#data-warehouse
#data-warehouse

Google Cloud and Wiz build multi-cloud platform on top of Security Graph

Wiz is essential for Google Cloud's security strategy in multi-cloud environments post-acquisition.

Business

from24/7 Wall St.

Forget Nvidia: Why HPE Could Be the Overlooked AI Infrastructure Play of 2026

Hewlett Packard Enterprise is an overlooked investment opportunity in AI infrastructure with strong financial growth and expanding margins.

Scala

Lakehouse Tower of Babel: Handling Identifier Resolution Rules Across Database Engines

Open table formats standardize data semantics but lack SQL dialect interoperability, complicating identifier resolution across different engines.

Google pitches Agentic Data Cloud to help enterprises turn data into context for AI agents

Google is enhancing its data and analytics portfolio to compete with AWS and Microsoft in AI data management.

fromTechRepublic

2 years ago

What is Cloud Security? Fundamental Guide

Cloud security requires specialized processes and technologies to protect assets and data from evolving threats in a dynamic environment.

#ai-integration

How to Evaluate AI Tools Without Being a Data Scientist

Many organizations struggle to integrate AI effectively, with only 25% having done so despite plans for increased spending.

fromWWD

Marketing tech

SAP and Google Cloud Join Forces to Revolutionize AI-Driven Marketing

SAP SE and Google Cloud are integrating AI agents to enhance marketing strategies through unified data access and multi-agent orchestration.

How to Evaluate AI Tools Without Being a Data Scientist

Many organizations struggle to integrate AI effectively, with only 25% having done so despite plans for increased spending.

fromWWD

SAP and Google Cloud Join Forces to Revolutionize AI-Driven Marketing

SAP SE and Google Cloud are integrating AI agents to enhance marketing strategies through unified data access and multi-agent orchestration.

Addressing the challenges of unstructured data governance for AI

Enterprises must enhance data governance for unstructured data as AI transforms data management practices.

Microsoft to test third-party AI models for incorporation in its security offerings

Microsoft is evaluating third-party AI systems to enhance its cybersecurity measures against AI-driven threats.

Microsoft Fabric Database Hub dubbed 'partial' solution

Microsoft's Fabric Database Hub offers a centralized management solution for its database services but lacks support for non-Microsoft databases.

fromNextgov.com

Microsoft to test third-party AI models for incorporation in its security offerings

Microsoft is evaluating third-party AI systems to enhance its cybersecurity measures against AI-driven threats.

Microsoft Fabric Database Hub dubbed 'partial' solution

Microsoft's Fabric Database Hub offers a centralized management solution for its database services but lacks support for non-Microsoft databases.

Why cloud computing still runs on coal and gas

Data centers' energy demands are straining U.S. power grids, leading to reliance on fossil fuels and delaying renewable energy goals.

AI is reshaping Britain's datacenter map away from London

UK AI datacenter capacity may shift from London due to power shortages and planning constraints, making other locations more appealing.

fromTechRepublic

AI Demand Is Forcing a Rethink of Data Center Power, Cooling

AI's rapid growth is challenging data center infrastructure, necessitating rethinking of power, cooling, and construction strategies.

Your AI can't read an invoice. That should worry you more than whether it can pass a math exam

Advanced AI excels in structured reasoning tasks but struggles with messy, real-world data extraction like invoices.

Google Cloud Next: It's time to create value, not slop, from the AI boom | Computer Weekly

AI mania raises concerns about reckless applications similar to the historical misuse of radium, highlighting the need for caution and understanding.

AI is upending the SaaS game

AI significantly enhances log examination by quickly identifying issues, making data production more valuable than mere interpretation.

How to mitigate the risk of AI implementation in enterprise environments

Only about 5% of AI projects deliver measurable business value despite high expectations.

London startup

6 days ago

AI is reshaping Britain's datacenter map away from London

UK AI datacenter capacity may shift from London due to power shortages and planning constraints, making other locations more appealing.

fromTechRepublic

AI Demand Is Forcing a Rethink of Data Center Power, Cooling

AI's rapid growth is challenging data center infrastructure, necessitating rethinking of power, cooling, and construction strategies.

Your AI can't read an invoice. That should worry you more than whether it can pass a math exam

Advanced AI excels in structured reasoning tasks but struggles with messy, real-world data extraction like invoices.

Google Cloud Next: It's time to create value, not slop, from the AI boom | Computer Weekly

AI mania raises concerns about reckless applications similar to the historical misuse of radium, highlighting the need for caution and understanding.

AI is upending the SaaS game

AI significantly enhances log examination by quickly identifying issues, making data production more valuable than mere interpretation.

How to mitigate the risk of AI implementation in enterprise environments

Only about 5% of AI projects deliver measurable business value despite high expectations.

more#ai

fromEntrepreneur

The Hidden Data Liability Every Leader Needs to Address Now

Data is no longer endlessly renewable; companies face a 'data liability gap' affecting AI systems and data recovery responsibilities.

fromThe Hacker News

Bridging the AI Agent Authority Gap: Continuous Observability as the Decision Engine

AI agents create a delegation gap in enterprise security that must be addressed before governing their authority.

fromComputerworld

Adobe builds an 'agentic content supply chain' for the AI era

Adobe's new tools automate content creation and enhance branding through generative AI and agentic assistants.

fromDevOps.com

Why Contact Enrichment Belongs in Your Application Architecture, Not Your Sales Workflow - DevOps.com

B2B applications often collect incomplete data, which can be resolved by integrating contact enrichment at the data ingestion point.

Orchestrating Agentic and Multimodal AI Pipelines with Apache Camel

AI systems require well-managed execution frameworks to avoid failures, as issues often stem from system design rather than model quality.

Blackbox replaces two racks of HPE storage with 8U of Everpure | Computer Weekly

Blackbox Hosting has consolidated storage from two full racks down to just 8U of rack space following migration to Everpure FlashArray hardware, achieving a 10:1 data reduction ratio and an 85% reduction in power utilization.

DevOps

fromAdExchanger

Going Global? Contextual AI Needs To Be Your Strategy | AdExchanger

US brands need to prioritize contextual targeting for effective global marketing strategies, as cultural nuances significantly impact engagement and attention.

#snowflake

Django

Snowflake Supports Directory Imports

Snowflake offers help to users and builders of AI agents

Snowflake enhances its Intelligence and Cortex Code for better automation and data source access, aiming for a unified enterprise AI experience.

Artificial intelligence

Snowflake Intelligence and Cortex Code become the agentic AI control layer

Artificial intelligence

Snowflake's ongoing pitch: bring AI to data, not vice versa

Django

Snowflake Supports Directory Imports

Easier package imports into Snowflake functions and procedures from stage directories and SnowGit directories streamline development and deployment.

Snowflake offers help to users and builders of AI agents

Snowflake enhances its Intelligence and Cortex Code for better automation and data source access, aiming for a unified enterprise AI experience.

Snowflake Intelligence and Cortex Code become the agentic AI control layer

Snowflake updates Intelligence and Cortex Code to enhance data integration and AI capabilities for the Agentic Enterprise.

Snowflake's ongoing pitch: bring AI to data, not vice versa

Snowflake is enhancing its platform for AI integration through strategic partnerships and acquisitions, focusing on customer ROI and data management efficiency.

more#snowflake

#ai-strategy

fromeLearning Industry

AI Strategy Framework: A Proven Model For Building And Scaling AI Initiatives

A structured AI strategy framework is essential for scalable transformation and measurable impact across organizations.

Google says it has all the answers for AI agent sprawl

Google has rebranded its AI platform to Gemini Enterprise Agent Platform to manage multiple AI agents effectively.

fromeLearning Industry

AI Strategy Framework: A Proven Model For Building And Scaling AI Initiatives

A structured AI strategy framework is essential for scalable transformation and measurable impact across organizations.

Google says it has all the answers for AI agent sprawl

Google has rebranded its AI platform to Gemini Enterprise Agent Platform to manage multiple AI agents effectively.

Is the Data Scientist Role Dead? No, it's Transforming

The data scientist role is evolving, not disappearing, as organizations demand broader skills and system-oriented thinking.

The DBMS chart that shows Oracle's crown is slowly slipping

Dominant database vendors are losing market share to emerging competitors, with only Microsoft showing growth since 2011.

fromNextgov.com

Data is a strategic asset and a strategic vulnerability

Data is a primary strategic asset in national security, transforming into both a powerful tool and a critical vulnerability.

fromEntrepreneur

Your Business Already Has the Most Valuable AI Asset. You Just Haven't Extracted It Yet.

Business leaders using AI often feel satisfied but lack competitiveness, highlighting a gap that needs addressing for sustained success.

6 days ago

Storage implications of a modern IT architecture | Computer Weekly

Organizations are increasingly using containers to modernize applications and manage both cloud-native and traditional workloads with Kubernetes.

fromTNW | Data-Security

Why data quality matters when working with data at scale

Data quality should be prioritized from the start to prevent costly issues later in data engineering projects.

#google-cloud

Google on why its all-in-one AI stack embraces competitors

Google Cloud has a unique advantage with its integrated AI infrastructure, models, and data platform, essential for enterprise AI value.

Google Cloud introduces QueryData to help AI agents create reliable database queries

QueryData enhances AI agents' accuracy in querying databases by translating natural language into precise database queries.

fromFortune

Google Cloud's next big moment-and what it needs to continue its ascent | Fortune

Google's AI advancements are revitalizing its cloud division, with significant revenue growth and a focus on addressing bottlenecks in AI implementation.

Google on why its all-in-one AI stack embraces competitors

Google Cloud has a unique advantage with its integrated AI infrastructure, models, and data platform, essential for enterprise AI value.

Google Cloud introduces QueryData to help AI agents create reliable database queries

QueryData enhances AI agents' accuracy in querying databases by translating natural language into precise database queries.

fromFortune

Google Cloud's next big moment-and what it needs to continue its ascent | Fortune

Google's AI advancements are revitalizing its cloud division, with significant revenue growth and a focus on addressing bottlenecks in AI implementation.

more#google-cloud

from3blmedia

3BL's Audience Data: Professional, Demographic, a

3BL's Audience Analytics helps communications teams understand audience engagement through professional, demographic, and geographic perspectives.

fromAdExchanger

AI Is Nothing Without Data Fidelity. Here's A Four-Step Approach to Protect It | AdExchanger

Data integrity is crucial for effective AI in advertising, as flawed data leads to poor outcomes.

Workday, Rippling, Slack lflunk data access test: Fivetran

Workday, Rippling, and Slack perform poorly in enterprise data movement, impacting analytics and AI integration.

from24/7 Wall St.

Oracle's New AWS Partnership Just Put It Ahead of Azure and Google Cloud

Multicloud setups are essential for enterprise AI, enabling seamless data movement and integration across different cloud providers.

Tredence powers up Gemini-powered agentic AI accelerators

Tredence's agentic AI accelerators provide ready-to-deploy, industry-specific AI solutions for rapid deployment and data modernization.

The agent tier: Rethinking runtime architecture for context-driven enterprise workflows

Digital workflows in large enterprises struggle to adapt to contextual variations, leading to increased complexity and challenges in customer onboarding processes.

fromeLearning Industry

6 days ago

AI Consulting Explained: What Services Companies Actually Need (And What To Avoid)

AI consulting is rapidly growing, driven by enterprise AI adoption and the need for strategic transformation partnerships.

Data, not infrastructure, must drive your AI strategy

Data centricity is essential for effective AI strategies, enabling collaboration and problem-solving across business units by making data accessible.

#agentic-ai

Qlik brings agentic execution to data engineering

Qlik is enhancing its data engineering capabilities with four new features to accelerate AI-ready data delivery for data teams.

Databricks launches Lakewatch: agentic SIEM on the Lakehouse

Lakewatch is an open SIEM platform that consolidates security, IT, and business data, enabling rapid threat detection and response using AI agents.

Qlik brings agentic execution to data engineering

Qlik is enhancing its data engineering capabilities with four new features to accelerate AI-ready data delivery for data teams.

Databricks launches Lakewatch: agentic SIEM on the Lakehouse

Lakewatch is an open SIEM platform that consolidates security, IT, and business data, enabling rapid threat detection and response using AI agents.

more#agentic-ai

fromTearsheet

Why the back office comes first in AI deployments and failures that keep reappearing - Tearsheet

67% of banks and credit unions are implementing AI, but only 16% have a coherent strategy for it.

Observability warehouses, the next structural evolution for telemetry

Observability is essential for real-time insights in cloud systems, helping to reduce downtime and improve performance.

DevOps

Snowflake updates developer tools, adds observability features

Observability warehouses, the next structural evolution for telemetry

Observability is essential for real-time insights in cloud systems, helping to reduce downtime and improve performance.

DevOps

Snowflake updates developer tools, adds observability features

more#observability

fromZDNET

I asked 5 data leaders about how they use AI to automate - and end integration nightmares

Strong processes and AI integration are essential for businesses to effectively utilize data.

AI is changing the way we think about databases

Developers have spent the past decade trying to forget databases exist. Not literally, of course. We still store petabytes. But for the average developer, the database became an implementation detail; an essential but staid utility layer we worked hard not to think about. We abstracted it behind object-relational mappers (ORM). We wrapped it in APIs. We stuffed semi-structured objects into columns and told ourselves it was flexible.

Software development

4 steps to create a future-proof data infrastructure

A future-proof IT infrastructure is often positioned as a universal solution that can withstand any change. However, such a solution does not exist. Nevertheless, future-proofing is an important concept for IT leaders navigating continuous technological developments and security risks, all while ensuring that daily business operations continue. The challenge is finding a balance between reactive problem solving and proactive planning, because overlooking a change can cost your organization. So, how do you successfully prepare for the future without that one-size-fits-all solution?

Tech industry

fromDbmaestro

5 years ago

5 Pillars of Database Compliance Automation |

There is a growing emphasis on database compliance today due to the stricter enforcement of compliance rules and regulations to safeguard user privacy. For example, GDPR fines can reach £17.5 million or 4% of annual global turnover (the higher of the two applies). Besides the direct monetary implications, companies also need to prioritize compliance to protect their brand reputation and achieve growth.

EU data protection

Software development

Unified Databricks Repository for Scala and Python Data Pipelines

Databricks repositories require structured setup with Gradle for multi-language support, dependency management, and version control to scale beyond manual notebook maintenance.

Building Consistent Data Foundations at Scale

Building consistent data foundations through intentional architecture, engineering, and governance is essential to prevent fragmentation, support AI adoption, ensure regulatory compliance, and enable reliable organizational decisions at scale.

Startup companies

Etleap Launches Iceberg Pipeline Platform to Simplify Enterprise Adoption of Apache Iceberg

Managed Iceberg pipeline platform unifies ingestion, transformation, orchestration, and table operations inside customers' VPCs, enabling enterprise Iceberg adoption without building custom stacks.

Migrating to the Lakehouse Without the Big Bang: An Incremental Approach

Query federation enables safe, incremental lakehouse migration by allowing simultaneous queries across legacy warehouses and new lakehouse systems without risky big bang cutover approaches.

Update your databases now to avoid data debt

Multiple major open source databases reach end-of-life in 2026, requiring teams to plan upgrades and migrations to avoid security risks and higher costs.

fromSecuritymagazine

Product Spotlight on Analytics

Taelor Sutherland is Associate Editor at Security magazine covering enterprise security, coordinating digital content, and holding a BA in English Literature from Agnes Scott College.

Snowflake's new 'autonomous' AI layer aims to do the work, not just answer questions

Project SnowWork is Snowflake's autonomous AI layer that automates data analysis tasks like forecasting, churn analysis, and report generation without requiring data team intervention.

Beyond the Warehouse: Why BigQuery Alone Won't Solve Your Data Problems

Data warehouses like BigQuery perform well initially but become slow, costly, and disorganized at scale, undermining low-latency operational use and innovation.

Snowflake debuts Cortex Code, an AI agent that understands enterprise data context

Cortex Code enables developers to use natural language to build, optimize, and deploy governed, production-ready data pipelines, analytics, ML workloads, and AI agents.

fromCIO

5 perspectives on modern data analytics

Data/business analytics is the top IT investment priority, yet analytics projects often fail due to poor data, vague objectives, and one-size-fits-all solutions.

fromEntrepreneur

The Game-Changing Tech Saving Companies From Data Disasters

Combining Continuous Data Protection with AI capabilities enables businesses to achieve near-zero Recovery Point Objectives and minimal Recovery Time Objectives, preventing data loss and minimizing downtime.

Databricks Introduces Lakebase, a PostgreSQL Database for AI Workloads

Databricks Lakebase is a serverless PostgreSQL OLTP database that separates compute from storage and unifies transactional and analytical capabilities.

Dataiku introduces platform for scalable enterprise AI

Dataiku launches Platform for AI Success with three new products designed to move AI initiatives from pilots to measurable business outcomes through unified orchestration across cloud providers.

Beware of data hubris

Organizations are drowning in dashboards, KPIs, performance metrics, behavioral traces, biometric indicators, predictive scores, engagement rates, and AI-generated forecasts. We have more data than we know what to do with. We pretend that the mere presence of data guarantees clarity. It does not. That's data hubris—the arrogant belief that because something can be measured, it can be mastered.

Business intelligence

Why AI requires rethinking the storage-compute divide

AI workloads require continuous processing of unstructured multimodal data, causing redundant data movement and transformation that wastes infrastructure costs and data scientist time.

Extracting AI-Ready Data From Organizational Documents

Poor document extraction corrupts retrieval; preserving document structure at ingestion produces reliable embeddings and trustworthy RAG outputs.