Keep up with the latest trends in data engineering by downloading your new and improved copy of The Big Book of Data Engineering. You’ll benefit from data sets, code samples and best practices as you translate raw data into actionable data. You’ll also see real-life end-to-end use cases from leading companies such as J.B. Hunt, ABN AMRO and Atlassian.
The lakehouse is an increasingly popular technology that combines the analytics power of a data warehouse with the data science and ML focus of a data lake – all in one open environment. That’s why Bill Inmon and Ranjeet Srivastava believe the lakehouse can unlock tremendous value for organizations. Get insights on how to launch a successful lakehouse architecture in this eBook.
Data, analytics and AI governance is perhaps the most important yet challenging aspect of any data and AI democratization effort. For your data analytics and AI needs, you’ve probably deployed two different systems — data warehouses for business intelligence and data lakes for AI. And now you’ve created data silos with data movement across two systems, each with a different governance model.
Bill Inmon, widely considered the father of the data warehouse, believes 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.
The Databricks Lakehouse Platform for Dummies is your guide to simplifying your data storage. The lakehouse platform has SQL and performance capabilities — indexing, caching and MPP processing — to make BI work rapidly on data lakes. It also provides direct file access and direct native support for Python, data science and AI frameworks without the need to force data through an SQL-based data warehouse. Find out how the lakehouse platform creates an opportunity for you to accelerate your data strategy.
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.