit queries on the Code tab