Bilvantis

Bilvantis makes data
a ‘ real asset’ for its banking customer

Challenge

A leading banking firm was using Mainframe Systems to store its data. However, the data lying in the mainframes were underutilized as it could not be readily used by intelligent data software like Splunk. Also, it was challenging to record real-time transactional data from Mainframe directly to cloud data platforms.

 

Scenario

The Mainframe was being used as a central data hub, which was connected to individual smaller terminals and workstations. As a legacy system Mainframe could store large amounts of data. However, it needed additional support programs for the data to be read or transferred. This made it an expensive, time-consuming, and complex process.

 
 

The Solution

Approach & Solution

The bank reached out to Bilvantis to modernize the data silo. Bilvantis zeroed on using Splunk intelligent data software Splunk was chosen as the Splunk software allows searching, processing, and analysis of data. It also equips users to generate reports and gain valuable insights using interactive dashboards. Bilvantis integrated Mainframe data with Splunk using protocols. This facilitated access to real-time transactional data that could, in turn, be utilized on intelligent Splunk dashboards.

Bilvantis then automated the process to continuously send real-time data from Mainframe to Splunk, in the desired format. In addition, Bilvantis also programmed the data software to:

  • – Flag anomalies or discrepancies, and share alerts
  • – Display relevant information on dashboards, such as transactions above a set value
  • – Monitor real-time transactional data
  • – Bilvantis leveraged the in-built functionalities of Splunk to program certain advanced functions to enhance user experience.

Bilvantis leveraged the in-built functionalities of Splunk to program certain advanced functions to enhance user experience.

Benefits

Bilvantis solution offered the following benefits:

  • Raw data from Mainframe could now be utilized on Splunk
  • Mainframe from other cloud services and database could be integrated
  • Real-time data was available for actionable insights
  • Detection of discrepancies was faster
  • Interactive dashboards were used for generating reports and monitoring real-time transactional data