On-demand resources

Rithesh Makkena, Global Head of Partner Sales Engineering of Snowflake, and Guy Adams, CTO of DataOps.live unpack Snowflake’s DevOps building blocks and how DataOps.live builds on top of these to deliver full CI/CD for Snowflake data products and native apps. 

Learn from IDC award-winning data platform consultant Paul Rankin how some of Switzerland's top companies are turning their attention to the developer experience in combination with true DataOps principles to increase productivity and accelerate data product development cycles.

Join us to learn how to build AI-powered data products using Snowflake and DataOps.live and how to industrialize your LLM fine-tuning with DataOps. Learn how to:

• Create high-quality models from training and validation data 

• Use AI Observability to assess model quality for Snowflake Cortex 

• Compare model performance for your data application with TruLens 

Host and Snowflake Data Superhero Frank Bell leads a no-holds-barred series of 30-minute discussions that dig into how, when, and why you should use DataOps.live.  

Learn all about DataOps.live new product features and how they work with the latest Snowflake product updates. You'll also see how you can use DataOps.live Assist to create a Streamlit application.

In this session we will build a Cortex-powered Snowflake Native App into production in less than ten minutes! Oh, and just to increase the degree of difficulty, we’ll include a Streamlit app. And some Snowpark. And let’s include Snowpark Container Services and some UDFs for good measure. All in 10 minutes or less?!

In today's data-driven landscape, the demand for creating high-quality Data Products more quickly is greater than ever. In this hands-on webinar for data engineers and data product owners, you will learn how we use DataOps.live Create and DataOps.live Assist to build trusted Data Products literally in minutes.

Watch and learn how to create new data products with simplicity and speed. Discover how the new DataOps.live Create helps you capture the business requirements. Learn how to use our new Assist AI-copilot in the DataOps Development Environment to rapidly create new datasets and data products. 

Listen to the replay of this exclusive webinar where DataOps.live, Snowflake and data.world industry experts unravel the complexities of AI strategy, data foundation, and seamless platform integration to accelerate business impact and strong ROI.

Join DataOps.live, Snowflake and Digikey as we unpack Digikey's cloud migration journey, along with real-world examples and use cases for their Data Product goals.

Topics include:  

• Data Platforms & Tooling Requirements and Selection Criteria
• DataOps/Data Products Strategy design discussion
• How to leverage DataOps.live to power Data Science initiatives 
• Integrating Data Governance details into Data Products
• Other tips and tricks for successful Data Product deployments

About DigiKey: Digikey is the fourth largest electronic component distributor in North America and the fifth largest electronic component distributor worldwide.

This discussion addresses the following key questions.

• How can enterprises achieve competitive advantages and operational efficiencies by accelerating the delivery of better AI/ML applications in the cloud?
• What platforms and tools do enterprises require to accelerate the building and deployment of trustworthy AI/ML applications in the cloud?
• What data engineering and data science best practices are key to enabling rapid development and deployment of high-performance cloud-native AI/ML applications?
• How should enterprises use advanced data sharing, data clean room, and data security capabilities in a cloud environment to build more compliant AI/ML applications?
• When should enterprises use cloud data marketplaces to acquire external data sets and other assets needed to accelerate the delivery of high-quality AI/ML applications?

Introducing DataOps.live Assist, your copilot for our Data Product Management Platform:  ​

• Become more productive in creating your SQL and Python models as a data engineer​
• Benefit from augmented code reviews and merge requests as a data product owner​
• Use our DataOps development environment with Snowflake SSO users​
• Learn the latest about updated and newly launching orchestrators​
• ...and more!

Data Products are all the rage. But to have real impact, it is essential to use the right methodology and tools to build and manage them. By bringing the best aspects of DevOps to Data, DataOps is that methodology. And when deployed using a leading platform like DataOps.live, you can achieve unmatched developer productivity without compromising on agility and governance. 

Many enterprises today face a data dilemma: long time to insights, limited data access, and data quality that's questionable at best. Data Productization is the answer to this problem. But what is a Data Product to you? In this fireside chat, the authors of the new book, Data Product for Dummies, and an esteemed panel of industry leaders discuss the definition of Data Products and how to build and manage them so they can create value for your organization. Bonus: get your FREE copy of the new Data Products for Dummies book, which gives pragmatic guidance to help the next wave of practitioners and adopters generate enormous value—without so many battle scars.

Whether you are just starting with Snowflake or taking full advantage of advanced features and use cases, there are always opportunities for optimization and efficiency.

Watch as DataOps.live and XponentL Data as they discuss how Spendview and Snoptimizer can help optimize your budget by identifying and automating optimization best practices and cost-saving strategies. 

Data Products are the future of how organizations will organize, develop, and deploy data assets and data applications. But current information about data products can be complex and confusing. Data Products for Dummies is your one-stop guide to moving beyond the theory to embark on a pragmatic and practical journey toward building data products for your organization.

Join Thomas Steinborn, VP of Products and Mark Bartlo, Senior Sales Engineer, at DataOps.live for our Data Products Done Right webinar. In this 45-minute event, you will learn how to:

• Turn data into an asset
• Manage Data as a Product with a concrete roadmap
• Automatically version the datasets of your Data Product
• Ensure Data Products don't break backward compatibility on release
• Understand the guardrails guiding your versioning decisions
  ...and more!

Sign for the DataOps.live Summer '23 launch webinar and learn how to:

• Optimize your Snowflake spend and consumption
• Utilize Your Snowflake data warehouse perfectly
• Identify your biggest spenders
• Build your next generation Data Product
• Treat Data as a Product
• Automatically version your Data Product 
• Ensure Data Products don't break backward compatability
• ...and more!
  

   

You may have heard about this large national bank where one customer data product has powered nearly 60 use cases—ranging from real-time scoring of credit risk to chatbots that answer customers’ questions—providing $60 million in incremental revenue and eliminating $40 million in losses annually (source: the Harvard Business Review). Too good to be true? Not for organizations using DataOps.live!

In today’s economic times, businesses are under increased scrutiny and only the most critical projects will get off the ground. Businesses have to be laser focused on their data spending and ensure proper utilization of technology.

Leveraging the Snowflake Data Cloud as your data platform enables data mobilization with near-unlimited scale, concurrency, and performance, but your operations and development teams may need extra support to streamline  migration and create data products. 

The combination of Collibra, Snowflake and DatatOps.live can help you achieve success and create value throughout your organization.

"When should we look at DataOps.live?” This is one of the most common questions we get when speaking with prospective Snowflake customers along with:

• Are there benefits to including DataOps.live DURING the evaluation process?
• What would this process look like?
• What about adding DataOps.live AFTER evaluating and selecting Snowflake as their Data Cloud?

In this webinar, you will learn how DataOps.live and VaultSpeed can help you:

• Successfully deploy and manage a Data Vault on Snowflake
• Develop data products faster and manage their lifecycle
• Reduce the costs of your data pipelines for Snowflake
• Bring more agility, flexibility, and resilience to change over time

Join DataOps.live’s Guy Adams, CTO & Co-Founder and Mark Bartlo, Senior Sales Engineer who will lead you through the journey from automated development, orchestration, observability and deployment to effective lifecycle management of Data Products.

In this session, we profile how a major pharmaceutical research company was able to scale out to 50 data products in less than 18 months. 

DataOps has been a hot topic lately—and you may be contemplating your approach to solve problems related to complex pipelines, lack of governance and trust in your data. While it would seem that a "DIY" approach makes sense, there's a better option and it's called DataOps.live.

This webinar is intended to introduce you to the latest updates from DataOps.live, including how to:  

• Automate, orchestrate, deploy, and govern your Data Products with our new Orchestrator for Collibra and Informatica
  
• Streamline and accelerate the build and deployment of your data vault defined in VaultSpeed
  
• Jumpstart your data team’s productivity using our exciting DataOps Developer Environment
  
• Have complete confidence in data infrastructure changes for Snowflake
  
• Improve compliance and enterprise security practices by leveraging new environment management capabilities.

Watch this webinar in partnership with DataOps.live and Roche Diagnostics, if you’d like to explore:

• How to build and deploy a single data product and data mesh approach with dramatic results
• The practical challenges of building a DataOps and data mesh center of excellence in an enterprise company
•  The working structures, blueprints, cadences, and collaboration needed to drive continual success week by week to each new domain.

To remain a data-first organization and to continue to prioritize self-service analytics, companies must move away from a centralized data architecture and consider alternatives. One such alternative is the domain-driven data mesh.  

Watch this master class with Snowflake and DataOps.live to learn:

• What the practical challenges are of implementing a data mesh
• Design patterns that can be used to overcome these challenges   
• How to be successful in building a domain-driven data mesh.

The global pandemic has accelerated the need for digital transformation, underscoring the necessity to be online for education, work, access to healthcare and to enable the IoT future and a pathway to 5G. OneWeb is driven by data: how the business operates, the partners it works with, the customers it serves, and IoT telemetry data on the status and health of millions of devices 24/7.

Join this session to learn:

• How OneWeb is securely storing and governing every item of data and automating every data pipeline from source to destination
• How they’ve built a data hub to foster a culture of self-service analytics across their business
• How they’re leveraging data sharing and have built their own private data exchange.

DataOps describes a novel way of development teams working together collaboratively around data to achieve rapid results and improve customer satisfaction. This book is intended for everyone looking to adopt the DataOps philosophy to improve the governance and agility of their data products. The principles in this book should create a shared understanding of the goals and methods of DataOps and #TrueDataOps and create a starting point for collaboration.

What You'll Learn:

• 10 Reasons to Consider DataOps
• Getting Started with DataOps
• Understanding the Benefits of DataOps
• Discover 7 Pillars of The #TrueDataOps Philosophy.

What's inside?

• This report examines four leading DataOps platforms: DataKitchen, DataOps.live, Zaloni, and Unravel. It describes each product, highlights its key differentiators, and identifies target customers for each
  
• From these profiles, readers will better understand the range of DataOps offerings and discover which products are best suited to their needs
  
• "DataOps.live is a great choice for companies that need orchestration of complex data pipelines around Snowflake, especially if they rely on a lot of IoT data. Its hybrid approach means you can use native development and testing tools for some data pipeline processes, and orchestrate any 3rd party tools as required."

Data engineering and its associated need to create optimized, orchestrated data pipelines that extract data from multiple, disparate data sources and load it into a centralized data platform, has risen to prominence. Before the development of automated workflow orchestration tools (like Airflow), data pipeline functionality was either manually coded and implemented, or run by batches of multiple lengthy crons and repetitive custom API calls. This has caused an erosion in the quality of the resultant data insights because of the overwhelming manual nature of data pipeline management before the arrival of workflow orchestration tools.

There is now a need to apply some (or all) of DevOps principles, battle hardened in the software development industry, to this world of data, to ensure the implementation of Agile and Lean principles in the data pipeline creation, testing, deployment, monitoring, and maintenance lifecycles. This white paper delves into the #TrueDataOps philosophy and why Apache Airflow, the forerunner, and originator of automated workflow monitoring and management tools, never was an ideal solution for data pipeline orchestration workflows. 

All too often, data is treated as a second-class citizen. Many organizations need the proper alignment on data ownership, leading to poor decision-making and unaccountable data that spawns risk. Treating your data as a product allows you to deliver complete data products with embedded value to support business agility and intelligence.