SNOWDAY + DISCOVER

A Discover first! Join Natalie Mead and special guest Christian Kleinerman (SVP Product, Snowflake) as they explore the latest in the Data Cloud platform. Data, Apps and AI Collaboration have all seen significant innovation and we take a walk through some of the highlights. This is a chance to meet Christian live, and as owner of the team that creates Snowflake’s products don’t miss this chance to hear the capabilities and vision from the source!

The Data Cloud platform has an incredible amount of capability and many sessions today feature these. If you are brand new to Snowflake and wondering how to get started, this session is for you. In a live walkthrough will give you an understanding of navigating the Snowflake interface, creating a warehouse, ingesting data, simple scaling and more. Zero to Snowflake Hero in one hour!

Data and analytics practitioners struggle with siloed and diverse data, performance degradation over time, exacerbated by operating and maintaining complex pipelines and architecture. In this session we will walk you through the Data Engineering workload on Snowflake to improve the reliability of your pipelines, understand how you can speed data transformation using streams and tasks, get granular control over data accessibility and security challenges, and much more.

Time to dig into some of the latest capabilities on Snowflake! By completing this session, you will be understand deploying different implementations of integrating Large Language Models (LLMs) such as OpenAI using External Access and External Functions in Snowflake. In this implementation, we will use External Access to securely connect to the OpenAI API from Snowpark, the set of libraries and runtimes in Snowflake that run non-SQL code, including Python, Java and Scala. External Access provides flexibility to reach public internet endpoints from the Snowpark sandbox without any additional infrastructure setup.

One of the most critical activities that a Data/Business Analyst has to perform is to produce recommendations to their business stakeholders based upon the insights they have gleaned from their data. In practice, the are a number of impediments that prevent creating the best model possible. Snowflake developed Machine Learning Powered Functions (MLPFs) which are a set of SQL functions that implement machine learning models on the user’s behalf. In this session we look at three MLPF’s so assist in Forecasting, Anomaly Detection and also Contribution Explorer.

In the era of data-driven business, the design of your data architecture is paramount. In this session we will explore the transition from the Object Per Tenant (OPT) design pattern to the Multi Tenant Table (MTT) design pattern within the context of the data platform built on Snowflake for a SaaS product. The OPT approach, while initially was useful, posed challenges as businesses scale, leading to increased complexity and costs. In contrast, MTT offers a streamlined, cost-effective, and scalable solution for multi-tenant data management. In this session, we will explore the benefits of multi-tenancy, such as scalability, and talk about how it helped manage costs, making maintenance easier, improved query performance, and data isolation.

In the modern data-driven landscape, organizations face a growing challenge to manage, analyze, and share data efficiently. Mindtickle, like many others, recognized the limitations of a centralized data platform and sought a more scalable and decentralized approach towards managing and processing data.
Have you ever wondered what it takes to revamp an entire organization’s data infrastructure? Join us as we take you through this journey of transformation.
In this session, we will take a look at the unique data-processing challenges that we face at Mindtickle with our current architecture and discuss how we plan to overcome them by creating a decentralised, domain-driven Data Mesh Architecture using Snowflake. Let’s deep dive on how the future of data management is being reshaped at Mindtickle!

This session is all about flexibility, first we look at Iceberg tables and the latest enhancements powering open standards in the data cloud.
Next, we look at the latest platform innovation Snowpack Container services – its enabling developers to new ways to work and build with data.

In this session you will get up and running with developing your first Snowflake Native Application! Snowflake Native Applications provide developers a way to package applications for consumption by other Snowflake users. The Snowflake Marketplace is a central place for Snowflake users to discover and install Snowflake Native Applications. In this example we will be building a Snowflake Native Application used for inventory and supply chain management to introduce you to the latest capability of the Data Cloud.

Join this session to understand the history of Large Language Models and gain a technical understanding of what embeddings are, how fine-tuning works, and more. By the end you will have a practical understanding of core technical concepts as well as take part in demos that will help you see Generative AI technologies you can use in Snowflake.