Why Data Integration is Key for M&A Success
Merging data systems post-acquisition? Joe Pardi, Senior Director of Global Data Engineering at Covetrus, explains how real-time data streaming architecture makes 1+1=3.&A.
Cloud Data Integration with MongoHQ and Integrate.io
Integrate.io loves MongoDB - MongoDB is great for storing and querying data, while Integrate.io is great for transforming the data and getting it ready for analysis. That’s why we integrate with MongoHQ, one of the leading MongoDB-as-a-Service solutions. Since MongoHQ is built on the cloud, it allows for fast and scalable work with MongoDB.
The 6 Building Blocks of ETL Architecture
Business intelligence (BI) and analytics projects depend on efficient and effective data integration, which in turn depends on processes such as ETL (extract, transform, load). Rather than performing data analysis from multiple sources in place, ETL collects information within a centralized data warehouse for faster and easier processing and querying.
Ultimate Guide to ESG Reporting
Environmental, social, and governance (ESG) reporting is no longer just a rising trend—it’s a fundamental part of how companies demonstrate accountability, resilience, and long-term value. Investors, stakeholders, and regulators have made it clear: ESG performance is now inseparable from financial performance.
Fivetran Connector SDK: Unlocking every data source
Start replicating from any and every source system with the Connector SDK.
Tech, talent or trust: What's holding back AI adoption the most?
Tech, talent or trust: What’s holding back organizations from AI adoption the most? Along with exploring that question, in this short video, Practice Director for Data Management, Analytics & AI at Informa TechTarget’s Enterprise Strategy Group, Michael Leone, discusses AI adoption with Hitachi Vantara leaders, including: The video also explores exciting AI use cases, the data issues hindering AI and tips for measuring the success of your AI initiatives.
AI initiatives and obstacles: How to stay competitive
By failing to adopt AI and modern data strategies, companies risk falling behind. According to Informa TechTarget’s Enterprise Strategy Group (ESG), 86% of enterprise-class organizations are planning to invest at least $1 million in data and AI initiatives. To help your business keep up, in this video ESG’s Practice Director for Data Management, Analytics & AI, Michael Leone, explores how to build a trusted data foundation, the biggest data challenges faced by companies, and much more.
Introducing the Agentic Semantic Layer: A New Standard for Data Foundations
For data analysts and engineers, the journey from raw data to actionable business insights for business users is never as simple as it sounds. The semantic layer is a critical component in this process, serving as the bridge between complex data sources and the business logic required for informed decision-making. However, not all semantic layers are created equal, and the evolving landscape of AI-powered analytics demands a new approach.
What's new in Cloudera Data Flow 2.10: Easily Build and Deploy NiFi 2 Flows
Learn about all the new NiFi 2 features in Cloudera Data Flow 2.10, including NiFi 2 General Availability across Flow Drafts, Deployments and Test Sessions and our brand new NiFi 1 to NiFi 2 Migration Experience (Technical Preview)!