White Papers


Open APIs in Financial Services for Dummies

Download this e-book "for dummies" to find out more about open APIs and implementing open APIs strategically in financial services organizations.


Service mesh or API management

This e-book provides essential knowledge and expert guidance for building an effective service management architecture that encompasses both API management and service mesh solutions.


Top considerations for building a production-ready AI/ML environment

This e-book reviews key technologies and best practices for building a production-ready architecture for artificial intelligence (AI), machine learning (ML), and deep learning (DL) workloads. Learn how to deploy an effective AI/ML environment to support your business goals in this e-book from Red Hat.


Red Hat OpenShift and Kubernetes ... what's the difference?

Learn how Red Hat OpenShift helps organizations transition to containers and Kubernetes and realize the full potential of a hybrid cloud strategy.


Top considerations for cloud-native databases and data analytics

Databases and data analytics can help you deliver differentiated cloud-native applications and gain a competitive advantage. Containers and Kubernetes can speed development of key components of these applications. Red Hat® OpenShift® gives you a consistent Kubernetes-based foundation for implementing data-driven cloud-native application development and deployment to support your business goals. Read this e-book to discover the benefits of containerized databases and data analytics workloads.


Red Hat cloud-native development outlook

As organizations seek to develop high-quality applications faster and more securely, developers naturally look for ways to build these applications.


Application development security

See how Red Hat solutions can enhance your enterprise's security initiatives.


Advance your business with AI and ML

This e-book shows how enterprises across industries are using Red Hat OpenShift to build AI/ML solutions that deliver real business outcomes.


Data Warehouses Meet Data Lakes

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.


The Delta Lake Series Complete Collection

Learn how to bring quality, reliability, security and performance to your data lake. In “The Delta Lake Series” of eBooks, we will explore how Delta Lake brings quality, reliability, security and performance to your data lake to enable a lakehouse architecture. Download this eBook series to understand the unique capabilities of Delta Lake, explore common use cases like streaming and learn how Delta Lake delivers substantial performance improvements for our customers.


The Hidden Value of Hadoop Migration

Discover the benefits of migrating from Hadoop to a modern, cloud-based analytics platform. While reducing licensing costs is one major advantage, a modern, cloud-data platform has the speed and scale to handle all your critical use cases — helping you meet your SLAs, streamline operations and improve productivity. Read on to learn how Hadoop migration can improve business outcomes across all use cases.


The Outsourcers' Guide to Quality

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.


Crowd vs. Managed Team - A Study on Quality Data Processing at Scale

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.


20 Critical Questions to Ask Data Labeling Providers

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.


Foundations for Architecting Data Solutions

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.


Scaling Quality Training Data

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.


Accelerate AI With Annotated Data

Discover how 9 industry leading companies are employing data annotation solutions to accelerate their machine learning projects and deliver the true promise of AI.


Reduce Risk & Improve Analytics with Solutions to Real-time KYC Compliance

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!


GE Aviation: From Data Silos to Self-Service

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.


The Importance of AutoML for Augmented Analytics

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.


Empowering Chief Data Officers With Tools to Succeed

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.


Six Key Challenges to Building a Successful Data Team

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.


Data Science Operationalization: Ten Steps

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.


InDepth Report - AI Driving a Radical Reshaping of the Healthcare Industry

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.