As I have explored in this “Sliding Doors” blog series, identifying the right door to create value with data can prove quite challenging - and once that door is opened, the journey ahead can seem daunting. But what if there was a way to make that journey a bit easier? Maybe it’s time to get back to basics… Who needs to hear this?

Big data has taken the world by storm, and as enterprises worldwide scramble to make sense of it, it continues to hit hard. Given the amounts of data produced daily, not only are they overwhelmed dealing with it, but they are also concerned that their existing ETL pipelines might not be able to cope without a solid data warehousing strategy.

Data governance covers processes, roles, policies, standards, and metrics that help an organization achieve its goals by ensuring the effective and efficient use of information. It sets up the processes and responsibilities necessary to maintain the data’s quality and security across the business. Data governance manages the formal data assets of an organization.

Apache Kafka has become the de facto standard for data streaming, used by organizations everywhere to anchor event-driven architectures and power mission-critical real-time applications. However, this rise has also sparked discussions on improving Kafka operations and cost-efficiency—streaming data is naturally prone to bursts and often unpredictable, resulting in inevitable variations in workloads and demand on your Kafka cluster(s).

Our new and improved feature provides robust metadata to improve visibility, streamline compliance and monitor spending.

For data engineers, the Generative AI (Gen AI) era is a transformative shift in how we approach data architecture and analytics. Professionals at the forefront of this shift will be gathering in San Francisco, at the Data+AI Summit June 10-13. Attendees will be exploring tools that integrate with Databricks Intelligent Data Platform that decrease data management costs and improve data's impact on business outcomes.

The payments industry is evolving rapidly, fueled by technological advancements, changing consumer behaviors, and a growing appetite for real-time transactions. As this transformation unfolds, new standards have been introduced to ensure the payments ecosystem's safety, security, and efficiency.

Organizations use enterprise resource planning (ERP) programs to meet the needs of an always-on culture in which a business's ability to pivot efficiently is important. Our five key takeaways about ERP integration and its business potential are.

A look at how to augment LLM results with retrieval augemented generation (RAG) and vector search, directly from BigQuery.