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SingleStore boosts database performance to meet AI needs
With AI development and deployment imposing greater workload demands on data management systems than traditional analytics, the vendor's latest update targets efficiency at scale.
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Whoop pushing AI limits powered by Snowflake
The wearable health and fitness technology vendor has already put advanced applications into production for its workers, with plans to dramatically expand over the next year.
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Why data platforms matter for AI agents and MCP success
AI agents and Model Context Protocol systems depend on fast, scalable access to diverse data. Modern data platforms deliver that access across fragmented enterprise environments.
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Customers pleased with Snowflake plans for AI
Features including a multimodal data ingestion and integration service that enables access to unstructured data demonstrate the vendor's move toward enabling app development.
Trending Topics
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Data science and analytics News
Latest Databricks tools use AI to simplify AI development
Fueled by user feedback, the vendor's newest features include a framework that automates building agents and a no-code interface for creating the pipelines that feed applications.
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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
EnterpriseDB targets AI development with latest update
A low-code/no-code interface and data observability across hybrid environments address the challenges enterprises face moving AI projects beyond development and into production.
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Data Integration News
Customers pleased with Snowflake plans for AI
Features including a multimodal data ingestion and integration service that enables access to unstructured data demonstrate the vendor's move toward enabling app development.
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Data Governance News
Addition of new AI capabilities shows Starburst's growth
The open source data lakehouse vendor continues to evolve beyond being a data mesh specialist with the additions of agentic tools, a development environment and a data catalog.
Sponsored Sites
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Collaboration
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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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Why data platforms matter for AI agents and MCP success
AI agents and Model Context Protocol systems depend on fast, scalable access to diverse data. Modern data platforms deliver that access across fragmented enterprise environments.
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The difference between data cleansing and data transformation
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Unified databases: A powerhouse behind generative AI success
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AI's appetite for data is changing data requirements
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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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Hybrid data management strategy for enterprise AI success
Hybrid data management gives organizations the access, control and agility needed to support reliable and scalable enterprise AI across various environments.
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AI data governance is a requirement, not a luxury
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Top trends in big data for 2025 and beyond
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Human oversight enables automated data governance
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Data Management/Data Warehousing Basics
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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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Get Started
What is data transformation? Definition, types and benefits
Data transformation is the process of converting data from one format -- such as a database file, Extensible Markup Language (XML) document or Excel spreadsheet -- into another format.
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Get Started
The difference between data cleansing and data transformation
Data cleansing corrects errors to improve data quality, while data transformation changes data format and structure to support analytics processes.
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Vendor Resources
- Modernize It Services And Operations With AI –White Paper
- The asset evolution Breaking free from traditional approaches to drive growth –eBook
- Conquering Tail Spend in 2025 –Analyst Report
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Data management strategies
EnterpriseDB targets AI development with latest update
A low-code/no-code interface and data observability across hybrid environments address the challenges enterprises face moving AI projects beyond development and into production.
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Data management strategies
SingleStore boosts database performance to meet AI needs
With AI development and deployment imposing greater workload demands on data management systems than traditional analytics, the vendor's latest update targets efficiency at scale.
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Data management strategies
Snowflake continues to add AI, boost Cortex capabilities
Features that enable users to develop agents, coupled with the integration of agentic capabilities into the vendor's own platform, show the vendor's growth beyond data management.
Search Data Management Definitions
- 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)?
- What is data egress? How it works and how to manage costs
- What is data?