AI Assistant With Cloudera Data Visualization
Learn how Cloudera Data Visualization uses large language models and retrieval augmented generation to enable faster exploration and analysis of data using natural language.
Analytics
Hitachi Vantara Expands Hybrid Cloud Storage Platform with Object Storage, All-QLC Flash and Advancing Cloud Integration
Virtual Storage Platform One integrates object storage with block and file, expands dense capacity with QLC flash, and extends software-defined cloud integration to provide reduced cost, improved management of unstructured data, and unmatched energy efficiency.
Data Platform Economics: Measuring and Improving Cost-per-App in Databricks
80% of data management experts struggle to forecast data-related cloud costs with precision (Forrester). The root causes? A critical shortage of granular visibility needed for accurate cost allocation, fragmented data siloed away from those who need it most, and a notable absence of AI-driven tools and automated processes capable of predicting future expenditures. Learn how to get granular costs with ease using Unravel Data. Join this Weekly Walkthrough series, FinOps Metrics that Matter, to understand the critical benefits of drilling down into your costs at the most detailed levels.
Unmatched Collaboration for Data and AI Products: What's New from Snowflake
Getting different teams, business units and even companies to work together toward a common goal not only maximizes efficiency, but drives innovation. Effective collaboration on data and AI has never been more closely tied to success. At Snowflake, we’re removing the barriers that prevent productive cooperation while building the connections to make working together easier than ever.
SAP S/4HANA Cloud Public Edition: Top Migration Challenges and Solutions
Your organization has decided to make the leap to SAP S/4HANA Cloud Public Edition, a strategic choice that offers improved performance, advanced analytics, and more efficient support for your business operations. While this cloud ERP offers streamlined processes and improved scalability, it also limits the level of customization that finance teams have come to rely on for tailored, actionable insights. The result post-migration?
Navigate the New Era of Data Management in Mid-Sized Enterprises
In the modern digital landscape, data grows at an astonishing rate. Mid-sized enterprises struggle to manage its volume and velocity, let alone its value. Today’s complex data environments must span hybrid and multicloud setups. And as transformative technologies like generative AI (GenAI) matter more to business operations, they must manage skyrocketing demand for sophisticated, flexible and scalable data solutions.
Build Enterprise-Grade AI Faster with New Multimodal Support, Enhanced Observability and More
At Snowflake BUILD, we are introducing powerful new features designed to accelerate building and deploying generative AI applications on enterprise data, while helping you ensure trust and safety. These new tools streamline workflows, deliver insights at scale, and get AI apps into production quickly. Customers such as Skai have used these capabilities to bring their generative AI solution into production in just two days instead of months.
Trends and Takeaways from Banking and Payments' Biggest Event of the Year
This fall, thousands of leaders in the financial services industry gathered at the annual Money 20/20 conference to talk trends in payments, compliance, fraud reduction, treasury and transactions and more. Conversations centered on the theme of “Human x Machine,” and while AI was a focus, there were plenty of other insights around real-time data analytics, security considerations and customer strategies that are guiding the future of money.
Snowflake Simplifies Data Architecture, Data Governance and Security to Accelerate Value Across All Workloads
It’s easy these days for an organization’s data infrastructure to begin looking like a maze, with an accumulation of point solutions here and there. While some businesses find ways to stitch together many tools with complex pipelines, wouldn’t it be better if you could remove some of the steps? What if you could streamline your efforts while still building an architecture that best fits your business and technology needs?
MuleSoft vs ETL: Understanding the Key Differences
In the digital era, data integration is not just a luxury—it’s a necessity for efficient business operations and informed decision-making. With data stored across different platforms, applications, and cloud environments, businesses need tools that can help them unify these disparate data sources. MuleSoft and ETL are two commonly discussed solutions in the data integration space, but they serve very different purposes.