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Vast Data targets secure, speedy agentic AI development
The vendor is furthering its expansion into AI development with features such as vector search and event streaming aimed at enabling users to build and maintain agents.
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New Databricks tools tackle lingering GenAI accuracy issues
Features such as centralized model governance and real-time monitoring aim to improve the accuracy of outputs so that enterprises can confidently scale beyond experimentation.
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Qdrant update adds security measures for AI development
The vector database specialist's update includes features that enable secure AI development such as role-based access control and an API for managing cloud deployments.
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Alation unveils AI agents plus SDK for agentic development
The data catalog vendor's new agents for documentation and data quality monitoring represent innovation among metadata management vendors and could force competitors to respond.
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Data science and analytics Evaluate
The pros and cons of self-service analytics
Self-service analytics lowers skill barriers for data use but does require training and financial investment. Evaluate the pros and cons before deciding if it's the right fit.
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Database Management News
Pinecone provides Assistant for generative AI development
The vector database specialist is expanding beyond managing data with a suite of APIs and other tools that enable users to tap into their data to create chatbots and agents.
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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
AWS unifies analytics and AI development in SageMaker
In a move that brings previously disparate analytics and AI development tasks together in one environment with data management, Unified Studio is now generally available.
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Data Integration News
Alation unveils AI agents plus SDK for agentic development
The data catalog vendor's new agents for documentation and data quality monitoring represent innovation among metadata management vendors and could force competitors to respond.
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Data Governance Manage
AI data governance is a requirement, not a luxury
Data governance is the backbone of any data initiative. Properly managing the new data risks and regulations of AI technologies requires the addition of AI data governance.
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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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Digital Migration
Migrate Off CentOS Linux With Confidence
CentOS Project will discontinue updates and releases of CentOS Linux® version 7 leaving many organizations to have to plan for a migration. Learn how easy it is to convert from CentOS to Red Hat Enterprise Linux on AWS.
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Collaboration
Increase Productivity with a Scalable Collaboration Solution
Learn how Slack offers significant advantages in scalability, security, platform depth and integrations, engagement, and shared channels are valued by organisations when undertaking digital transformation initiatives.
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AI relies on high-quality real-time data. Companies that fail to modernize their data strategies risk falling behind, while those that adapt unlock AI's competitive advantage.
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Turning data into a strategic advantage
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18 top data catalog software tools to consider using in 2025
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No organization can successfully use data without data governance. Addressing 10 data governance challenges is necessary to avoid financial loss and reputation damage.
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Data lake governance: Benefits, challenges and getting started
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NoSQL database types explained: Key-value store
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Data Management/Data Warehousing Basics
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What is data preprocessing? Key steps and techniques
Data preprocessing, a component of data preparation, describes any type of processing performed on raw data to prepare it for another data processing procedure.
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What is data cleansing (data cleaning, data scrubbing)?
Data cleansing, also referred to as data cleaning or data scrubbing, is the process of fixing incorrect, incomplete, duplicate or otherwise erroneous data in a data set.
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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 document or Excel spreadsheet -- into another.
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Data management strategies
AWS unifies analytics and AI development in SageMaker
In a move that brings previously disparate analytics and AI development tasks together in one environment with data management, Unified Studio is now generally available.
-
Data management strategies
Vast Data targets secure, speedy agentic AI development
The vendor is furthering its expansion into AI development with features such as vector search and event streaming aimed at enabling users to build and maintain agents.
-
Data management strategies
New Databricks tools tackle lingering GenAI accuracy issues
Features such as centralized model governance and real-time monitoring aim to improve the accuracy of outputs so that enterprises can confidently scale beyond experimentation.
Search Data Management Definitions
- What is data preprocessing? Key steps and techniques
- What is data cleansing (data cleaning, data scrubbing)?
- What is data transformation? Definition, types and benefits
- What is data egress? How it works and how to manage costs
- What is data?
- What is Microsoft Visual FoxPro (VFP)?
- What is corporate performance management (CPM)?
- What is NoSQL (Not Only SQL database)?