All news with #data security tag

📈 BigQuery Graph enables building a digital twin of interconnected systems like supply chains and restaurant networks by creating a Graph View over existing tables. The approach maps items, recipes, locations and dependencies into nodes and edges, enabling targeted queries for issues such as recalls, weather disruptions, or procurement leaks. It emphasizes keeping relational data for metrics while using graphs for structure, cleaning keys, and capturing edge properties for richer modeling.

📢 Amazon Simple Email Service (Amazon SES) now supports tenant-level suppression lists to isolate bounces and complaints per tenant. Previously, a single suppression list applied to all tenants in an account, which could cause one tenant's delivery issues to affect others. Administrators can choose suppression scope (TENANT or ACCOUNT) and reason filters (BOUNCE, COMPLAINT, or both). API operations with a TenantName parameter let you view and manage suppressed addresses.

📊 Connected Sheets removes CSV exports and turns Google Sheets into a live, secure interface to BigQuery, enabling business users to analyze petabytes of governed data without SQL. Admins retain security and governance by provisioning table or view access while preventing data alteration from Sheets. End users gain immediate agility using familiar tools like pivot tables, charts, and formulas to analyze billions of rows and create refreshable reports and hybrid models. Connecting requires a Google Workspace account and a billing-enabled Google Cloud project, with connections established either from Sheets or the BigQuery UI.

📊 Cloudflare built Town Lake, a lakehouse-style unified data analytics platform, and Skipper, an AI data agent, to make its vast telemetry and logs queryable and auditable. Town Lake combines Trino, Iceberg on R2, a metadata catalog, PII scanning, access control, and ELT tooling to provide fresh, accurate, and governed data. Skipper lets non-SQL users ask natural-language questions, produce correct SQL-backed answers, and create shareable charts and dashboards.

🔍 Data security posture management (DSPM) tools help security teams locate shadow data across cloud and on-premises systems to reduce data loss risk. These products focus on data discovery, classification, mapping, and risk assessment, complementing CSPM and other security platforms. The market has seen heavy M&A as vendors expand integrations and AI capabilities to address evolving cloud, AI, and hybrid data risks.

🚀 Amazon EMR now supports Apache Spark 4.0.2 across all deployment models, adding ANSI SQL and VARIANT data type support to simplify data pipelines. The release enables fine-grained access control (FGAC) for read and write operations on Lake Formation registered tables and adopts Apache Iceberg v3 for stronger transaction guarantees and lineage tracking. Enhanced streaming capabilities improve stateful processing and monitoring for real-time applications.

🧊 Amazon Redshift now writes directly to Apache Iceberg tables via the auto-mounted awsdatacatalog and supports ALTER TABLE DDL to change schema, partitioning, and table properties. Supported operations include ADD/DROP/ALTER columns, RENAME COLUMN, SET TABLE PROPERTIES, and ADD/DROP/REPLACE PARTITION FIELD to evolve partition strategies and compression settings. Tables modified by Redshift remain interoperable with other Iceberg engines and respect AWS Lake Formation permissions.

🔁 Amazon Aurora DSQL now supports change data capture (CDC) in preview, enabling real-time streaming of database changes directly to Amazon Kinesis Data Streams. The fully managed capability captures insert, update, and delete operations as discrete change events and removes the need to build and maintain custom streaming pipelines. It is designed for zero impact on database throughput and latency, requires no infrastructure setup, and integrates with AWS Lambda and Data Firehose for downstream delivery. CDC streaming in preview is available in all Regions where Aurora DSQL is offered and is billed using Distributed Processing Units (DPUs); standard Amazon Kinesis pricing applies separately.

⚡ Amazon ElastiCache now supports aggregation queries that let developers filter, group, transform, and summarize data directly in cache with a single query. By running aggregations in-memory, applications can deliver microsecond latencies across terabytes of data while returning results that reflect completed writes. The feature reduces architectural complexity by removing the need for a separate analytics engine and enables use cases such as faceted navigation, rollups, leaderboards, and real-time dashboards. Aggregations are available at no additional cost on node-based clusters running Valkey 9.0 in commercial, GovCloud, and China Regions.

🔍 Amazon ElastiCache now supports real-time hybrid search that combines vector similarity and full-text search in a single query, removing the need for a separate search service. New writes are searchable immediately, enabling microsecond latencies and up to 99% recall across billions of embeddings from providers such as Bedrock, SageMaker, Anthropic, and OpenAI. The feature is available at no additional cost for node-based clusters running Valkey 9.0+ in all commercial, GovCloud (US), and China Regions, and Valkey is recommended as a permissive, vendor-neutral alternative to Redis.

🔎 Amazon ElastiCache now provides real-time full-text, exact-match, and numeric range search directly in the cache, eliminating the need for a separate search service. Applications can query terabytes of frequently changing data with microsecond latency and up to millions of operations per second, and can combine search types in a single query to power complex filters. The capability is available in all commercial Regions, AWS GovCloud (US), and China Regions for node-based clusters running Valkey 9.0 at no additional cost; create or upgrade clusters via Console, SDK, or CLI.

🔄 AWS announces General Availability of AWS Entity Resolution incremental ML-based matching workflows. Customers can now process only newly added records rather than reprocessing entire datasets, cutting latency and infrastructure costs. The feature supports up to 50M incremental records against 1B historical records and processes 1M incremental records in under one hour.

🔎 Data security posture management (DSPM) is less about buying a single product and more about adopting a mindset: identify where sensitive data lives, quantify its value-at-risk, and use that information to prioritize remediation and investments. Full DSPM platforms can demand one to three dedicated FTEs to maintain, so many organizations should start with manual inventories, lightweight scanners or existing DLP outputs. The piece highlights practical scenarios—patch prioritization, M&A integrations, and IAM reviews—and warns that rising agentic AI and vendor access requirements make timely, measurable data discovery increasingly urgent in 2026.

🔒 New Cyber360 research shows the overlooked Zero Trust gap is not identity or endpoints but the movement of data across boundaries. The survey of 500 government, defense, and critical services leaders found 84% see cross-network data sharing as a heightened cyber risk and 53% still use manual transfer processes. That mismatch creates an attack surface as AI accelerates operations; layered approaches combining Zero Trust, data-centric controls, and cross-domain technologies are recommended for secure, near-real-time sharing.

📎 Amazon Connect now supports attachment file sizes up to 100 MB for chat, cases, and tasks, increased from the previous 20 MB limit. Administrators can enable the higher limits and configure custom file extensions for attachments across chat, email, cases, and tasks via the Amazon Connect admin website or APIs. This reduces back-and-forth by allowing customers to upload diagnostic bundles, log archives, signed contracts, and other larger documents directly during interactions; the feature is available in multiple AWS Regions.

🛰️ Google has extended geospatial analytics in BigQuery, integrating Google Earth AI models and new datasets to enable richer planetary and community insights. Announced at Google Cloud Next '26 and with recent March updates, the release includes Street View Insights (GA) with upcoming LiDAR, experimental Aerial and Satellite Insights, and licenseable Aerial & Satellite Models in Model Garden. These capabilities aim to accelerate infrastructure assessment, logistics planning, renewable-energy siting, and public-sector decision-making by bringing multi-perspective imagery and derived datasets directly into analytics workflows.

🔗 Amazon Athena now provides managed connectors for 12 external data sources, including DynamoDB, PostgreSQL, MySQL, and Snowflake, enabling queries against data outside Amazon S3 without deploying connector infrastructure. Athena creates and manages AWS Glue Data Catalog federated connectors on your behalf and registers each source as a federated catalog. You can query those sources alongside S3 data and optionally apply fine‑grained access controls through AWS Lake Formation. Federated queries are available in all standard AWS Regions except AWS GovCloud (US) and China Regions.

🚀 Google has previewed Spanner Omni, a downloadable edition of Spanner that runs outside Google Cloud — on-premises, multicloud, hybrid, and air-gapped environments. It delivers Spanner’s distributed SQL capabilities including high scalability, availability, strong consistency, and multimodal features while replacing cloud dependencies with a Colossus-like storage layer and a software TrueTime alternative. The developer preview is available for non-production use; commercial access requires engaging Google.

🚀 Google Cloud introduces its Agentic Data Cloud to remove the barrier between analytical history and live operational data, enabling real-time AI decisioning. By integrating AlloyDB, BigQuery, and Spanner with features like Lakehouse federation, Reverse ETL, Spanner Columnar Engine, and Datastream CDC, the platform aims to eliminate latency and brittle pipelines. It also expands Knowledge Catalog to provide unified governance and reduce agent hallucinations.

🧭 Google announced the Agentic Data Cloud, an AI-native architecture that integrates models, analytics, and operational databases to ground agentic applications in trusted, real-time data. The release emphasizes embedding AI across the data stack, unifying transactional and analytical workloads, and simplifying enterprise deployments. New developer tools include Vibe coding integrations with Google AI Studio, modular Tools for Data Agents and onboarding/observability agents, while AlloyDB gains large-scale vector search and optimized in-database AI functions.