Another year on the books already? When you’re focused on using data to take your business to the next level, time does fly. Inside the Data Cloud saw upwards of 1,050 blog posts this year (that’s busy), and well over a million views (that’s fun).
Here are our most popular blog posts of 2022, along with some from our technical communities as well.
More Snowflake features, more power for users
Every year—even every month!—Snowflake adds new features, guided by the problems our customers want to solve. So it’s no surprise that many of our most popular posts are about new functionality, integrations, and products that help teams get work done and create new business value from data.
Unistore: Snowflake’s New Workload for Transactional and Analytical Data Together in One Platform Tired of moving data from system to system? Join the crowd—and here’s major relief. Unistore breaks down the wall between transactional and analytical data silos. Snowflake’s Carl Perry walks you through Hybrid Tables and how they can transform your architecture, applications, and workflows.
Expanding the Data Cloud with Apache Iceberg
Customers want to use Snowflake innovations to solve three challenges they commonly face with large data sets: control, cost, and interoperability. Snowflake’s support for Apache Iceberg solves these challenges and makes it even easier to use Snowflake as the platform for your architecture of choice. James Malone, Senior Manager, Product Management, has the details.
Introducing the Snowflake Native Application Framework
Now you can build applications with familiar Snowflake functionalities, distribute them on Snowflake Marketplace, and deploy them directly inside a customer’s Snowflake account. Application providers reach thousands of customers across the Data Cloud; customers keep data centralized and simplify their procurement process. A true win-win, as Principal Product Manager Unmesh Jagtap explains.
Snowflake for Python: Machine Learning Models, Feature Engineering
Python, the most popular language for data scientists and many data engineers, is now natively supported in Snowflake via Snowpark for Python. Check out the building blocks used by customers to build secure and scalable data pipelines and machine learning (ML) workflows directly within Snowflake.
Democratizing Data Apps—Snowflake Acquires Streamlit
What if you could build interactive web apps using only Python? Our customers, and Snowflake’s own team, have been using Streamlit’s development framework for years to do just that. With our acquisition of Streamlit, we’re combining Streamlit’s ease of use, flexibility, and open source community with Snowflake’s scalability, scope of data, and governance to power a new class of data apps.
Snowflake Connector for Azure Data Factory (ADF)
With our March 2022 release, Azure Snowflake customers are now able to use ADF as their end-to-end data integration tool with relative ease. This updated post gives the details.
Insights from our Data Heroes Community
Ready to roll up your sleeves and rummage around in settings and code? To help practitioners get even more value, even faster, Snowflake’s Data Heroes community offers an extensive (and growing) knowledge base, as well as a Medium blog by community members.
Getting Started with Snowpark for Python and Streamlit
With Snowpark, data engineers, data scientists, and developers coding in languages other than SQL (such as Scala, Java, and Python) can take advantage of Snowflake’s powerful platform without having to first move data out of Snowflake. This tutorial walks through creating a Python application.
How to Use AWS Glue with Snowflake
AWS Glue lets developers build and manage data preparation and loading processes with generated code that is customizable, reusable, and portable—no infrastructure to buy, set up, or manage. This post, with the companion piece How to Set Up AWS Glue ETL for Snowflake, shows you how to do it.
SQL Scripting: Live in Snowflake
Snowflake Scripting is a SQL extension to facilitate migrations and development of stored procedures. Data Cloud Advocate Felipe Hoffa provided his notes and basic scripts to get you started.
Snowpark Fast and Furious: Streamlining Your Data Pipelines
Snowpark Scala and Java UDFs offer a big step forward to streamline architectures, build scalable and optimized data pipelines, and enforce security and governance across all workflows. This post dives in.
Introducing the 2022 Snowflake Data Superheroes!
Data Superheroes are an elite group of Snowflake experts who are highly active in the community. They share their top-tier knowledge with their peers and offer constructive feedback to the Snowflake product and engineering teams. Are you ready to earn your cape and become a Data Superhero? Fill out the form here.
Deploying Custom Python Packages from GitHub to Snowflake
Snowpark provides a way for developers to code in the language of their choice. Senior Evangelist and Snowflake advocate Dash Desai walks us through deploying pure Python packages from a GitHub repo.
Solving industry challenges
Every industry has its own demands. Here are Snowflake customers making the most of their data to improve operations and innovation. (Many of these fine folks as well as others have shared their stories on our Data Cloud Podcast.)
Optimizing the Manufacturing Process at Valmet, Powered by the Snowflake Data Cloud
Valmet’s Industrial Internet lets its customers connect data from different plant-level and process automation systems—making them more resource-efficient and less dependent on operating location. The company’s Anomaly Detector application has been proven to catch 15-20% of potential web breaks, generating an annual savings of €300,000.
Data Mesh Perspectives: A Q&A with Roche Diagnostics
Data mesh architectures significantly help remove barriers associated with scaling data and making it available to users across an organization. This isn’t just a technology implementation; it also requires a transformative cultural shift. Omar Khawaja, Head of BI and Analytics at Roche Diagnostics, and his team offer lessons from their own journey.
How Under Armour Became a Data-First Company in the Cloud
During the pandemic, being able to share data quickly with a global network of suppliers, distributors, and retailers has been critical to keep the supply chain running smoothly, says Under Armour’s Vice President of Enterprise Data Management, Patrick Duroseau. He expands on where the pursuit of unsiloed data began and what the company plans to do going forward.
Eneco Uses Snowflake’s Modern Tech Stack for Insights
European energy company Eneco’s has an ambitious goal to get to climate neutrality by 2035. A few years ago, the company’s IT landscape was fragmented: multiple data warehouses, scalability limitations—you know the drill. Moving to Snowflake transformed Eneco’s ability to clear the path to help reach its goal.
People, planet, data
Numbers can be cold and hard; human endeavors are what give data meaning. From individual careers, through societal and business trends, to our current planet-level climate challenges, these posts look at how data—particularly data sharing—can improve the human condition.
Why Snowflake Was My Next Strategic Move After Google
Before joining Snowflake, Distinguished Engineer Tal Shaked earned the Grandmaster title in chess. Then he worked on incorporating ML into Google Search, YouTube, and more. He says Snowflake is the next step in “a journey to help make machine learning and AI more accessible to everyone.”
To celebrate International Women’s Day, three Snowflake team members discuss women in technology, career paths, workplace culture, and more: Amanda Hergott, Senior Solutions Architect; Shweta Gummidipudi, VP of Enterprise Applications and Data; and Allison Lee, Senior Director of Engineering and Founding Engineer, SQL.
You Can’t Go Solo Without Collaboration
Alex Honnold’s “free solo” climb to the summit of El Capitan took four hours, but the preparation lasted years and was anything but “solo.” Honnold shared lessons from his experience, and how they apply to working with data, onstage with Principal Data Strategist Jennifer Belissent at our Snowflake Summit event.
Overcoming Territorialism to Increase Data Sharing
Conflicts over data ownership and data sharing can, and often do, arise in any corner of the enterprise. Snowflake’s Belissent and Rich Peters of Tongere Partners offer plenty of practical strategies for getting past it.
How to Find, Hire, and Retain Data Scientists
It’s one of the most in-demand professions worldwide, so landing and keeping your data science team members is tough. We interviewed five data scientists and managers here at Snowflake for their advice and best practices.
Moving Healthcare Toward True Equality
Disparities in patient outcomes have many underlying causes. Overcoming the evidence gap—the lack of diversity in patients across controlled trials causing a gap between research and clinical practice—is a huge undertaking, and data has many roles to play in ensuring quality care for everyone.
The connected world continues to pump up the volume, with data creation and usage skyrocketing everywhere. We take a look at internet usage, streaming media, financial transactions, and a dozen other measures of how big “big data” has become.
The World of Data Collaboration for the Climate“The topic is vast and the stakes are high. But, the good news is that we’re all in this together.” Here’s a popular roundup of insights and resources on making business—particularly business data use—more sustainable. (Also see our story and infographic Can Data Help Save the Planet?)
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