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How data for AI is changing the modern data platform
Data platforms must evolve to meet AI requirements, with a greater focus on real-time integration, unified governance, infrastructure flexibility and data quality.
News
Microsoft, Databricks simplify synchronizing, sharing data
A new integration designed by the tech giant and data platform vendor eliminates the need for users to move or copy data to join it across platforms for better-informed analysis.
News
SnapLogic adds MCP support to aid agentic AI deployment
Following the launch of AgentCreator in 2024, the data integration vendor is adding support for the open standard to better enable customers to build and manage agentic tools.
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Qdrant lowers vector database complexity to aid development
The vendor now provides an integrated environment for operationalizing unstructured data to aid enterprises struggling with a profusion of tools to generate and manage vectors.
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Data science and analytics Manage
7 predictive analytics skills to improve simulation modeling
Predictive analytics skills such as statistical analysis, data preprocessing and model evaluation can help data professionals build more accurate, dynamic simulation models.
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Database Management News
Informatica to build agents, foster agentic AI development
With agents now a major trend in data management, the vendor plans to join the fray by developing agentic capabilities and providing customers with the tools to do the same.
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Data Warehousing News
Oracle Exadata update boosts performance to meet AI needs
With database workloads growing due to the demands of AI development and real-time analytics, the tech giant's latest database infrastructure update focuses on efficiency.
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Data Management Strategies News
Ataccama targets business users with latest AI capabilities
The vendor's latest update makes data lineage accessible to business users, enabling them to trust their data and make decisions without consulting trained experts for assistance.
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Data Integration News
Qdrant lowers vector database complexity to aid development
The vendor now provides an integrated environment for operationalizing unstructured data to aid enterprises struggling with a profusion of tools to generate and manage vectors.
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Data Governance Manage
Enterprise data platforms adapt for GenAI and agentic AI
Generative and agentic AI are redefining enterprise data strategy as platforms evolve to support new demands for quality, access and governance.
Sponsored Sites
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Data Management
Intel and Microsoft: Intelligent Edge to Cloud Solutions
Microsoft and Intel build on long-standing co-engineering efforts to enable differentiated services within Azure. By combining innovative software and services with cutting-edge hardware, the Intel and Microsoft partnership delivers state-of-the-art-edge to cloud solutions for Industrial IoT and computer vision edge AI, SAP on Azure, high-performance computing (HPC), confidential computing, hybrid cloud, Microsoft SQL Server, AI, analytics, and more.
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Collaboration
Increase Productivity with a Scalable Collaboration Solution
Learn how Slack offers significant advantages in scalability, security, platform depth and integrations, engagement, and shared channels are valued by organisations when undertaking digital transformation initiatives.
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Cloud
Optimize Your Cloud Migration with AWS & Infoblox
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Data warehouse vs. data mart: Key differences and use cases
Data warehouses support integrated, governed reporting, while data marts offer faster, focused insights. Together they provide scalable, adaptable data strategies.
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Why Apache Iceberg is essential for modern data lakehouses
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Why data platforms matter for AI agents and MCP success
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The difference between data cleansing and data transformation
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Problem Solve
7 data cleansing best practices
Organizations rely on data for analytics and decision-making, but if that data is flawed, inconsistent or otherwise unreliable, it's not as valuable.
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10 data governance challenges that can sink data operations
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6 dimensions of data quality boost data performance
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Data lake governance: Benefits, challenges and getting started
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How data for AI is changing the modern data platform
Data platforms must evolve to meet AI requirements, with a greater focus on real-time integration, unified governance, infrastructure flexibility and data quality.
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Enterprise data platforms adapt for GenAI and agentic AI
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Hybrid data management strategy for enterprise AI success
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AI data governance is a requirement, not a luxury
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Data Management/Data Warehousing Basics
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What is data orchestration?
Data orchestration is the process of automating, coordinating and organizing the movement of data across an enterprise through business intelligence (BI) and other analytical tools.
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Get Started
What is database as a service (DBaaS)?
Database as a service (DBaaS) is a cloud computing managed service offering that provides access to a database without requiring the setup of physical hardware, the installation of software or the need to configure the database.
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Get Started
What is stream processing? Introduction and overview
Stream processing is a data management technique that involves ingesting a continuous data stream to quickly analyze, filter, transform or enhance the data in real time.
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Data management strategies
Ataccama targets business users with latest AI capabilities
The vendor's latest update makes data lineage accessible to business users, enabling them to trust their data and make decisions without consulting trained experts for assistance.
-
Data management strategies
Microsoft, Databricks simplify synchronizing, sharing data
A new integration designed by the tech giant and data platform vendor eliminates the need for users to move or copy data to join it across platforms for better-informed analysis.
-
Data management strategies
SnapLogic adds MCP support to aid agentic AI deployment
Following the launch of AgentCreator in 2024, the data integration vendor is adding support for the open standard to better enable customers to build and manage agentic tools.
Search Data Management Definitions
- What is data orchestration?
- What is database as a service (DBaaS)?
- What is stream processing? Introduction and overview
- What is data transformation? Definition, types and benefits
- What is data profiling?
- What is a data lake?
- What is data preprocessing? Key steps and techniques
- What is data cleansing (data cleaning, data scrubbing)?