Splunk: A Comprehensive Analytics Data Platform

Splunk is a modern Data Platform that enables centralised data management, near real-time data capture and transformation, application of Artificial Intelligence to various use cases including AIOps with Splunk IT Service Insight that provides end-to-end tracking of digital services, intelligent management of notifications and alerts and automation of Root Cause Analysis

Use Case 1 – Operations Monitoring

Customer: Milan/Bergamo Airport (BGY) – Third airport in Italy, one of Ryanair’s three main operational bases

Need: provide a single, real-time view of all processes to ensure optimal and seamless operations

Highlights of the project

  • Low initial time and cost to meet priority needs quickly and at low risk
  • Agile design to progressively extend the scope of the solution
  • Define concrete and measurable objectives
  • Transform raw data into information

Use Case 2 – Transaction Monitoring

Customer: Major Italian player, POS payments – e-money services

Need:

  • Real-time visibility on all transactions
  • Automatic alarms
  • Integration with legacy Mainframe systems

Project highlights

  • Phased Agile approach to quickly meet priority needs and minimise time and risk
  • Splunk + Splunk ITSI integration
  • Transforming complex transactional logs into talking metrics and KPIs

Use Case 3 – AIOps

Customer: A major insurance player, a large reality present with agencies throughout Italy and Spain. Direct interlocutor: the Business Service Monitoring team of the company that provides IT services to the group

Need:

  • Accurately monitor the service levels of more than 40 business applications
  • Provide early warnings of any malfunctions
  • Move from reactive monitoring of business processes to predictive monitoring

Project highlights

  • A tool, Splunk ITSI, capable of tracking and measuring end-to-end the health of digital services required for business operations
  • The use of appropriate Artificial Intelligence techniques to provide accurate predictions
  • Collaboration between the client and the data science team to identify services and create KPIs for each one to be tracked

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