Five ways marketers can use Genie One
Summary
Genie One enables marketing teams to translate governed data into real-time insights and uncover cross-channel performance trends without relying on manual reporting. By independently exploring customer and pipeline data, teams can accelerate strategy speed-to-market and maximize campaign ROI.
Summary generated by brickster.ai. For the full article, follow the source link above.
More from Databricks Blog
Databricks Is Doubling Down On New York City As A Premier AI Talent Hub
Databricks is doubling its New York City office footprint to 120,000 square feet at 5 Bryant Park, adding a dedicated Engineering and Research floor alongside an Executive Briefing Center. The expanded location will house teams driving enterprise AI research, infrastructure such as Unity Gateway, and agentic applications like CustomerLake.
Transactions are Generally Available, advancing warehousing on the Lakehouse
Multi-statement transactions are now generally available for Delta Lake and Apache Iceberg tables on Databricks, bringing native atomic guarantees to multi-table workflows. Backed by row-level concurrency and Unity Catalog governance, this capability allows practitioners to run critical warehouse workloads directly on open lakehouse data without maintaining separate warehouse systems.
Closing the Binary Blind Spot: Domain-Knowledge Injection for LLM Malware Triage in npm Packages
Injecting domain knowledge into large language models resolves the binary blind spot to enhance automated malware triage across npm packages. This approach strengthens software supply chain defenses against the rising volume and sophistication of attacks targeting package registries.
How our AI Research team uses AI Runtime
Databricks AI Research uses AI Runtime to train and fine-tune models across hundreds of GPUs, supporting an 8x surge in training jobs fueled by agent-driven research. Built-in GPU reliability, fast job launches, and native integrations with MLflow and Unity Catalog accelerate these automated experimentation workflows at scale.
Stripe Data Pipeline now syncs real-time Stripe data to Lakebase Postgres
Stripe Data Pipeline now streams real-time Stripe data directly into Databricks Lakebase Postgres with no code required, eliminating the need to build and maintain custom API or webhook integrations. Applications can now query always-current Stripe data using simple SQL to gate features, display live billing details, and trigger personalized offers.
Reducing the noise: How Atlassian built an OCSF security lakehouse on Databricks
Atlassian normalized 44 billion daily events into an OCSF security lakehouse on Databricks, cutting ingestion costs by 80% and accelerating queries by up to 95%. The unified architecture now powers over 500 production threat-detection signals while driving a 60% increase in security analyst productivity.