2021: Recalibrating Customer Analytics Strategy
The unification of data engineering and analytics has become essential for forward-thinking companies to thrive in the digital era. Many still struggle to create a 360° view of their customers and extract business-relevant information. Moreover, they require diverse data applications, including SQL analytics, real-time monitoring, data science, and machine learning.
Consequently, architects have envisioned lakehouse, a new data management paradigm that allows traditional analytics and data science to co-exist in the same system. This architecture radically simplifies enterprise data infrastructure and accelerates innovation in an age when machine learning is poised to disrupt every industry.
- Why is building a 360° view and micro-segmentation engine in the cloud becoming an industry trend?
- How are businesses applying lakehouse architecture to reduce complexity and accelerate decision making?
- How can companies effectively perform BI and SQL workloads on a multi-cloud lakehouse architecture?