The Great Convergence: How Martech and Adtech Are Uniting Around First-Party Data on Snowflake

A revolution is underway as martech and adtech continue to converge around first-party data — and the revolution is happening on Snowflake. This seismic shift isn't a mere trend; it’s a game-changing transformation that will continue to shape the way that marketers and advertisers connect with consumers amid increasing privacy regulations, new identity frameworks and rising customer expectations.

The AI Tipping Point: What Sports Organizations Need to Know for 2025

Sports organizations have made major strides in recent years. Teams across the industry are transforming into data-driven organizations on the fan engagement, monetization and sports operations sides of the business. This trend is perfectly timed with the AI hype cycle. AI is proving that it’s here to stay. While 2023 brought panic and wonder, and 2024 saw widespread experimentation, 2025 will be the year sports teams get serious about AI's applications.

Why Short-Lived Connections Are Killing Your Performance! | Kafka Developer Mistakes

Constantly starting and stopping Apache Kafka producers and consumers? That’s a recipe for high resource usage and inefficiency. Short-lived connections are heavy on resources, and can slow down your whole cluster. Keep them running to boost performance, cut latency, and get the most out of your Kafka setup.

Cloudera announces 'Interoperability Ecosystem' with founding members AWS and Snowflake

Today enterprises can leverage the combination of Cloudera and Snowflake—two best-of-breed tools for ingestion, processing and consumption of data—for a single source of truth across all data, analytics, and AI workloads. But now AWS customers will gain more flexibility, data utility, and complexity, supporting the modern data architecture.

Fueling the Future of GenAI with NiFi: Cloudera DataFlow 2.9 Delivers Enhanced Efficiency and Adaptability

For more than a decade, Cloudera has been an ardent supporter and committee member of Apache NiFi, long recognizing its power and versatility for data ingestion, transformation, and delivery. Our customers rely on NiFi as well as the associated sub-projects (Apache MiNiFi and Registry) to connect to structured, unstructured, and multi-modal data from a variety of data sources – from edge devices to SaaS tools to server logs and change data capture streams.

Cloudera AI Inference Service Enables Easy Integration and Deployment of GenAI Into Your Production Environments

Welcome to the first installment of a series of posts discussing the recently announced Cloudera AI Inference service. Today, Artificial Intelligence (AI) and Machine Learning (ML) are more crucial than ever for organizations to turn data into a competitive advantage. To unlock the full potential of AI, however, businesses need to deploy models and AI applications at scale, in real-time, and with low latency and high throughput. This is where the Cloudera AI Inference service comes in.

EP 2: Beyond Just Data in Today's Market

Airports are an interconnected system where one unforeseen event can tip the scale into chaos. For a smaller airport in Canada, data has grown to be its North Star in an industry full of surprises. But in order for data to bring true value to operations–and ultimately customer experience–those data insights must be grounded in trust. Ryan Garnett, Senior Manager Business Solutions of Halifax International Airport Authority, joins The AI Forecast to share how the airport revamped its approach to data, creating a predictions engine that drives operational efficiency and improved customer experience.

Securely Query Confluent Cloud from Amazon Redshift with mTLS

Querying databases comes with costs—wall clock time, CPU usage, memory consumption, and potentially actual dollars. As your application scales, optimizing these costs becomes crucial. Materialized views offer a powerful solution by creating a pre-computed, optimized data representation. Imagine a retail scenario with separate customer and product tables. Typically, retrieving product details for a customer's purchase requires cross-referencing both tables.