Resource Categories: EBook

In this e-book, we’ll highlight new ways Snowflake and Microsoft Azure are addressing the most challenging supply chain issues across three industries: manufacturing, consumer goods, and healthcare and life sciences. You’ll see how Snowflake on Microsoft Azure paves the way to a unified data strategy that leverages AI to solve key supply chain challenges. For each industry, we’ll share tools and strategies that:

• Drive visibility upstream and downstream by eliminating data silos.

• Leverage AI to improve planning accuracy.

• Improve product quality, service, and market growth with connected product data.

Build Apps Quickly and Cost-effectively with Snowpark

Today’s organizations are building modern data-intensive and AI-enriched applications to gain a competitive advantage. But there are major compute challenges involved in processing large volumes of complex and dynamic data from different sources, analyzing it with AI and ML models, and presenting insights so that customers or employees can make better decisions and perform smarter actions.

This book reveals how Snowpark leverages the Snowflake Data Cloud to help developers overcome these challenges to build, deploy, and monetize applications quickly, easily, and cost effectively.

Highlights include:

• What modern applications require
• Using the Snowflake Data Cloud to develop apps
• Why use Snowflake to build apps
• What you can build with Snowpark
• The benefits of building with Snowpark
• How to get started with Snowpark

Manufacturers rely on systems that can accurately capture their processes, products and dependencies, efficiently handle transactions, scale well and provide cost-effective analytical capabilities. By moving existing on-premises transitional system to the cloud, manufacturers can save on costs, enable better visibility on their spend and provide more flexibility and capacity to their analytics.

Read this ebook to learn how Snowflake:

• Helps unlock advanced analytics with ERP data
• Partner solutions streamline data ingestion from ERP systems to Snowflake
• Improves manufacturing and business processes by eliminating data silos

When people ask me about my secret to success, they may be surprised that the explanation is so simple. Anyone can do it. Most organizations are underperforming, whether their people realize it or not. The secret to amping it up is finding the slack that naturally exists and eliminating it by setting bigger goals, a faster pace, and a higher intensity. It’s about pushing the organization to perform at a much higher level and reaping the results of your amplified efforts.  

This field book’s activities will help you create a concrete path to executing the ideas and guidance in Amp It Up. If you haven’t amped it up before, you may need to prepare yourself for the magnitude of change you are pursuing. To this end, some of the exercises will help you shift your mindset, so you can be ready to make a major impact on your organization or team.

embrace generative ai and llms with the snowflake data cloud

Generative AI (gen AI) and large language models (LLMs) are revolutionizing personal and professional lives. From supercharged digital assistants that manage email to seemingly omniscient chatbots that can communicate with enterprise data across industries, languages, and specialties, these technologies are driving a new era of convenience, productivity, and connectivity.

This book provides an introductory overview to LLMs and gen AI applications, along with techniques for training, tuning, and deploying machine learning (ML) models.

Highlights include:

• Five steps to get started with generative AI
• Understand important LLM concepts
• Develop applications with user-friendly interfaces
• Select an appropriate LLM
• Recognize the importance of data governance
• See how to orchestrate AI agents

Using AI to achieve real and sustainable goals starts with a solid data strategy that can include, but doesn’t necessarily start with, AI technologies. What many organizations are missing amid the excitement about generative AI is how they are—and could be—leveraging available data, how they could “productionalize” the data, and how they could protect, secure, and govern it.

To have all this worked out, you need a data strategy that opens opportunities and accelerates time-to-value. That’s what we’ll be talking about in this ebook: the too-often-overlooked fact that AI strategy must be an outgrowth of data strategy, not the other way around. Snowflake operating on Microsoft Azure paves the way to do that.

Organizations are turning to data as the catalyst for transformative business outcomes as they search for a competitive edge.

The success stories are clear: Harnessing high volumes of data from diverse sources helps organizations — from media to financial services to telecommunications and more — innovate, cut costs and gain unparalleled insights through analytics.

Download your complimentary copy of “3 Challenges of Data Streaming Pipelines (and How to Overcome Them)” to learn:

• How capturing and processing data can help organizations gain visibility into customer sentiment, website behavior, operational issues and more.
• How to navigate the complexities of streaming systems by adopting a unified approach that seamlessly integrates streaming and batch processing pipelines.
• How practical strategies can help organizations efficiently handle streaming data by leveraging familiar tools, like SQL or Python, and strike the perfect balance between speed and affordability.

To compete successfully and respond to business challenges with data insights, organizations need to advance beyond the traditional division between transactional and analytical data. Tighter integration between online transaction processing (OLTP) systems and the data systems organizations have set up to support business intelligence (BI) reporting, analytics, and data science will enable organizations to improve customer experiences, move faster to adjust supply chains, and gain near-real-time insights into key issues such as fraudulent behavior. Getting to the next level with initiatives such as real-time customer personalization and cross-channel marketing depends on a seamless data flow between transactional and analytics systems.

This TDWI Checklist focuses on how organizations can gain advantage from unifying data on modern cloud data platforms.

The details you need to understand Snowflake costs

At Snowflake, we keep things simple with a consumption-based pricing model that allows customers to only pay for what they use. This approach gives customers flexibility and control to easily scale up and down to meet demand — all while gaining clear visibility into their usage and spend.

Download this guide to understand a range of Snowflake pricing elements, including:

• Optimized data storage and transfer
• Elastic compute
• Snowflake credits and virtual warehouse sizes
• Snowflake editions and purchasing options
• Pricing examples with sample bills