Business Impact

  • ~70%

    increase in identification and remediation of data quality issues

  • 60%

    reduction in human resource dependency

  • 70%

    reduction in time to production using DevOps best practices

  • ~80%

    reduction in time to market for the analytics solution

Customer Key Facts

  • Location : Toronto, Canada
  • Industry : Recruitment & Talent management

Problem Context

TalentNet’s customizable talent acquisition platform empowers the world’s leading brands to revolutionize the way they attract and engage with top talent. With a large number of data sources and integrations, their data ecosystem was complex and difficult to consolidate. This limited TalentNet’s capacity to utilize customer data for business intelligence and analytics at scale. TalentNet wanted to centralize and modernize its data warehouse on AWS and enhance its software as a service offering by adding a data visualization layer to help its customers analyze and monitor the talent acquisition process (TAPs) and hiring performance


  • Absence of a unified platform with scalable and sustainable data storage 
  • Requirement of a single source of truth out of the disparate tenant databases for data analytics and business insights
  • Provision of automated CICD pipeline for the entire multi-layered data warehouse while parallelly enabling CDC
  • A singular platform with data analytics and self-serve capabilities to optimize the decision-making process.

Technologies Used

Lake Formation
AWS Glue
AWS Redshift
Step functions
Concourse CI


Quantiphi collaborated with different teams within TalentNet during the MAP Assessment to discover current pain points and business priorities and designed a roadmap.

Following the assessment, the Quantiphi team mobilized implementation by setting up an enterprise data warehouse on Amazon Redshift with

  • Data pipelines for staging, integration, and presentation layers 
  • Continuous data integration 
  • Dashboards on Amazon Quicksight

Through the data analytics platform, TalentNet can:

  • Provide in-depth analysis of talent management through 6+ custom dashboards
  • Allow users to analyze hiring patterns using trend analytics in talent management
  • Enable Q&A capabilities on the dashboard for users by leveraging the NLP features of Amazon QuickSight
  • Provide a single source of truth for future use cases such as fraud detection, text and engagement analysis, and benchmarking study


  • As a single point of truth, the enterprise data warehouse is a three-layered model that captures Change Data 
  • Over six multi-layered dashboards with business KPIs in Quicksight enable data analytics
  • Self-serve analytics using Quicksight’s NLP features 
  • Future readiness for advanced analytics

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