Improving data-driven app development at reduced cost for a global technology giant | HCLTech

Improving data-driven app development at reduced cost for a global technology giant

HCLTech helped the client’s development team build a proprietary application deployment platform that enabled them to develop data-driven applications more productively.
5 min read
5 min read


Our client, a Fortune 5 technology company, wanted to custom-build a proprietary app deployment platform that includes the essential features of the earlier product but improves functionality and delivers better value.

The Challenge

Lack of desired value from existing solution

The client’s business insights team was not getting the value it needed from its enterprise analytics and visualization solution. The packaged application-builder proved cumbersome for the development of internal applications, as each app required additional coding to implement the desired access control. In addition, although the suite offered a wide range of functionality, a considerable portion of it was underutilized by the organization.


The Objective

Improve application platform performance and enhance user experience

For the replacement to enable a more effective development experience, the client agreed to:

  • Custom-build a proprietary application deployment platform that would include all essential features of the enterprise product it would replace, eliminate feature bloat and deliver better value over time
  • Ensure a smooth transition for users, maintaining the frontend characteristics of the current solution, offering every feature that users had been relying on and improving on the overall user experience, most notably that of access control
  • Accommodate the needs of users — data scientists, data engineers, data visualization experts, etc. — who wanted to create more advanced visualizations than was possible in their existing platform

The Solution

Develop custom-built application platform to ensure effectiveness in the client’s unique use cases

The HCLTech team built a proprietary application deployment platform that enabled the client to develop data-driven applications more productively.

  • The new platform accurately recreated the user-requested aspects of its predecessor’s look, feel and functionality
  • It ran on a Linux environment and leveraged a range of preexisting components — such as a PotgreSQL database and the client’s internal authentication proxy, including a user search function and a solution for monitoring the memory and CPU usage of apps created on the platform
  • Among the third-party software components that the team selected, Dokku stood out as especially important, as this platform-as-a-service (PaaS) enabled the final product to improve development times with automated “push-to-deploy” capability
  • As a result, users could now push an application to a Git repository and a CI/CD layer, which combined the best practices of continuous integration and DevOps
  • The solution also streamlined the development process by setting user-level permissions for each application by incorporating an authentication and access layer, which automatically handled Identity and Access Management (IAM) through the client’s internal directory service

The Impact

Reduced operating costs and improved decision-making

HCLTech delivered a that exceeded the functionality and improved the user experience of the license-based product it replaced. This was done at considerable cost savings over the product lifecycle. The solution enabled users with sufficient — but not necessarily developer-level — knowledge of Python or React code to create and deploy custom visualizations with considerably less coding overhead. This made it possible to integrate the client’s IAM system in cases where it was previously unfeasible and made it significantly easier in every other case. The solution enabled the client to involve a greater number of users in development to ensure faster delivery of internal products, as well as interoperability and information-sharing. As a result, the time it took to recreate reports from major enterprise data visualization tools in Python decreased dramatically.