As businesses become AI-ready, efficient data management has acquired an unprecedented role in ensuring their success. Bottlenecks in the data pipeline can cause massive revenue loss while having a negative impact on reputation and brand value. Consequently, there’s a growing need for agility and resilience in data preparation, analysis, and implementation.
On the one hand, data-analytics teams extract value from incoming data, preparing and organizing it for the production cycle. On the other, they facilitate feedback loops that enable continuous integration and deployment (CI/CD) of new ideas.
