Snowflake

San Mateo, CA, USA
2012
  |  By Jakub Puchalski
The journey toward achieving a robust data platform that secures all your data in one place can seem like a daunting one. But at Snowflake, we’re committed to making the first step the easiest — with seamless, cost-effective data ingestion to help bring your workloads into the AI Data Cloud with ease. Snowflake is launching native integrations with some of the most popular databases, including PostgreSQL and MySQL.
  |  By Rudi Leibbrandt
Last year at Summit, we announced the public launch of the Snowflake Performance Index (SPI), an aggregate index for measuring real-world improvements in Snowflake performance experienced by customers over time.
  |  By Nikolai Scholz
It is estimated that between 80% and 90% of the world’s data is unstructured1, with text files and documents making up a significant portion. Every day, countless text-based documents, like contracts and insurance claims, are stored for safekeeping. Despite containing a wealth of insights, this vast trove of information often remains untapped, as the process of extracting relevant data from these documents is challenging, tedious and time-consuming.
  |  By Sandeep Gupta
Bringing machine learning (ML) models into production is often hindered by fragmented MLOps processes that are difficult to scale with the underlying data. Many enterprises stitch together a complex mix of various MLOps tools to build an end-to-end ML pipeline. The friction of having to set up and manage separate environments for features and models creates operational complexity that can be costly to maintain and difficult to use.
  |  By Anurag Gupta
Today’s data-driven world requires an agile approach. Modern data teams are constantly under pressure to deliver innovative solutions faster than ever before. Fragmented tooling across data engineering, application development and AI/ML development creates a significant bottleneck, hindering the speed of value delivery required to stay competitive. Disparate tools create a complex landscape for developers and data teams, hindering efficient pipeline development and deployment.
  |  By Ashwin Kamath
Discovering and surfacing telemetry traditionally can be a tedious and challenging process, especially when it comes to pinpointing specific issues for debugging. However, as applications and pipelines grow in complexity, understanding what’s happening beneath the surface becomes increasingly crucial. A lack of visibility hinders the development and maintenance of high-quality applications and pipelines, ultimately impacting customer experience.
  |  By Anissa Alusi
We’re pleased to announce the launch of Snowflake Notebooks in public preview, a highly anticipated addition to the Snowflake platform tailored specifically to integrate the best of Snowflake within a familiar notebook interface. Snowflake Notebooks aim to provide a convenient, easy-to-use interactive environment that seamlessly blends Python, SQL and Markdown, as well as integrations with key Snowflake offerings, like Snowpark ML, Streamlit, Cortex and Iceberg tables.
  |  By Snowflake
Snowflake announced the global winners of the sixth annual Data Drivers Awards, the premier data awards that honor Snowflake customers who are leading their organizations and transforming their industries with the AI Data Cloud. This year’s winners of the Data Drivers Awards include data leaders from across global organizations, including Caterpillar, Bentley, Mitsubishi Corporation, Zoom and more.
  |  By Muzz Imam
Apps are the way to democratize AI: to make it accessible to everyone and streamline customers’ experiences with faster time to insights. According to a recent IDC survey, AI applications is currently the largest category of AI software, accounting for roughly one-half of the market’s overall revenue in 2023.
  |  By Jeff Hollan
In today’s world, innovation doesn’t happen in a vacuum; collaboration can help technological breakthroughs happen faster. The rise of AI, for example, will depend on the collaboration between data and development. We’re increasingly seeing software engineering workloads that are deeply intertwined with a strong data foundation.
  |  By Snowflake
In this "Data Cloud Podcast" episode, David Cohen, Chief Data Officer at Weight Watchers, shares his thoughts on why having silos of information hobbles an organization and how Snowflake continues to help Weight Watchers do its job well. He also walks through the important distinction between what it means to be data-informed versus data-driven.
  |  By Snowflake
Watch the full Opening Keynote presentation from Snowflake Summit 2024. The presentation features comments by Snowflake CEO Sridhar Ramaswamy, who discusses the impact AI has had across every organization, followed by a CEO fireside conversation between Sridhar and NVIDIA Founder and CEO Jensen Huang, who discusses what the future holds in this new AI era.
  |  By Snowflake
The excitement of Data Cloud Summit 2024 continued into Day Three as attendees got to witness some fantastic demos showcasing new Snowflake products and capabilities, hear about successful AI and LLM implementations and enjoy some fun and games on the show floor.
  |  By Snowflake
Enjoy these highlights from the Data Cloud Summit 2024 opening keynote session, which features a conversation between Snowflake CEO Sridhar Ramaswamy and NVIDIA Founder and CEO Jensen Huang that explores the impact AI is having on the digital transformation of organizations in every industry.
  |  By Snowflake
There may be snow in San Francisco at #SnowflakeSummit, but we're not cooling off yet! Day 2 brought the heat with AI demos, audience participation, and best of all...DARK MODE!
  |  By Snowflake
In this "Data Cloud Podcast" episode, host Steve Hamm sits down with Philip Zelichenko, VP of Data and Analytics at ZoomInfo, to discuss the benefits the ZoomInfo business go-to-market platform provides to companies. During the conversation, he explains ZoomInfo's role as a data broker that maintains a database with profile information on 100 million companies, iinformation that clients can use to fuel sales and marketing growth.
  |  By Snowflake
To kick off the fifth season of "The Data Cloud Podcast," host Steve Hamm is joined by Snowflake CEO Sridhar Ramaswamy. In this episode, Sridhar explains why organizations need to have a data strategy in order to implement a successful AI strategy. He also discusses the steps involved in creating a foundation model from scratch and why he believes AI is the glue that will bind enterprise software together.
  |  By Snowflake
In December 2023, Snowflake announced its acquisition of data clean room technology provider Samooha. Samooha’s intuitive UI and focus on reducing the complexity of sharing data led to it being named one of the most innovative data science companies of 2024 by Fast Company. Now, Samooha’s offering is integrated into Snowflake and launched as Snowflake Data Clean Rooms, a Snowflake Native App on Snowflake Marketplace.
  |  By Snowflake
The Snowflake Marketing Data Cloud empowers organizations to simplify complex MarTech architectures, deliver superior customer experiences, and maximize marketing and advertising ROI.
  |  By Snowflake
Watch the full video to learn more about the Redica data analytics platform.
  |  By Snowflake
There's never been a better time to be an entrepreneur looking for investment funding. Global venture capital activity grew mightily in the first half of 2021, and the trend appears to be continuing as we head into 2022. However, that doesn't mean building a new company is any easier. The same inherent resource and growth challenges exist, and venture capitalists still want to see value creation and strong indicators for future success before they invest.
  |  By Snowflake
Data scientists require massive amounts of data to build and train machine learning models. In the age of AI, fast and accurate access to data has become an important competitive differentiator, yet data management is commonly recognized as the most time-consuming aspect of the process. This white paper will help you identify the data requirements driving today's data science and ML initiatives and explain how you can satisfy those requirements with a cloud data platform that supports industry-leading tools.
  |  By Snowflake
Many organizations struggle to share data internally across departments and externally with partners, vendors, suppliers, and customers. They use manual methods such as emailing spreadsheets or executing batch processes that require extracting, copying, moving, and reloading data. These methods are notorious for their lack of stability and security, and most importantly, for the fact that by the time data is ready for consumption, it has often become stale.
  |  By Snowflake
DELIVER ALL YOUR DATA WORKLOADS WITH SNOWFLAKE Gartner predicts that 75% of all databases will be deployed or migrated to a cloud platform by 2022. But how does e a cloud data platform enable a long-term strategy for maximizing all of an organization's data assets? Snowflake's cloud data platform is a highly extensible, multi-region and multi-cloud platform that powers all types of data workloads. Specifically, Snowflake: To learn everything Snowflake offers today's, forward-looking organizations, download our white paper, Snowflake: One Cloud Data Platform for All Your Analytic Needs.
  |  By Snowflake
Most companies that build software have a strong DevOps culture and a mature tool chain in place to enable it. But for developers that need to embed a data platform into their applications to support data workloads, challenges emerge. DevOps for databases is much more complex than DevOps for code because database contain valuable data, while code is stateless. Instantly creating any number of isolated environments Reducing schema change frequency with variant data type
  |  By Snowflake
Companies are moving workloads to the cloud as they seek to improve speed, scale, and agility. Today's data warehouse managers want to boost analytics productivity, increase the ability to scale instantly, and ingest and support a diverse set of data without bottleneck delays. In this white paper, we explain how Snowflake delivers the speed, scale, and agility organizations need for data-driven decision-making.
  |  By Snowflake
Financial institutions are embracing cloud-based data technologies to improve their service and product offerings, streamline operations, and gain deeper customer insights. This ebook features success stories about the many ways financial services companies are leveraging Snowflake Cloud Data Platform to build a 360 degree view of customers, accelerate financial analysis with unlimited scale, and keep sensitive and regulated data secure.
  |  By Snowflake
Read about Snowflake's comprehensive approach to protecting data and access to data.
  |  By Snowflake
As companies have recognized the importance of unifying customer data to obtain business insights, customer data platforms that consolidate and activate known customer information have become ubiquitous. Customer data platforms enable marketers to segment and share customer profiles with marketing systems to personalize the content of email campaigns, digital ads, and other channels. In this ebook, we explore how marketers can launch and operate a customer data platform successfully, with a focus on how to.

Snowflake’s mission is to enable every organization to be data-driven. Our cloud-built data platform makes that possible by delivering instant elasticity, secure data sharing and per-second pricing, across multiple clouds. Snowflake combines the power of data warehousing, the flexibility of big data platforms and the elasticity of the cloud at a fraction of the cost of traditional solutions.

Conventional data platforms and big data solutions struggle to deliver on their fundamental purpose: to enable any user to work with any data, without limits on scale, performance or flexibility. Whether you’re a data analyst, data scientist, data engineer, or any other business or technology professional, you’ll get more from your data with Snowflake.

What Makes Snowflake Unique:

  • A Multi-Cluster Shared Data Architecture Across Any Cloud: Easily scale up and down any amount of computing power for any number of workloads or users and across any combination of clouds, while accessing the same, single copy of your data but only paying for the resources you use thanks to Snowflake’s per-second pricing.
  • Secure Data Sharing and Collaboration: Eliminate the cost and headache of static data sharing methods by easily sharing any amount of live structured and semi-structured data, without having to move data, whether it be across your enterprise, with customers and business partners, or to monetize your data.
  • One, Near-Zero Maintenance Platform Delivered as a Service: Choose any combination of infrastructure providers, enable your workloads where you want, rely on Snowflake to manage the data platform, and deploy across and between different clouds and regions to support business efficiencies and data sovereignty.

A Modern Data Platform Built For Any Cloud.