Systems | Development | Analytics | API | Testing

Ingest your data with Cloudera Streaming & DataFlow

Cloudera Data in Motion is designed to enable businesses to respond to critical events in real-time and streamline their data capture, processing, and distribution, while maintaining security and governance. It offers an open architecture for maximum flexibility and control over resources, addressing data in motion challenges.

How to start a data literacy program in 6 steps

In a world where 2.5 quintillion bytes of data are created every day, it’s not surprising that organizations want to harness the power of being data-driven. In our 2022 Data Health Barometer, 99% of companies surveyed recognized that data is crucial for success — but 97% said they face challenges in using data effectively. Perhaps in response to those challenges, 65% of companies reported that they'd started a data literacy program.

Building a Data-Centric Platform for Generative AI and LLMs at Snowflake

Generative AI and large language models (LLMs) are revolutionizing many aspects of both developer and non-coder productivity with automation of repetitive tasks and fast generation of insights from large amounts of data. Snowflake users are already taking advantage of LLMs to build really cool apps with integrations to web-hosted LLM APIs using external functions, and using Streamlit as an interactive front end for LLM-powered apps such as AI plagiarism detection, AI assistant, and MathGPT.

Using Dead Letter Queues with SQL Stream Builder

Cloudera SQL Stream builder gives non-technical users the power of a unified stream processing engine so they can integrate, aggregate, query, and analyze both streaming and batch data sources in a single SQL interface. This allows business users to define events of interest for which they need to continuously monitor and respond quickly. A dead letter queue (DLQ) can be used if there are deserialization errors when events are consumed from a Kafka topic.