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Analytics

AWS, Qlik, and SAP Data: Turning the Lifeblood of Business into Value and Action

One of my favorite analogies is that data is the lifeblood of the business. Before you roll your eyes at me (I see it now), hear me out. At your annual physical, when you get your blood work done, think of how much information is uncovered about your overall health from a tiny vial of your blood. From those 10 CCs they extract comes back pages of information regarding your cell counts, glucose, cholesterol, and other information.

Apache Kafka Message Compression

Apache Kafka® supports incredibly high throughput. It’s been known for feats like supporting 20 million orders per hour to get COVID tests out to US citizens during the pandemic. Kafka's approach to partitioning topics helps achieve this level of scalability. Topic partitions are the main "unit of parallelism" in Kafka. What’s a unit of parallelism? It’s like having multiple cashiers in the same store instead of one.

Telecommunications Data Monetization Strategies in 5G and beyond with Cloudera and AWS

The world is awash with data, no more so than in the telecommunications (telco) industry. With some Cloudera customers ingesting multiple petabytes of data every single day— that’s multiple thousands of terabytes!—there is the potential to understand, in great detail, how people, businesses, cities and ecosystems function.

Fine-Tuning a Foundation Model for Multiple Tasks

In this video we discuss the reasons why fine-tuning is needed to create mroe contextual accurate LLMs, and the methods that you can do to accomplish this. We also give a demo of our newest Applied ML Prototype (AMP) which demonstrates how to implement LLM fine-tuning jobs that make use of the QLoRA and Accelerate implementations available in the PEFT open-source library from Huggingface and an example application that swaps the fine-tuned adapters in real time for inference targetting different tasks. Learn more at cloudera.com#ai #ml.