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Analytics

Shift Left: Bad Data in Event Streams, Part 2

Alright, I’m back. Time for part 2. In the first part, I covered how we handle bad data in batch processing. In particular, cutting out the bad data, replacing it, and running it again. But this strategy doesn’t work for immutable event streams as they are, well, immutable. You can’t cut out and replace bad data like you would in batch processed data sets.

One Workflow to Rule Them All

Let’s say you’re leading a company that receives thousands of documents daily. These documents come in various formats like Excel, PDFs, CSVs, and more. And they differ in terms of layout. Before you can analyze the data, your team spends hours sorting, cleaning, and preparing these documents. Most of their time is spent preparing the documents for integration into business systems. Then, a colleague shares how intelligent document processing helped him save time and boost productivity.

RAG: An X-Ray for Your Data

Retrieval Augmented Generation (RAG) is an intelligent assistant that helps you find exactly what you’re looking for in a pile of medical records. Like an X-ray shows you hidden details inside the body, RAG helps you quickly extract precise information from complex data. RAG provides instant, accurate answers—often visualized in charts or summaries that require analysts to produce manually. RAG combines two AI capabilities—retrieval systems and generative models.

Protecting Customer Data In A Collaborative, Data-Sharing World | OneTrust

In this episode of "Powered by Snowflake," we hear from Ojas Rege, GM of Privacy and Data Governance at OneTrust, about his company's consent and privacy platform, a platform that helps organizations manage customer data in a way that allows for data sharing and collaboration without compromising data security and customer privacy. The conversation includes a discussion about the role Snowflake technology plays in providing this kind of capability as well as an in-depth demo of the OneTrust Snowflake Native Application.

Unlocking Data Value in the Age of AI and Data Streaming

Imagine getting into your car to head to work on a hot day. Your car already knows and sets the temperature, the ambient lighting, and the music you prefer. Not only that, it optimizes your route, and with Level 3 autonomy, it can even drive you there. But what does the automotive industry have to do on the backend in order to achieve this kind of personalization?