Lens for drag-and-drop analysis in Elasticsearch - Mini Project: Build & Apply

Lens for drag-and-drop analysis

📖 Scenario: You work as a data analyst using Elasticsearch. You want to create a simple Lens visualization that lets you drag and drop fields to analyze sales data easily.

🎯 Goal: Build a Lens configuration JSON that defines a drag-and-drop analysis for sales data, showing total sales by product category.

📋 What You'll Learn

Create a base index pattern for sales data

Add a configuration for a metric to sum sales amounts

Add a configuration for a bucket to group by product category

Output the final Lens configuration JSON

💡 Why This Matters

🌍 Real World

Elasticsearch Lens helps analysts quickly explore and visualize data by dragging and dropping fields without writing complex queries.

💼 Career

Data analysts and engineers use Lens configurations to build dashboards and reports that help businesses understand trends and make decisions.

1

Create the base index pattern

Create a variable called indexPattern and set it to the string "sales-data" representing the Elasticsearch index pattern.

Elasticsearch

# Create a variable called indexPattern and set it to "sales-data"
# Your code here

Need a hint?

The index pattern is the name of the Elasticsearch index you want to analyze.

2

Add metric configuration for total sales

Create a dictionary called metric with keys operationType set to "sum" and field set to "sales_amount" to sum the sales amounts.

Elasticsearch

indexPattern = "sales-data"
# Create a dictionary called metric with operationType "sum" and field "sales_amount"
# Your code here

Need a hint?

The metric defines what calculation Lens will do on the sales_amount field.

3

Add bucket configuration for product category

Create a dictionary called bucket with keys operationType set to "terms" and field set to "product_category" to group data by product category.

Elasticsearch

indexPattern = "sales-data"
metric = {"operationType": "sum", "field": "sales_amount"}
# Create a dictionary called bucket with operationType "terms" and field "product_category"
# Your code here

Need a hint?

The bucket groups the data by product category for the Lens visualization.

4

Create and print the Lens configuration JSON

Create a dictionary called lensConfig with keys indexPattern, metric, and bucket using the variables you created. Then print lensConfig.

Elasticsearch

indexPattern = "sales-data"
metric = {"operationType": "sum", "field": "sales_amount"}
bucket = {"operationType": "terms", "field": "product_category"}
# Create lensConfig dictionary with indexPattern, metric, and bucket
# Print lensConfig
# Your code here

Need a hint?

The final Lens configuration combines all parts and shows the JSON structure.