Resource Categories: EBook

How Comcast, Dropbox, Cedar Health and others detect threats and protect their organizations

Every year, the cybersecurity stakes get higher. As organizations face more sophisticated, persistent and unpredictable threats, forward-thinking security teams are creating well-rounded cybersecurity programs built on a data cloud platform to fortify their systems.

That’s why organizations of all sizes and industries are using Snowflake’s modern security data lake to make their cybersecurity goals a reality — whether it’s Centers for Medicare & Medicaid Services achieving a more cost-effective solution, Navan maintaining compliance or Figma automating workflows to solve problems more effectively.

Download “Secrets of Cybersecurity Success” to discover how Snowflake customers are achieving amazing outcomes, including how:

• Cedar Health expanded detections eightfold and accelerated query time by 50%
• Comcast increased endpoint detection and response coverage to 95% in just three days for one of its business units
• Dropbox scaled threat detection and response while reducing costs

As long-time early adopters of advanced technology, advertising, media and entertainment companies are rapidly adopting generative AI. This groundbreaking technology can help companies across the industry meet escalating consumer expectations and deliver new, innovative content. But taking advantage of gen AI’s many benefits requires companies to think differently about their data and their data strategy.

Read this ebook to learn:

• The top gen AI use cases for advertising, media and entertainment companies
• How gen AI powers conversations with data
• The challenges facing gen AI adoption in the industry
• Why gen AI requires a robust data strategy

Not too long ago, the term “generative artificial intelligence” (gen AI) was known only to data scientists and machine learning specialists. Now it’s a topic of cocktail party conversations, comedy monologues and congressional hearings.

Today there is a frenetic new frontier. Companies from every industry are scrambling to develop their own gen AI products and make sure they have a data strategy in place.

But enterprises are still grappling with how to tap into the enormous potential of this technology while avoiding the pitfalls. To understand how gen AI can improve productivity and drive business decisions — while skirting the biggest potholes of possible reputational danger — it helps to understand how the technology works and how we got here.

Download The Essential Guide to Generative AI to learn:

• The history of generative AI and how its “iPhone moment” came to be.
• What enterprises need to consider before developing their gen AI strategy.
• How major companies like Deloitte and Snowflake are helping companies navigate this new revolution.

Top analytical streaming reference architectures and use cases across 7 industries 

Across various industries, streaming data and analytics play a crucial role in making better-informed decisions, leading to better outcomes, faster. But for data to be valuable to the business, it needs to be ingested from diverse sources with low latency, which can be a challenge that requires organizations to strike a balance between latency and cost.  

Snowflake engaged with customers across seven diverse sectors to learn more about how they’re addressing these challenges and achieving streaming success. 

Download “The Modern Data Streaming Pipeline” to discover:

• Top analytical data streaming use cases across seven industries — and why they’re beneficial 
• Recommended streaming reference architectures that optimize performance and efficiency for these high-demand use cases 
• Key partner solutions designed to help data flow quickly, smoothly and reliably in a variety of environments and architectures

In the generative AI era, having a comprehensive data strategy is more critical than ever

In 2023, generative AI (gen AI) stepped into the tech and cultural spotlight. Though the large language models (LLMs) that serve as the foundation for gen AI tools have been in development for years, chatbots, like OpenAI’s ChatGPT, emerged seemingly overnight.

Along with this milestone came the increasing recognition that data is the fuel that makes gen AI work—and that comprehensive data governance and efficient data management can determine the success or failure of an enterprise AI project.

2024 promises to deliver even broader adoption of such tools alongside more substantial investment, as innovations continue to emerge at breakneck speed, and the way data scientists and data analysts work continues to change.

In this ebook, you will learn about five emerging trends that organizations can use to inform their data strategies and accelerate their AI efforts. Specifically how:

1. Organizations are prioritizing getting their data house in order
2. Vector and feature stores will begin to live side by side to manage AI data
3. General-purpose chatbots will be supplanted by task-tuned counterparts
4. A new breed of AI apps will emerge from LLMs
5. Open source will continue to be a catalyst for innovation

Discover the top three takeaways from the world’s most influential connectivity event of the year, Mobile World Congress (MWC) Barcelona. In case you couldn’t make it or you missed some of the activities, we have you covered with a look at our top three takeaways:

• Telecoms are getting serious about gen AI
• The telecom data strategy is evolving
• Data collaboration: The sustainable competitive advantage