Data API and GraphQL leader Hasura announced significant innovations that enable unified access to distributed data, governed by a central semantic and authorization framework. This solves one of the hardest problems facing businesses building AI features and products: connecting their LLM models to enterprise data, composed from multiple domains, while complying with governance and security policies.
The insideAI News IMPACT 50 List for Q3 2024
The team here at insideAI News is deeply entrenched in keeping the pulse of the big data ecosystem of companies from around the globe. We’re in close contact with the movers and shakers making waves in the technology areas of big data, data science, machine learning, AI and deep learning. Our in-box is filled each day with new announcements, commentaries, and insights about what’s driving the success of our industry so we’re in a unique position to publish our quarterly IMPACT 50 List.
From ER Diagrams to AI-Driven Solutions
In this contributed article, Ovais Naseem from Astera, takes a look at how the journey of data modeling tools from basic ER diagrams to sophisticated AI-driven solutions showcases the continuous evolution of technology to meet the growing demands of data management. Understanding how data modeling tools have changed over time gives us important insights into why organizing and analyzing data well is so important.
Matillion Democratizes GenAI with No-Code Cortex Components on Snowflake AI Data Cloud
Modern data pipeline platform provider Matillion today announced at Snowflake Data Cloud Summit 2024 that it is bringing no-code Generative AI (GenAI) to Snowflake users with new GenAI capabilities and integrations with Snowflake Cortex AI, Snowflake ML Functions, and support for Snowpark Container Services.
Heard on the Street – 6/3/2024
Welcome to insideAI News’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.
Unleashing the Power of Graph and Vector Databases in the Age of Generative AI
In this contributed article, Dave Voutila, solutions engineer at Redpanda, does a dive deep into the world of graph and vector databases, explores how these technologies are converging in the age of generative AI and provides real-time insights on how organizations can effectively leverage each approach to drive their businesses.
Heard on the Street – 5/9/2024
Welcome to insideAI News’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.
Data Libraries – the Secret Sauce to Regulatory Environments
In this contributed article, Ryan Lougheed, Director, Platform Management at Onspring, discusses how data silos wreak havoc not only on the decision-making process, but also on the ability to enact regulatory compliance. The threat of data duplications and inability to scale are some of the main issues with data silos. And suspect data leads to regulatory compliance issues, like unknowingly not following GDRP regulations, which can lead to fines and other legal complications. Building a comprehensive data library can reap several benefits.
AI Fuels Nearly 30% Increase in IT Modernization Spend, Yet Businesses Are Unprepared for Growing Data Demands, Couchbase Survey Reveals
Couchbase, Inc. (NASDAQ: BASE), the cloud database platform company, released the findings from its seventh annual survey of global IT leaders. The study of 500 senior IT decision makers found that investment in IT modernization is set to increase by 27% in 2024, as enterprises look to take advantage of new technologies, such as AI and edge computing, while meeting ever-increasing productivity demands.
Avoid these 8 Data-related Mistakes on Data Projects
This article is excerpted from the book, “Winning with Data Science: A Handbook for Business Leaders,” by Howard Friedman and Akshay Swaminathan with permission from the publisher, Columbia Business School Publishing. The article covers how to avoid 8 data-related mistakes on data projects