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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.
News
Denodo unveils DeepQuery to provide AI-powered deep analysis
The data virtualization specialist's new GenAI feature lets users dig deep into their data to discover the reasons underlying what's happening within their organization.
News
Confluent platform update targets performance, simplicity
The vendor's latest release replaces its coordinating technology to make its tools easier to use and updates its Control Center for more efficient streaming data workloads.
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New Actian features target data discoverability, reliability
Automatically embedded data governance, data product registration on a data marketplace platform and a natural language interface aim to make trusted data easier to discover.
Trending Topics
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Data science and analytics Evaluate
Data science applications across industries in 2025
Industries like healthcare, retail and finance use data science applications to improve diagnostics, optimize operations, forecast trends and prevent fraud.
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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
Confluent platform update targets performance, simplicity
The vendor's latest release replaces its coordinating technology to make its tools easier to use and updates its Control Center for more efficient streaming data workloads.
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Data Integration Evaluate
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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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.
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Storage
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AWS & Red Hat
Simplify App Modernization and Innovation with Red Hat OpenShift Service on AWS
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Evaluate
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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Manage
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 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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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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Data integration
Denodo unveils DeepQuery to provide AI-powered deep analysis
The data virtualization specialist's new GenAI feature lets users dig deep into their data to discover the reasons underlying what's happening within their organization.
-
Data management strategies
Confluent platform update targets performance, simplicity
The vendor's latest release replaces its coordinating technology to make its tools easier to use and updates its Control Center for more efficient streaming data workloads.
-
Data management strategies
New Actian features target data discoverability, reliability
Automatically embedded data governance, data product registration on a data marketplace platform and a natural language interface aim to make trusted data easier to discover.
Search Data Management Definitions
- 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)?
- What is data egress? How it works and how to manage costs