Build the Perfect Dashboard using Kibana

Big data analytics is going from nice-to-have to necessity for all types of businesses these days. By capturing and analyzing relevant data, businesses can turnaround a mountain of data into informed business moves.

Put another way: a thorough analysis of big data can help businesses streamline operations, increase profits, and even ensure happier customers.

Not surprisingly, Big Data Analysis is on the radar of major businesses these days. 

So, that begs the question, in a world where the data is available in an unstructured or semi-structured format, how do you analyze and streamline this data? How will businesses mine required information from unstructured data?  

This is where the ELK stack helps.  ELK stack is going to gain some serious traction in the coming years because it’s programmed to take the guesswork out of big data analysis. In short, big data analysis works best when it combines with ELK Stack.

The ELK stack involves Elasticsearch, Logstash, and Kibana, the three open-source projects, that helps in end-to-end big data analysis.   

Before we start talking about Kibana in detail, let’s touch upon Elasticsearch briefly given that Kibana works with Elasticsearch.

First off: What’s Elasticsearch?

Products, involving eCommerce and search engines, which rely on massive databases, continually face product information retrieval issues. This leads to poor user experience, which turns potential users off.

Enter Elasticsearch. Elasticsearch is a database that stores, retrieves, and manages unstructured and semi-structured data.

Presently, businesses are looking for alternatives to store data that enables quick data retrieval. This can be achieved by leveraging NoSQL. Elasticsearch is one such NoSQL distributed database.    

The Importance of Elasticsearch

In Elasticsearch, data is stored in JSON document form. And you can query them for retrieval. It automatically indexes the data unless you provide mapping as per your needs.  Elasticsearch leverages Lucene StandardAnalyzer for indexing and automatic guessing.  

Every feature of Elasticsearch is exposed as a REST API:

• Index API: Documents the index
• Get API: Retrieves the document
• Search API: Submits query and gets results
• Mapping API: Defines mapping

In Elasticsearch, with its query domain-specific language, the query needs to be specified in JSON format. 

Given that data is scattered among multiple tables and fetching meaningful data takes time, especially when the data is vast, this is where Elasticsearch helps out.     

Now, let’s start with Kibana?

What’s Kibana?

Kibana is an open-source visualization and analytics platform that helps understand large volumes of data through the building of dynamic dashboards that facilitates the creation of histograms, line graphs, pie charts, maps, and more.

It works with Elasticsearch and facilitates visualization of data to be indexed on an Elasticsearch cluster.

The platform helps search, view, and even interact with data stored in Elasticsearch indices. Plus, it enables you to perform advanced data analysis and also visualize data in the form of charts, tables, and maps.

Most importantly, setting up Kibana is easy. You can install Kibana and start exploring your Elasticsearch indexes in minutes. No code, no additional infrastructure required.

Kibana Dashboard Offers the Following Features Right off the Bat:

Leverage the Map Service to visualize custom location data on a schematic of your choosing.

Time Series Analysis

Our smartly curated time series UIs perform advanced time series analysis based on your Elasticsearch data. You can even report queries, witness transformations and, visualize the entire time series analysis.

Connect the Dots in Data

The dashboard will help you interpret the uncommon relationships in your Elasticsearch data.

Explore Inconsistencies with Machine Learning

Figure out the inconsistencies in your Elasticsearch data and zero down the properties that influence with machine learning features.

Color your Canvas

Bring out your creative side. Play with logos, colors and different design elements to stand out.  Canvas enables you to get creative with your live data.  

No matter what keep it simple in the launch phase  

While setting up the Kibana dashboard, you shouldn’t consider any fancy visualization with diverse sub aggregations. Start simple and then grow from there. 

For any visual, use the basic default setting to breakdown the top 3 or 5 results for a specific field.  Then preview the results. If it requires further development, continue development using different configuration options.

Don’t complicate your visuals. In short, don’t combine a correctly done visual with a sub aggregation of unnecessary fields.

The Art of Kibana Dashboarding

Once you have your visuals lined up, it’s time to bring them under one roof, which is your comprehensive dashboard built on Kibana.  It’s easy. But then, make sure that you think twice before piling up all the visuals. Every panel has a different goal and purpose. A system monitoring dashboard works differently from a dashboard that troubleshoots an issue in production.   

The same factor has a direct effect on the number of data sources used for the dashboard. For example, multiple data sources are imperative for getting a general idea of a system, but useless when it comes to drilling down.  

Sigma offers complete ELK service. Contact or email us for your ELK service requirements.

All the images have been sourced from elastic.co.