With marketing analytics now influencing more than half (53%) of marketing decisions, there’s finally some good data around using data in marketing. In fact, Gartner found that when analytics influences less than 50% of decisions, organizations find it challenging to prove the value of their marketing.

Recently, I got my hands dirty working with Apache Flink®. The experience was a little overwhelming. I have spent years working with streaming technologies but Flink was new to me and the resources online were rarely what I needed. Thankfully, I had access to some of the best Flink experts in the business to provide me with first-class advice, but not everyone has access to an expert when they need one.

In the age of the AI revolution, where chatbots, generative AI, and large language models (LLMs) are taking the business world by storm, enterprises are fast realizing the need for strong data control and privacy to protect their confidential and commercially sensitive data, while still providing access to this data for context-specific AI insights.

Gartner predicts that by 2026, 75% of organizations will adopt a digital transformation model predicated on the cloud as the fundamental underlying platform. Every organization has a cloud strategy and vision with annual goals, yet the business risky cloud migrations have aged in backlogs or implemented with straying budgets & timelines. ‘Assurance’ is the most critical factor in business readiness, scoping, budgeting, and concluding the cloud migration.

Data is essential to marketing. It’s how we know our audience and measure campaign outcomes. It shows us where to adjust a campaign on the fly, for even better results. But working with data is increasingly complex, and having the right stack of technologies is invaluable.

Traditional metrics like ticket resolution time or customer satisfaction scores (CSAT) are undeniably significant. However, to gain a more holistic picture, product analytics can be applied to: ‍