Data strategies for revenue growth: a live discussion

Data strategies for revenue growth: a live discussion

Today on Zero-Touch Telecom Live, we welcomed Rakuten Symphony AI team members Gaurav Jain and Piyush Khurana to discuss data transformation strategies that support revenue growth initiatives. The discussion builds on our recent newsletter article about this topic.

The conversation replay is available below.

Striking a data strategy balance

Gaurav and Piyush kicked off the interview highlighting the benefits of a dual approach that brings data from a top down perspective to build a comprehensive platform and identifies opportunities and use cases through a bottom up, product-centric model. They emphasized the critical role of well-managed and high-quality data in successful AI initiatives.

Other key takeaways from the discussion included:

  • How to overcome data integration challenges. Piyush shared how data volume, costs of expanding data lakes and complexity associated with identifying relevant data sets imposes challenges, and experiences in overcoming them.
  • Guiding investments with the right data. Gaurav explained how data from deep packet inspection (DPI), call detail records (CDR) and business support systems (BSS) provides details about the network ecosystem and customer behavior to help make better investment decisions and identify potential use cases.
  • Achieving business outcomes. Piyush discussed how teams can use modern data platforms to find relevant data sets that help achieve new business outcomes, such as targeting customers likely to subscribe to an adjacent service.
  • Ensuring data privacy and cost-efficiency. Gaurav and Piyush revealed strategies for managing data privacy and cost-efficiency, including using data marts and data governance systems to manage data usage and costs. Data mesh-based approaches for privacy can help ensure access control via enhanced governance.

Check out the replay of our conversation now for the latest on how to develop effective data strategies for AI growth, and navigate the challenges of data integration and management. A transcript is also available here.

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