Dashboard creation in Elasticsearch - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ visualization

intermediate

Identify the correct Kibana visualization type for time series data

You want to create a dashboard showing sales trends over time using Elasticsearch data in Kibana. Which visualization type is best suited for this purpose?

A Pie chart

B Tag cloud

C Data table

D Line chart

💡 Hint

Think about which chart shows changes over time clearly.

Line charts are ideal for showing trends over time because they connect data points chronologically, making it easy to see increases or decreases.

❓ dax_lod_result

intermediate

Calculate total sales for a specific region using Elasticsearch SQL

Given an Elasticsearch SQL query to calculate total sales for the 'West' region, what is the correct query to get the sum of sales?

Elasticsearch

SELECT region, SUM(sales) AS total_sales FROM sales_data WHERE region = 'West' GROUP BY region

A SELECT SUM(sales) AS total_sales FROM sales_data WHERE region = 'West'

B SELECT region, SUM(sales) FROM sales_data GROUP BY region HAVING region = 'West'

C SELECT SUM(sales) FROM sales_data WHERE region = 'West' GROUP BY region

D SELECT region, sales FROM sales_data WHERE region = 'West' SUM(sales)

💡 Hint

Focus on summing sales only for the 'West' region without grouping by region.

Option A correctly sums sales filtered by region 'West' without unnecessary grouping.

❓ data_modeling

advanced

Best practice for indexing time-based data in Elasticsearch for dashboards

You have large volumes of time-stamped log data. What is the best practice for indexing this data to optimize dashboard performance?

A Store all data in one index and filter with queries only

B Use a single index for all data regardless of time

C Create time-based indices, such as daily or monthly indices

D Index data without timestamps to reduce index size

💡 Hint

Think about how Elasticsearch handles large datasets efficiently over time.

Creating time-based indices allows efficient querying and management of large time-series data, improving dashboard responsiveness.

🔧 Debug

advanced

Fix the Kibana dashboard filter not applying correctly

You created a dashboard filter for 'product_category' but it does not filter the visualizations. What is the most likely cause?

A The field 'product_category' is not mapped as keyword in Elasticsearch

B The filter syntax in Kibana is correct but the dashboard needs refresh

C The filter is applied but visualizations are set to ignore filters

D The Elasticsearch cluster is down

💡 Hint

Check how fields are mapped in Elasticsearch for filtering.

Fields not mapped as keyword cannot be filtered properly in Kibana filters because they are analyzed text fields.

🎯 Scenario

expert

Design a dashboard to monitor real-time error rates with alerting

You need to build a Kibana dashboard that shows real-time error rates from logs and triggers alerts when error counts exceed thresholds. Which approach is best?

A Build a tag cloud of error messages and rely on visual inspection

B Use a line chart with a date histogram aggregation and set up Kibana alerting on the error count metric

C Use a data table with all log entries and filter errors manually

D Create a pie chart showing error types and manually check the dashboard hourly

💡 Hint

Consider automation and real-time monitoring capabilities.

Line charts with date histograms show trends over time, and Kibana alerting automates notifications when thresholds are crossed.