Lens for drag-and-drop analysis in Elasticsearch - Step-by-Step Execution

Concept Flow - Lens for drag-and-drop analysis

Open Lens Interface

↓

Select Data Source

↓

Drag Field to Visualization Area

↓

Lens Auto-Detects Visualization Type

↓

Adjust Visualization Settings

↓

View Updated Visualization

↓

Repeat Drag-and-Drop for More Fields

↓

Save or Export Analysis

Lens lets you drag fields from your data to create visualizations quickly, auto-selecting the best chart type and updating it as you add more fields.

Execution Sample

Elasticsearch

1. Open Lens in Kibana
2. Choose an index pattern
3. Drag 'timestamp' to X-axis
4. Drag 'count' to Y-axis
5. Lens shows a time series chart

This example shows how dragging fields creates a time series chart automatically.

Execution Table

Step	Action	Input Field	Lens Response	Visualization State
1	Open Lens Interface	-	Lens ready for input	Empty canvas
2	Select Data Source	index-pattern: logs-*	Fields loaded	Empty canvas
3	Drag field	timestamp	Assign to X-axis	X-axis set to timestamp
4	Drag field	count	Assign to Y-axis	Y-axis set to count, chart type: line
5	Lens auto-selects chart	-	Line chart displayed	Time series line chart shown
6	Drag field	host.keyword	Add as breakdown	Chart splits by host.keyword
7	Adjust settings	Change color palette	Colors updated	Chart colors changed
8	Save analysis	-	Saved successfully	Analysis saved
9	Exit	-	-	Lens closed

💡 User finishes analysis and closes Lens interface

Variable Tracker

Variable	Start	After Step 3	After Step 4	After Step 6	Final
X-axis field	None	timestamp	timestamp	timestamp	timestamp
Y-axis field	None	None	count	count	count
Breakdown field	None	None	None	host.keyword	host.keyword
Chart type	None	None	line	line	line
Visualization state	Empty	X-axis set	Line chart	Split by host.keyword	Final saved chart

Key Moments - 3 Insights

Why does Lens automatically choose a line chart after dragging timestamp and count?

Lens detects that timestamp is a time field and count is numeric, so it picks a line chart to best show trends over time, as seen in execution_table row 5.

What happens if you drag a keyword field after setting X and Y axes?

Lens adds the keyword field as a breakdown or split dimension, updating the chart to show multiple lines or segments, shown in execution_table row 6.

Can you change the chart type manually after Lens auto-selects it?

Yes, you can adjust visualization settings like chart type or colors anytime, as shown in execution_table row 7.

Visual Quiz - 3 Questions

Look at the execution_table, what is the visualization state after step 4?

A Y-axis set to count, chart type: line

B X-axis set to timestamp only

C Y-axis set to count only

D Chart splits by host.keyword

💡 Hint

Check the Visualization State column at step 4 in execution_table

At which step does Lens add a breakdown field to the visualization?

A Step 3

B Step 4

C Step 6

D Step 7

💡 Hint

Look for when 'host.keyword' is dragged in execution_table

If you drag a numeric field instead of 'count' at step 4, how would the visualization state change?

A Lens would show a pie chart

B Lens would still show a line chart with the new numeric field on Y-axis

C Lens would remove the X-axis field

D Lens would not update the chart

💡 Hint

Lens auto-selects chart types based on field types, see step 5 in execution_table

Concept Snapshot

Lens lets you drag fields from your data to build visualizations.
Drag a time field to X-axis and a numeric field to Y-axis.
Lens auto-selects the best chart type (like line chart for time series).
Add keyword fields to split data by categories.
Adjust colors and settings anytime.
Save your analysis when done.

Full Transcript

Lens is a tool in Kibana that helps you create visualizations by dragging fields from your data. First, you open Lens and select your data source. Then you drag a time field like 'timestamp' to the X-axis and a numeric field like 'count' to the Y-axis. Lens automatically chooses a line chart to show trends over time. You can add more fields, such as a keyword field, to split the chart into categories. You can also change colors and other settings. Finally, you save your analysis. This step-by-step process helps you explore data visually without writing code.