The article further outlines seven key areas for successful data modernization, including AI-driven platforms, treating data as a monetizable asset, hyper-personalization, autonomous operations, cloud-native architectures, data-based decision-making culture, and data trust and observability. It also provides practical steps for executives to modernize their data infrastructure, such as assessing the current data landscape, prioritizing data governance, building a cross-functional data team, and investing in technology and talent. The author concludes by urging business leaders to modernize their data systems now to lead in the future industries and to prepare for emerging technologies like quantum computing, 6G, and robotics.
Key takeaways:
- Data modernization is a strategic necessity for companies to stay competitive in an AI-powered future, offering a strategic advantage that fuels innovation and growth.
- Seven key areas for successful data modernization include AI-driven platforms, treating data as a monetizable asset, hyper-personalization, autonomous operations, cloud-native architectures, a data-based decision-making culture, and data trust and observability.
- Executives can modernize their data infrastructure by assessing their current data landscape, prioritizing data governance, building a cross-functional data team, and investing in technology and talent.
- Emerging technologies like quantum computing, 6G, and robotics can only fully benefit businesses if they have a robust, modernized data infrastructure in place.