New & Notable
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.
News
Alteryx One launch aims to unify, simplify vendor's platform
The updated version of the data integration vendor's platform aims to make it easier to prepare data for AI and analytics, while new GenAI tools further simplify data preparation.
News
Databricks adds Postgres database with $1B Neon acquisition
The vendor's latest purchase comes six months after it raised $10B in funding. By adding PostgreSQL database capabilities, it aims to better enable users to build AI applications.
News
Boomi launches agentic AI development tools, support for MCP
The longtime iPaaS vendor continues to expand beyond its historical base with the additions of Agentstudio, agents that simplify integration and change data capture capabilities.
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Data science and analytics Evaluate
8 top cloud analytics certifications
Cloud data analytics certifications enhance careers and business efficiency. Compare costs, skills taught and time required to earn top credentials.
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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
Alation boosts agentic AI with Numbers Station acquisition
The acquisition adds capabilities such as Chat that enable users to embed agents in workflows to complement the vendor's existing plans for agentic development.
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Data Integration 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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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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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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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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Turning data into a strategic advantage
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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 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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Get Started
What is data profiling?
Data profiling refers to the process of examining, analyzing, reviewing and summarizing data sets to gain insight into the quality of data.
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Vendor Resources
- CW APAC May 2025 – Trend Watch: API management –Ezine
- The New Rules of Data Management –White Paper
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Data management strategies
Alation boosts agentic AI with Numbers Station acquisition
The acquisition adds capabilities such as Chat that enable users to embed agents in workflows to complement the vendor's existing plans for agentic development.
-
Data governance
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.
-
Data management strategies
Alteryx One launch aims to unify, simplify vendor's platform
The updated version of the data integration vendor's platform aims to make it easier to prepare data for AI and analytics, while new GenAI tools further simplify data preparation.
Search Data Management Definitions
- 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?
- What is Microsoft Visual FoxPro (VFP)?