Prerequisite: None
Data monetization opportunities are within reach of businesses everywhere. Recent innovations in converged data analytics platforms can accelerate an enterprise's ability to productize their data and other data-derived assets, such as trained ML models. In addition, cloud data marketplaces can be key channels for monetizing these assets as well as any AI/ML-powered products and services with which they are bundled or into which they’ve been embedded.
In this Executive Summit Day 1 keynote, TDWI senior research director James Kobielus will discuss how to build a strategy for managing the monetization of enterprise data assets. Kobielus will address the following essential elements of enterprise data monetization:
- Identifying who should lead data monetization initiatives in your enterprise
- Developing an optimal organizational business model for monetization of data assets
- Democratizing access to self-service data analytics tools to boost the bottom-line contribution of data analytics assets
- Assessing which enterprise data assets should be made available for sale, subscription, licensing, and other monetization initiatives
- Measuring revenue generation and other bottom-line impacts from monetization of enterprise data assets
- Deploying the tools, applications, and platforms that are necessary for data monetization in your enterprise
- Relying on cloud data marketplaces, data exchanges, or other channels to sell and/or license high-quality data sets, pretrained machine -learning models, and other digital assets
- Implementing effective controls and safeguards to ensure that data monetization activities remain in compliance with relevant laws, regulations, mandates, and policies
- Leveraging enterprise investments in cloud data catalogs, DataOps and MLOps platforms, data and model governance, and other key infrastructure to support data productization and monetization