We announced several new innovations with our autonomous data to AI platform powered by BigQuery, alongside our unified, trusted, and conversational Looker BI platform:
125. BigQuery pipelines, now GA, supports building data pipelines.
126. BigQuery data preparation, now GA, transforms and enriches data.
127. BigQuery anomaly detection, now in preview, maintains data quality and automates metadata generation.
128. Data science agent, now GA, is embedded within Google’s Colab notebook, provides intelligent model selection, enabling scalable training, and faster iteration.
129. Looker conversational analytics, in preview, lets business users interact with data using natural language.
130. The Looker Conversational Analytics API, now in preview, lets developers build and embed conversational analytics into applications and workflows. Sign up to gain access.
131. BigQuery knowledge engine, in preview, leverages Gemini to analyze schema relationships, table descriptions, and query histories to generate metadata on the fly, model data relationships, and recommend business glossary terms.
132. BigQuery semantic search, is now GA, providing AI-powered data insights and across BigQuery, grounding AI and agents in business context.
133. BigQuery’s contribution analysis feature, now GA, helps you pinpoint the key factors (or combinations of factors) responsible for the most significant changes in a metric.
134. We added Gemini in BigQuery features into existing BigQuery pricing models across all BigQuery compute pricing options. Express your interest in trying out the new features.
135. BigQuery pipe syntax is GA, letting you apply operators in any order and as often as you need, and is compatible with most standard SQL operators.
Then, for data science and analyst teams, we added AI-driven data science and workflows as part of BigQuery notebook:
136. New intelligent SQL cells understand your data’s context and provide smart suggestions as you write code, and let you join data sources directly within your notebook.
137. Native exploratory analysis and visualization capabilities in BigQuery make it easy to explore data, as well as add features to enable easier collaboration with colleagues. Data scientists can also schedule analyses to run and refresh insights periodically.
138. The new BigQuery AI query engine lets data scientists process structured and unstructured data together with added real-world context, co-processing traditional SQL alongside Gemini to inject runtime access to real-world knowledge, linguistic understanding, and reasoning abilities.
139. Google Cloud for Apache Kafka, now GA, facilitates real-time data pipelines for event sourcing, model scoring, messaging and real-time analytics.
140. Apache Spark workloads within BigQuery, now in preview, execute serverlessly, that is, on a fully managed platform.
141. New dataset-level insights in BigQuery data canvas, in preview, surface hidden relationships between tables and generate cross-table queries by integrating query usage analysis and metadata.
142. BigQuery ML includes the new AI.GENERATE_TABLE in preview to capture the output of LLM inference within SQL clauses.
143. BigQuery ML now supports open-source and Anthropic’s Claude, Llama, and Mistral models, hosted on Vertex AI.
144. BigQuery vector search includes a new index type, now GA, based on Google’s ScaNN model that’s coupled with a CPU-optimized distance computation algorithm for scalable, faster and more cost-efficient processing.
145. The preview of BigQuery ML’s pre-trained TimesFM model developed by Google Research simplifies time-series forecasting.
146. We integrated new Google Maps Platform datasets directly into BigQuery, to make it easier for data analysts and decision makers to access insights.
147. In addition, Earth Engine in BigQuery brings the best of Earth Engine’s geospatial raster data analytics directly into BigQuery. Learn more here.
148. GrowthLoop introduced its Compound Marketing Engine built on BigQuery with Growth Agents powered by Gemini, so marketing can build personalized audiences and journeys that drive rapidly compounding growth.
149. Informatica expanded its services on Google Cloud to enable sophisticated analytical and AI governance use cases.
150. Fivetran introduced its Managed Data Lake Service for Cloud Storage with native integration with BigQuery metastore and automatic data conversion to open table formats like Apache Iceberg and Delta Lake
151. DBT is now integrated with BigQuery DataFrames and DBT Cloud is now on Google Cloud.
152. Datadog introduced expanded monitoring capabilities for BigQuery, providing granular visibility into query performance, usage attribution, and data quality metrics.
BigQuery’s autonomous data foundation provides governance, orchestration for diverse data workloads, and a commitment to flexibility via open formats. Announcements in this area include:
153. BigQuery makes unstructured data a first-class citizen with multimodal tables in preview, bringing rich, complex data types alongside structured data for unified storage and querying via the new ObjectRef data type.
154. BigQuery governance in preview provides a single, unified view for data stewards and professionals to handle discovery, classification, curation, quality, usage, and sharing.
155. The new BigQuery universal catalog brings together a data catalog (formerly known as Dataplex Catalog) and a fully managed, serverless metastore, now generally available.
156. BigQuery metastore, now GA, enable engine interoperability across BigQuery, Apache Spark, and Apache Flink engines, with support for the Iceberg Catalog.
157. BigQuery business glossary, now GA, lets you define and administer company terms, identify data stewards for these terms, and attach them to data asset fields.
158. BigQuery continuous queries, now GA, enable instant analysis and actions on streaming data using SQL, regardless of its original format.
159. BigQuery tables for Apache Iceberg in preview, lets you connect your Iceberg data to SQL, Spark, AI and third-party engines.
160. New advanced workload management capabilities, now GA, scale resources, manage workloads, and help ensure their cost-effectiveness.
161. BigQuery spend commit, now GA, simplifies purchasing, unifying spend across BigQuery data processing engines, streaming, governance, and more.
162. BigQuery DataFrames now has AI code assist capabilities in preview, letting you use natural language prompts to generate or suggest code in SQL or Python, or to explain an existing SQL query.
163. SQL translation assistance, now GA, is an AI-based translator that lets you create Gemini-enhanced rules to customize your SQL translations, to accelerate BigQuery migrations.
164. Catalog metadata export, GA, enables bulk extract of catalog entries into Cloud Storage.
165. BigQuery can now perform automatic at-scale cataloging of BigLake and object tables, now GA.
166. BigQuery managed disaster recovery is now GA, featuring automatic failover coordination, continuous near-real-time data replication to a secondary region, and fast, transparent recovery during outages.
167. New workload management capabilities in preview include reservation-level fair sharing of slots, predictability in performance of reservations, and enhanced observability through reservation attribution in billing.
Looker, is adding a host of new conversational and visual capabilities, aimed at making BI accessible and useful to all users, accelerated by AI.
168. Gemini in Looker features are now available to all Looker platform users, including Conversational Analytics, Visualization Assistant, Formula Assistant, Automated Slide Generation, and LookML Code Assistant.
169. Code Interpreter for Conversational Analytics is in preview, allowing business users to perform forecasting and anomaly detection using natural language without needing deep Python expertise. Learn more and sign up for it here.
170. New Looker reports feature an intuitive drag-and-drop interface, granular design controls, a rich library of visualizations and templates, and real-time collaboration capabilities, now in the core Looker platform.
171. With Google Cloud’s acquisition of Spectacles.dev, developers can automate testing and validation of SQL and LookML changes using CI/CD practices.
Firebase
172. The new Firebase Studio, available to everyone in preview, is a cloud-based, agentic development environment powered by Gemini that includes everything developers need to create and publish production-quality full-stack AI apps quickly, all in one place. Gemini Code Assist agents are available via private preview.
173. Genkit, an open-souce framework for building AI-powered applications, using your preferred language, now has early support for Python and expanded support for Go. Try this template in Firebase Studio to build with Genkit.
174. Vertex AI in Firebase now includes support for the Live API for Gemini models, enabling more conversational interactions in apps such as allowing customers to ask audio questions and get responses.
175. Firebase Data Connect is now GA, offering the reliability of Cloud SQL for PostgreSQL with instant GraphQL APIs and type-safe SDKs.
176. Firebase App Hosting is also GA, providing an opinionated, git-centric hosting solution for modern, full-stack web apps.
177. A new App Testing agent within Firebase App Distribution, also in preview, prepares mobile apps for production by generating, managing, and executing end-to-end tests.
Google Cloud Consulting
Google Cloud Consulting introduced several new pre-packaged service offerings:
178. Agentspace Accelerator provides a structured approach to connecting and deploying AI-powered search within organizations, so employees can easily gain access to relevant internal information and resources when they need it.
179. Optimize with TPUs helps customers migrate workloads to our purpose-built AI chips, TPUs.
180. Oracle on Google Cloud lets customers combine Oracle databases and applications with Google Cloud’s advanced platform and AI capabilities for enhanced database and network performance.
181. We expanded access to Delivery Navigator, a series of proven delivery methodologies and best practices to help with migrations and technology implementations to customers as well as partners, in preview.
Networking
Google’s global network is the backbone of Google Cloud’s services, and relies on a long list of innovations.
182. Cloud WAN, a Cross-Cloud Network solution, is a fully managed, reliable, and secure enterprise backbone that makes Google’s global private network available to all Google Cloud customers. Cloud WAN delivers up to 40% improved network performance, while reducing total cost of ownership by up to 40%. Read more here.
183. The new 400G Cloud Interconnect and Cross-Cloud Interconnect, available later this year, offers up to 4x more bandwidth than our 100G Cloud Interconnect and Cross-Cloud Interconnect, providing connectivity from on-premises or other cloud environments to Google Cloud.
184. Build massive AI services with networking support for up to 30,000 GPUs per cluster in a non-blocking configuration, available in preview now.
185. Zero-Trust RDMA security helps you secure your high-performance GPU and TPU traffic with our RDMA firewall, featuring dynamic enforcement policies. Available later this year.
186. Get accelerated GPU-to-GPU communication, with up to 3.2Tbps of non-blocking GPU-to-GPU bandwidth with our high-throughput, low-latency RDMA networking, now generally available.
187. Leverage GKE Inference Gateway and Cloud Load Balancing alongside Model Armor, NVIDIA NeMo Guardrails, and Palo Alto Networks AI Runtime Security, all using Service Extensions.
188. Cloud Load Balancing has optimizations for LLM inference, letting you leverage NVIDIA GPU capacity across multiple cloud providers or on-prem infrastructure.
189. New Service Extensions plugins, powered by WebAssembly (Wasm), let you automate, extend, and customize your applications with plugin examples in Rust, C++, and Go. Support for Cloud Load Balancing is now generally available, and Cloud CDN support will follow later this year.
190. Cloud CDN‘s fast cache invalidation delivers static and dynamic content at global scale with improved performance, now in preview.
191. TLS 1.3 0-RTT in Cloud CDN boosts application performance for resumed connections, now in preview.
192. App Hub provides streamlined service discovery and management by automating service discovery and cataloging.
193. App Hub service health enables resilient global services with network-driven cross-regional failover. Available later this year.
194. Later in 2025, you’ll be able to use Private Service Connect to publish multiple services within a single GKE cluster, making them natively accessible from non-peered GKE clusters, Cloud Run, or Service Mesh.
Then, to help you secure your workloads, we introduced enhancements to protect distributed applications and internet-facing services against network attacks:
195. The new DNS Armor detects DNS-based data exfiltration attacks performed using DNS tunneling, domain generation algorithms (DGA) and other sophisticated techniques. Available in preview later this year.
196. New hierarchical policies for Cloud Armor let you enforce granular protection of your network architecture.
197. There are new network types and firewall tags for Cloud NGFW hierarchical firewall policies, coming this quarter in preview.
198. Cloud NGFW adds new layer 7 domain filtering, allowing firewall administrators to monitor and control outbound web traffic to only allowed destinations. Coming later in 2025.
199. Inline network DLP for Secure Web Proxy and Application Load Balancer provides real-time protection for sensitive data-in-transit via integration with third-party (Symantec DLP) solutions using Service Extensions. In preview this quarter.
200. Network Security Integration, now generally available, helps you maintain consistent policies across hybrid and multi-cloud environments without changing your routing policies or network architecture.
201. Imperva Application Security is integrated with Cloud Load Balancing, via Service Extensions, and is now available in the Google Cloud Marketplace.
Additional partner announcements
We’ve always taken an open approach to AI, and the same is true for agentic AI. With updates this week at Next ‘25, we’re now infusing partners at every layer of our agentic AI stack to enable multi-agent ecosystems. Here’s a closer look:
202. Expert AI services: Our ecosystem of services partners — including Accenture, BCG, Capgemini, Cognizant, Deloitte, HCLTech, Infosys, KPMG, McKinsey, PwC, TCS, and Wipro — have actively contributed to the A2A protocol and will support its implementation.
203. AI Agent Marketplace: We launched a new AI Agent Marketplace — a dedicated section within Google Cloud Marketplace that allows customers to browse, purchase, and manage AI agents built by partners including Accenture, BigCommerce, Deloitte Elastic, UiPath, Typeface, and VMware, with more launching soon.
204. Power agents with all your enterprise data: We are partnering with NetApp, Oracle, SAP, Salesforce, and ServiceNow to allow agents to access data stored in these popular platforms.
205. Better field alignment and co-sell: We introduced new processes to better capture and share partners’ critical contributions with our sales team, including increased visibility into co-selling activities like workshops, assessments, and proofs-of-concept, as well as partner-delivered services.
206. More partner earnings: We are evolving incentives to help partners capitalize on the biggest opportunities, such as a 2x increase in partner funding for AI opportunities over the past year. We also introduced new AI-powered capabilities in Earnings Hub, our destination for tracking incentives and growth.
207. We partnered with Adobe, the leader in creativity, to bring our advanced Imagen 3 and Veo 2 models to applications like Adobe Express.
208. Together with Salesforce’s Agentforce, we’re leading the digital labor revolution, driving massive gains in human augmentation, productivity, efficiency, and customer success.
Security
We offer critical cyber defense capabilities for today’s challenging threat environment, and introduced a number of new innovations:
209. Google Unified Security: This solution brings together our visibility, threat detection, AI powered security operations, continuous virtual red-teaming, the most trusted enterprise browser, and Mandiant expertise — in one converged security solution running on a planet-scale data fabric.
Source Credit: https://cloud.google.com/blog/topics/google-cloud-next/google-cloud-next-2025-wrap-up/
