Data analytics with Amazon ElasticSearch 

Use case


Main challenges

Organizations deploy systems and technologies that generate large volumes of both structured and unstructured data. They need to analyze the data to enhance decision making. 

Meanwhile, many companies still rely on traditional relational databases to capture, manage, and process data with low latency. These solutions lack useful data analytics capabilities to analyze large volumes and various data types at unprecedented speed. 

Some data analytics approaches fail to synchronize data across disparate sources. Besides, there is an acute shortage of professionals who understand big data analytics. 

Business/technical goals

Enterprises analyze big data for insights that improve decision-making and enhance strategic business moves. Data analytics with Amazon ElasticSearch aims to analyze logs and metrics to give insights into your IT environment performance. The solution also enables interactive investigation and automated threat detection. 


Technofy offers Data Analytics with Amazon Elastic Search (Amazon ES) as a reliable solution for log analytics, search experience, real-time application monitoring, clickstream analysis, and more. The solution enables enterprises to ingest millions of new logs and metrics each day. Amazon ElasticSearch provides multi-instance clusters configured and running in minutes. Data analytics with Amazon ElasticSearch can also scale in or out as required with proper configuration changes in the infrastructure pipelines. 
Technofy's solution allows businesses to get near-real-time insights into resource usage, system metrics, and application performance. Besides, data analytics with Amazon ElasticSearch helps companies build a great search experience for their sites. It also enables interactive investigation and automated threat detection and mitigation.   

Situation before & after the implementation


The amount of data business enterprises produce is growing at 40 to 60 percent per year. Merely storing this voluminous amount of data is not productive for an organization. 

Some companies fail to deploy solutions to analyze this data. Others implement ineffective tools to handle big data.  


Businesses using data analytics with Amazon ElasticSearch can search across everything to find specific insights. The solution helps companies create new growth opportunities by generating insights about the products and services and consumer preferences. 

Implementing the solution enables businesses to utilize intelligence while making decisions. Organizations can improve operational efficiency and detect risks early using the near-real-time data analytics with Amazon ElasticSearch.  



Introduction with the client to understand his context - both business and technical. The aim of the phase is to explore this new context, gather the needs through exchange with the different key points of contact, answer unclear points, and agree on a defined scope.


Proposition of several potential solutions that could fit the need and iterate on it based on client feedback. In this step, we can include a prototype or a Proof of Concept to have a better sense of the feasibility of the architecture to put in place with its different layers/components.

Implementation & tests

Iterative phase based on Agile methodologies & rituals: sprint planning, demo, retrospective, prioritization, etc. Each sprint will include the implementation of the technical architecture, the deployment of the infrastructure, and the development phase if required.


Go in production with the defined solution and ensure post-production support if required.


  • Speed - Data Analytics with Amazon ElasticSearch runs in minutes, generating near-real-time insights into IT resource usage. The solution's distributed nature enables it to process large volumes of data in parallel, quickly discovering the best matches for queries. 
  • Scalability - The solution can scale in and out as required with simple configuration changes in the infrastructure pipelines. 
  • Managed service - Technofy takes care of administrative functions like monitoring, hardware provisioning, backup, failure recovery, and patching, enabling your organization to save a significant amount of time and costs. 
  • A broad scope of use cases - Data analytics with Amazon ElasticSearch is used for a wide range of use cases, including log analytics, full-text search, security intelligence, business analytics, and operational intelligence 
  • Compatibility - You can use ElasticSearch with other tools like Kibana to visualize data and create interactive dashboards  
  • Easy application development - ElasticSearch supports various programming languages, including Java, Python, PHP, JavaScript, Node.js, Ruby, and many more. 
  • All-inclusive - The solution indexes all data at incredible speeds.
  • Error-handling - Amazon ElasticSearch is capable of handling human mistakes and complexities like typos. The solution detects failures to keep clusters and data safe and available.  

Getting started with Technofy

Technofy experts offer fully managed Data Analytics with Amazon ElasticSearch. Our team comprises big data scientists and analysts with varied skills to deploy the solution in diverse use cases to derive meaningful insights. Our solutions have robust security and privacy controls to mitigate vulnerabilities and non-compliance issues. 
Talk to us today to explore practical ways our technology and expertise can analyze your business's data for great insights.  
Contact us for more