Integrating, Governing, and Consuming Data for the Machine Learning Lifecycle

Jun 09, 2022 by Kevin Petrie in Decoding Data Software

ABSTRACT:

To succeed with machine learning projects, data science teams must handle key aspects of data management and consumption.

Data Architecture as a Service: How to Evaluate Products

Jun 09, 2022 by Wayne Eckerson in Data Strategy Insider

ABSTRACT:

Products that support data architecture-as-a-service are emerging. This article describes what to look for in a commercial DAaaS-based product.

Deep Dive on Machine Learning Platforms: Three Tools to Consider

Jun 03, 2022 by Kevin Petrie in Decoding Data Software

ABSTRACT:

Enterprises need to foster open collaboration between business owners, data scientists, machine learning (ML) engineers, and data engineers. The machine learning platform enables these cross-functional teams to build and manage ML projects as part of an efficient, governed, and scalable process....

Testing Capabilities and Tools for Data Engineers – Part 2

Jun 03, 2022 by Guest Author and Wayne Yaddow in Guest Blogs

ABSTRACT:

This article outlines how and why data engineers perform tests on their work efforts as they use automated testing and monitoring tools.

Autonomous Data Management: Requirements, Use Cases, and Guidelines

May 20, 2022 by Kevin Petrie in Decoding Data Software

ABSTRACT:

Autonomous data management (ADM) software uses metadata, automation, and artificial intelligence to standardize and accelerate data delivery. ADM guides data teams with prompts and recommendations as they manage infrastructure, data pipelines, and governance. Enterprises can use ADM to ease...