AWS for M&E Blog

Better understand sports fan data with Fan360 on AWS


Companies and businesses of all sizes across industries now consider acquiring data-driven insights from their customer base as a key priority. Sports entities (teams, leagues, sport broadcasters and partners) are no different. Understanding their global, diverse, and distributed fan-bases is critical to their business strategies. Sports fans interact with their favorite sports and teams in many different ways. This puts sports organizations in a challenging position. The various channels available that connect fans and sports entities lead to valuable information coming from many sources, often in incompatible data formats, isolated from each other. Sports entities need a reliable way to get value from all information sources, to provide fans with the curated experience they expect, and also support conversations with external parties, like sponsors, to generate new revenue streams.

This is the first in a two-part blog series about how sports organizations can use a Fan360 data mesh to gain new insights from existing and emerging data. It focuses on how a data mesh architecture works and how it can enable collaboration at scale, both within an organization and with external partners. The second post will explain how to create refined data products within a data domain. It will go into more detail on how insights are generated from the data.

Introducing the Fan360 data mesh

To create a 360-degree view of a fan-base, a modern data strategy dedicated to sports fan data is needed. Modern data strategies allow customers to connect multiple data sources to the end consumer of that data, providing valuable insights to existing raw data. To achieve a connection between data sources and data consumers, consider these key functional aspects:

  • Data ingest: Collect data from diverse, siloed sources in an optimized way.
  • Store and govern: Acquire a scalable, secure and unique storage layer for different data formats, and control data access at scale.
  • Clean and process: Clean and refine data to make it consumable as needed.
  • Share data securely: Once refined data is available, share it securely with internal teams and external partners.
  • Enrich and activate: Create the curated experiences fans are looking for by leveraging technology like machine learning (ML) and artificial intelligence (AI) to make data-driven decisions.
Flow diagram - functional aspects of modern data strategy

Fig. 1 – Key functional aspects of modern data strategy

As your data volumes grow, it can be challenging to manage all the functional requirements, data access, and governance at scale. In this blog post, we propose using a data mesh architecture to ensure your data strategy scales as your fan-base increases.

A data mesh is an architectural framework that decentralizes data management responsibilities across an organization. Rather than having one central data team handle all data, your strategy is organized into separate data domains. Each domain relates to a business domain, with actors in that domain managing every aspect from ingestion to activation.

Within a domain, you ingest and store various raw data sources, then clean and process them. You need to govern access to those datasets to expose them to other domains or third parties. Each domain is accountable for handling relevant data end-to-end, creating what data mesh architectures call data products.

A data product includes not only the refined dataset for consumption but also the access rules to expose it to consumers. A shared data catalog allows producer domains to publish their data products for consumer domains.

The data mesh architecture connects producer and consumer domains through secure governance.

Visual representation of data mesh and data domain components

Fig. 2 – Visual representation of data mesh and data domain components

Sport entities can manage fan data available as incoming sources of the Fan360 data domain, and create refined Fan360 data products to expose to other internal teams, or external parties depending on the use case.

The second part of the blog series will cover in more details how sport entities can create refined data products within a data domain. The following sections provide an overview of why secure data sharing is important, and walks through some opportunities to enrich fan data.

You can find more detail about AWS data mesh reference architecture in this blog post.

Sharing the fan profile

Different business users within a sports entity can gain value from Fan360 data products. Amazon DataZone is a data management service that makes it faster and easier to catalog, discover, share, and govern data stored across an organization. With Amazon DataZone, administrators who oversee an organization’s data products in different domains can manage and govern access to data using fine-grained controls.

Data producer domain administrators can publish data products to the Amazon DataZone catalog from the data stored in AWS Glue Data Catalog, Amazon Redshift tables and views, or grant access to AWS Lake Formation managed tables. Data consumers can use Amazon Athena or Amazon Redshift query editors to access and analyze published data products.

Amazon DataZone helps increase a business unit’s efficiency and ease the adoption of data mesh products across the organization.

Data collaboration is also a critical step in unlocking new revenue streams and activating partnerships. Sport entities seek to collect different pieces of the Fan360 puzzle from disparate sources. The ability to exchange data, through AWS Clean Rooms, with partners and without comprising the privacy between entities, is a critical practice.
Secure sharing capabilities, allow you to add newly gained insights to your data domain and reinforce your Fan 360 data products. By integrating your first-party data with external views, you can provide a more tailored experience to your fan-base.

Enrich and activate

Once refined data products are defined and made available for consumption, sports entities can enrich data products and activate their value in different ways. Following are some examples:

  • Personalized product and content recommendation: Amazon Personalize allows entities to customize their product recommendations based recent sport events or fan reaction accessed from Fan360 data products. Learn more about Amazon Personalize recommendations.
  • Connect different aspects of fan interactions: Using a graph database like Amazon Neptune, you can connect different fan data products related to the various aspects of fan engagement. Create a holistic view of fan interaction across different channels, like marketing website, on demand content and in venue experience. Find out how to build a customer knowledge repository with Amazon Neptune.
  • Supply tailored advertising: React to audience signals, for example reactions to a specific player or team performance, to prompt relevant advertising campaigns to the fan-base. Learn how AWS Elemental MediaTailor helps optimize ad delivery.
  • Tailored in venue-experience: Recommend tickets for an upcoming event based on fan history, or offer a discount for food and beverage products on a fan’s next visit to the venue. Learn what game-day merchandising fans appreciate most based on their recent interactions.
  • Data Collaboration with partners: Transition Fan 360 into a data product where you can offer data following the AWS Data Exchange Publishing Guidelines. This allows consumers to pay for the data you provide and help progress the precision of your Fan360 profile.

The ability to personalize experiences allows fans to be heard and seen by receiving tailored content, products, highlights, etc based on their interests.


Completing the Fan360 profile with an AWS data mesh architecture can revolutionize the way sports entities engage with a fan-base. The combination of AWS services in the Fan360 architecture empowers sports organizations to effectively analyze and leverage data to enhance fan engagement, deliver personalized experiences, and optimize monetization strategies with third parties. This approach offers sport entities an unprecedented opportunity to monetize their fan data effectively while deepening the connection to the fan-base. By collecting, analyzing, and leveraging the fan profile, Fan360 enables sport entities to stay competitive and build lasting relationships with their fans. The future of your sports organization awaits, ready to be shaped by the game-changing synergy of Fan360 on AWS.

Please check the second post in this blog series to learn more about how to build refined data products within the Fan360 domain.

Miles Boxer

Miles Boxer

Miles is an Associate Solution Architect based in NYC with a passion for Data Analytics, Sports, and Media.

Federico Bianchi

Federico Bianchi

Federico is a Senior Solution Architect based in Amsterdam, helping Enterprise customers from early stages of their cloud journey. Coming from a background in the payments industry, he's also passionate about Sports and Data Analytics.

Jacob Carstens

Jacob Carstens

Jacob is a Senior Sport Solution Architect Specialist based in NYC. Jacob spent over half a decade focusing on bringing Data Analytics best practices to the forefront of the Sport Industry.