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Collibra's acquisition of Deasy targets unstructured data
With AI development on the rise, the vendor's latest purchase better enables customers to combine the complete array of relevant data to inform advanced applications.
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StarTree adding Iceberg support to simplify, speed analysis
With open table data storage formats gaining popularity, the vendor's pending support for Apache Iceberg promotes flexibility while also making analysis more efficient.
StarTree adding Iceberg support to simplify, speed analysis
With open table data storage formats gaining popularity, the vendor's pending support for Apache Iceberg promotes flexibility while also making analysis more efficient.
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Data lake vs. data warehouse: Key differences explained
Data lakes and data warehouses differ in structure, processing and use cases, offering distinct advantages for enterprise analytics and data strategies.
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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
StarTree adding Iceberg support to simplify, speed analysis
With open table data storage formats gaining popularity, the vendor's pending support for Apache Iceberg promotes flexibility while also making analysis more efficient.
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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 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.
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Simplify App Modernization and Innovation with Red Hat OpenShift Service on AWS
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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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Data lake vs. data warehouse: Key differences explained
Data lakes and data warehouses differ in structure, processing and use cases, offering distinct advantages for enterprise analytics and data strategies.
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Data warehouse vs. data mart: Key differences and use cases
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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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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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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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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
StarTree adding Iceberg support to simplify, speed analysis
With open table data storage formats gaining popularity, the vendor's pending support for Apache Iceberg promotes flexibility while also making analysis more efficient.
-
Data management strategies
StarTree adding Iceberg support to simplify, speed analysis
With open table data storage formats gaining popularity, the vendor's pending support for Apache Iceberg promotes flexibility while also making analysis more efficient.
-
Data integration
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.
Search Data Management Definitions
- What is data orchestration?
- What is database as a service (DBaaS)?
- What is stream processing? Introduction and overview
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- What is a data lake?
- What is data preprocessing? Key steps and techniques
- What is data cleansing (data cleaning, data scrubbing)?