Overcome 10 key data challenges
A guide for CIOs, CDOs, and data and AI executives
Data transformation initiatives often fail to meet expectations. More often than not, this can be traced back to the strategy. As organizations look at their legacy IT platforms, they quickly realize the existing infrastructure can’t scale to meet modern demands for better analytics and hundreds of thousands of AI use cases. To transform the way your organization uses and processes data, you’ll need to unify your data warehousing and AI use cases on a single platform so you can innovate faster while improving your total cost of ownership. Don’t start your next transformation to become AI-driven without this comprehensive guide to develop your data and AI strategy.
- The 10 key considerations for building your strategy
- 5 reasons why it’s no longer enough to use SQL and BI tools to query your data
- How to prioritize your AI use cases to accelerate momentum and generate ROI
- Which 11 essential Lakehouse features can help you execute your data and AI strategy