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MongoDB launches enterprise-focused AI models
The vendor's new models enhance document context capture and enable developers to guide the reranking process with instructions, while improving accuracy.
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Top data quality management tools in 2025
Data quality management tools provide profiling, cleansing and monitoring features that keep enterprise data accurate and consistent across analytics and governance efforts.
News
Aerospike update aims to improve database performance
With the addition of expression indexes that enable users to streamline the data discovery process, the vendor is providing capabilities that could force competitors to respond.
Evaluate
Is Apache Iceberg worth a full migration?
Apache Iceberg delivers modern data lake features, but adoption depends on existing architecture, team resources and tolerance for migration complexity.
Trending Topics
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Data science and analytics Evaluate
What makes an effective data science team structure?
Data science team structures vary in strength, and their success depends on how roles and leadership align with business goals to meet analytics needs.
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Database Management News
Aerospike update aims to improve database performance
With the addition of expression indexes that enable users to streamline the data discovery process, the vendor is providing capabilities that could force competitors to respond.
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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
Modern architecture, high-quality data key to AI development
An expert explains how components such as a shared foundation and protocols that ensure quality help foster real-time insights and AI-driven analysis.
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Data Integration News
Oracle adds MCP support to advance agentic AI development
Given that the open standard simplifies the complex process of connecting systems during agentic AI development, the tech giant's integration with MCP stands to benefit users.
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Data Governance Evaluate
Top data quality management tools in 2025
Data quality management tools provide profiling, cleansing and monitoring features that keep enterprise data accurate and consistent across analytics and governance efforts.
Sponsored Sites
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Generative AI
Enhancing Generative AI for Independent Software Vendors (ISVs)
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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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Storage
Benefit From the Power of Consolidated Storage
Learn how a consolidated approach to storage can modernize your storage which will increase efficiency and can decrease costs.
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Find Solutions For Your Project
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Evaluate
Top data quality management tools in 2025
Data quality management tools provide profiling, cleansing and monitoring features that keep enterprise data accurate and consistent across analytics and governance efforts.
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Is Apache Iceberg worth a full migration?
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Hadoop vs. Spark for modern data pipelines
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Data lake vs. data warehouse: Key differences explained
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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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Manage
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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Get Started
What is data quality and why is it important?
Data quality measures a data set's condition based on factors such as accuracy, completeness, consistency, timeliness, uniqueness and validity.
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Get Started
What is data automation?
Data automation is the use of software tools and infrastructure to streamline data management tasks. Data automation techniques intentionally limit human interaction with data-related jobs.
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Get Started
What is data lineage? Techniques, best practices and tools
Organizations can bolster data governance efforts by tracking the lineage of data in their systems. Get advice on how to do so and how data lineage tools can help.
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Vendor Resources
- CARE TRENDS REPORT 2025 –Research Content
- Bridging IT and OT: Challenges and Opportunities –eBook
- AI in the Workplace Playbook –eBook
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News
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Data management strategies
Modern architecture, high-quality data key to AI development
An expert explains how components such as a shared foundation and protocols that ensure quality help foster real-time insights and AI-driven analysis.
-
Data management strategies
MongoDB launches enterprise-focused AI models
The vendor's new models enhance document context capture and enable developers to guide the reranking process with instructions, while improving accuracy.
-
Database management
Aerospike update aims to improve database performance
With the addition of expression indexes that enable users to streamline the data discovery process, the vendor is providing capabilities that could force competitors to respond.
Search Data Management Definitions
- What is data quality and why is it important?
- What is data automation?
- What is data orchestration?
- What is database as a service (DBaaS)?
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- What is data transformation? Definition, types and benefits
- What is data profiling?
- What is a data lake?