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This article explores Google Data Cloud's data curation accelerators that automate the process of organizing, cleaning, and enriching raw data for enterprise AI and analytics.
Google reintroduced Data Studio as the new central hub for Google Data Cloud assets with unified access to data visualization and analysis tools.
TriNetX leverages Databricks' lakehouse architecture to power AI-driven analytics on real-world health data (RWD) from nearly 300 million patients, accelerating clinical drug development timelines.
Databricks releases Apache Iceberg v3 in Public Preview, introducing Row Lineage, Deletion Vectors, and VARIANT.
Zalando shares how they built a unified data foundation using the Databricks platform to address governance and metric consistency challenges at scale.
Google announces read/write interoperability between BigQuery and Iceberg engines (Spark, Flink, Trino) via Google-managed Iceberg REST Catalog.
This post demonstrates how Databricks' unified Data Intelligence Platform enables cross-team collaboration in financial institutions through governed analytics and AI-powered workflows.
MakeMyTrip, India's largest online travel agency, achieved millisecond-level personalization latency using Databricks' Real-Time Mode (RTM) in Apache Spark Structured Streaming.
This post describes an interval-aware caching layer Netflix built on top of Apache Druid to eliminate redundant query load at trillion-row scale.
Google announces the general availability of Conversational Analytics API for Looker Embedded environments, enabling natural language data querying in third-party applications.
Looker introduces self-service Explores, letting users import flat files and Google Sheets directly into the Looker semantic layer for instant ad-hoc analysis.
RVU shares how they use Google Cloud Dataproc and Serverless Apache Spark to power hyper-personalization across their consumer brands (Confused.com, Uswitch, Money.co.uk, etc.).
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