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Top 5 Data + AI Predictions for Financial Services in 2024

Snowflake

The foundation for success is a data platform that allows flexible, cost-effective ways to access gen AI — whether organizations want to use off-the-shelf commercial and open-source large language models (LLMs), or fine-tune their own LLMs for more complex applications. Rinesh Patel, Snowflake’s Global Head of Financial Services 2.

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Complying with Quebec’s Data Privacy Laws Is Easier with the Data Cloud

Snowflake

Canada, in addition to being one of those 71% of countries with data protection and privacy legislation, stands out as an early adopter of privacy legislation. Quebec takes that a step further with its Bill 64, now referred to as Law 25, which modernizes data protection and privacy legislation for Canada’s second most populated province.

Cloud 76
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How Much Data Do We Need? Balancing Machine Learning with Security Considerations

Towards Data Science

Taking a hard look at data privacy puts our habits and choices in a different context, however. Data scientists’ instincts and desires often work in tension with the needs of data privacy and security. Anyone who’s fought to get access to a database or data warehouse in order to build a model can relate.

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Certifying Ripple's System and Organization Controls: SOC 2

Ripple Engineering

How do you make a computer system maximally secure and reliable? Disconnect it from all networks and never change any of the software or data. How do you make a computer system maximally useful? Connect it to networks and make frequent changes to the software and data! What is SOC 2? How did Ripple pass SOC 2?

Systems 52
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Cybersecurity in Banking: Importance, Threats, Challenges

Knowledge Hut

The stakes are high in the banking and financial industry since substantial financial sums are at risk and the potential for significant economic upheaval if banks and other financial systems are compromised. Take a look at the best Security certifications. The attackers entered the system using fake RBI IDs.

Banking 98
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Easy and Secure LLM Inference and Retrieval Augmented Generation (RAG) Using Snowflake Cortex

Snowflake

While every organization should keep both options on the table, to quickly deliver value, the key is to identify and deploy use cases that can deliver value using prompt engineering and retrieval augmented generation (RAG), as these can be fast and cost-effective approaches to get value from enterprise data with LLMs. What is RAG?

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The Symbiotic Relationship Between AI and Data Engineering

Ascend.io

And crucially, what does the future hold for data engineering in an AI-driven world? While data engineering and Artificial Intelligence (AI) may seem like distinct fields at first glance, their symbiosis is undeniable. The foundation of any AI system is high-quality data.