This rubric covers the use of statistical tools working on large datasets to create models and derive inferences, as well as coverage of the field in its entirety. This differs from machine learning primarily in that the latter focuses on functional gradient analysis or neural networks (kernels) to derive models.
Data governance is the management of organizations’ data availability, usability, integrity, security, and privacy. According to Gartner, Data governance is the specification of decision rights and… Read More »Data Governance Tool: What To Look For?
Increasingly, companies are focused on finding ways to connect to new and valuable sources of data in order to enhance their analytical capabilities, enrich their… Read More »Five Key Components of a Data Sharing Platform
The previous post covered the problem of oversiloing. Systems thinking, I pointed out, can help reduce the practice of siloing when it’s not necessary. In… Read More »The long game: Feedback loops and desiloed systems by design (Part II of II)
How does Spotify battle against a giant like Apple? One word: data. With machine learning and AI, Spotify creates value for its users by providing… Read More »How Metadata Improves Security, Quality, and Transparency
Every time we think we have grasped a new technology and its use. Sometimes that shift is an increase in the technology itself that seemingly… Read More »Understanding the Role of Augmented Data Catalogs in Data Governance
In this latest Data Science Central webinar, meet Shadow IT’s younger sibling. Shadow AI is the result of one-off AI initiatives inside organizations, where siloed… Read More »DSC Webinar Series: Shadow AI, the Silent Killer of Deep Learning Productivity
Data engineering is a critical part of data science. Most of the time, they occur together in business applications. However, there are some fundamental differences… Read More »Top 5 Fundamental Concepts of Data Engineering
Data science management has become an essential element for companies that want to gain a competitive advantage. The role of data science management is to… Read More »5 Product Management Tips for Data Science Projects
This is part 1 in a multi-part series on the value-realizing, collaborative power of decisions. My mom used to say, “If it was a snake,… Read More »Decisions Part 1: Creating an AI-driven Decision Factory
In a week when privacy is very much on the agenda, we ask how can we protect AI models. This is already a mature field… Read More »Could an explainable model be inherently less secure?
