This comprehensive reference guide provides everything you need to get started with data science at scale — including code samples, notebooks and use cases from leading companies such as Comcast, Regeneron and Nationwide.
The world of machine learning is evolving so quickly that it’s challenging to find real-world use cases that are relevant to what you’re working on. That’s why we collected these technical blogs from industry thought leaders with practical use cases you can leverage today. This how-to reference guide provides everything you need — including code samples and notebooks — to start putting the Databricks platform to work.
Want to learn how to overcome key data reliability challenges? Download a preview of the O’Reilly ebook, Delta Lake: The Definitive Guide, to learn about Delta Lake basic operations and how the time travel feature gives you access to historical data.
Bill Inmon, widely considered the father of the data warehouse, heralds the birth of the data lakehouse, which makes efficient ML and business analytics possible directly on data lakes. According to Bill, the data lakehouse presents an opportunity similar to the early years of the data warehouse market. The lakehouse’s unique ability to combine the data science focus of the data lake with the analytics power of the data warehouse — in an open environment — will unlock incredible value for organizations.
This comprehensive eBook showcases data engineering best practices on the Databricks Lakehouse Platform. You‘ll learn how to translate raw data into actionable data — armed with data sets, code samples and best practices from leaders and experts.
Databricks is proud to announce that Gartner has named us a Leader in both the 2021 Magic Quadrant for Cloud Database Management Systems and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms. Download these reports to learn why Databricks was named a Leader and gain additional insight on what to look for when evaluating a cloud data platform that can deliver on both your traditional analytics needs and your goals for AI.
This e-book shows how enterprises across industries are using Red Hat OpenShift to build AI/ML solutions that deliver real business outcomes.
Ventana Research found that 73% of organizations are combining their data warehouse and data lakes in some way — and 23% of organizations are replacing the data warehouse with data lakes. As the data warehouse and data lake converge, a new data management paradigm has emerged that combines the best of both worlds: the Lakehouse architecture.
Like any project or task, without the proper tools, data labeling vendors simply can’t do a good job. Learn tips for evaluating vendor toolsets and our approach to tooling in the Outsourcer's Guide to Quality.
Hivemind data scientists tested CloudFactory’s managed workforce against a leading crowdsourcing platform’s anonymous workers. Completing a series of tasks, from basic to complicated, they determined which team delivered the highest-quality structured datasets and costs associated.
When you’re creating high-performing machine learning models, you need quality, labeled data...and lots of it. Getting it can be a challenge. A growing number of innovators are outsourcing data labeling operations so their teams can focus on strategy and innovation. Choosing a data labeling partner is an important decision that can affect your model performance and speed to market. But how do you choose the right data labeling vendor? Find all of the answers here.
Now more than ever, CIOs and COOs must maximize long-term success throughout the life of AI projects. One of the ways of doing that is by reducing risk.
The right workforce gives you the flexibility to respond to changes in the market, products or your business. Find out which workforce is ideal for scaling and accelerating your AI training data labeling.
Discover how 9 industry leading companies are employing data annotation solutions to accelerate their machine learning projects and deliver the true promise of AI.
Leverage our digital identity cloud API Personator to protect against fraud, verify customer data and ensure compliance at point-of-entry. Cross verify all contact information – address, name, email and phone – and SSN and ID documentation with Personator. Try it Free!
This white paper tells the story of GE Aviation’s data revolution. Discover the history of their data teams, the technological and organizational setup that enabled transformation, use cases, how they handle data education, and more.
This white paper provides a deep dive into how AutoML came to be, the difference between it and Augmented Analytics, and how they both have brought about the rise of the citizen data scientist.
We surveyed more than 50 Chief Data Officers (CDOs) worldwide to uncover how they overcome their data and organizational challenges. This report explores the data landscape and maps the Data Revolution. Learn more.
Whether you’re in the process of building a data team from the ground up or looking to scale a data team that already exists, this white paper will detail how to address, avoid, and fix challenges. Learn more.
Use this guide to learn how to find the common ground between data and IT teams, empowering them to work together to operationalize data projects - quickly. Get the details behind the ten recommendations to go from data project development to operationalizion. Learn more.
Read this In-Depth Report to find out more about the prominent role Artificial Intelligence (AI) is taking in the healthcare industry including medical records management, predictive analytics, early diagnosis, and treatment design. Learn more.