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2023 Trends in Data Modeling 

In this contributed article, editorial consultant Jelani Harper discusses how the centrality of data modeling to data management will likely remain for some time. What’s most notable about this fact is it’s becoming considerably simpler to perform some of the basic tasks associated with this discipline. From flexible, schema-on-read models to the multitude of options for clarifying semantics and implementing the basics of domain models, data modeling’s effectiveness is increasing almost as much as the effort it requires is decreasing.

“Above the Trend Line” – Your Industry Rumor Central for 11/16/2022

Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz.

Comet Introduces Kangas, An Open Source Smart Data Exploration, Analysis and Model Debugging Tool for Machine Learning 

Comet, provider of a leading MLOps platform for machine learning (ML) teams from startup to enterprise, announced a bold new product: Kangas. Open sourced to democratize large scale visual dataset exploration and analysis for the computer vision and machine learning community, Kangas helps users understand and debug their data in a new and highly intuitive way.

Four Steps to Building a Data Science Organization that Delivers ROI

In this contributed article, VP, Data Science for 84.51° Insights business, Emily Gibbons, offers tips for building a successful data science organization that delivers ROI. Included is advice for understanding common pitfalls and where to begin – i.e. start small, ensure tech teams have context they need, how to drive scale and advocacy across the organization to sustain ROI.

The Chaos of Collaboration Data: Understanding the New Unstructured Data Set

In this special guest feature, Chris Plescia, Chief Technology Evangelist, Aware, highlights how conversational platforms and tools such as Slack, Microsoft Teams, Yammer, and Workplace from Meta have made the digital workplace more productive, social and collaborative but they’ve also introduced a non-standard data set into the enterprise. The article will help readers to understand the new data set by describing IT challenges, governance risks, and other considerations for the collaboration ecosystem.

Heard on the Street – 11/14/2022

Welcome to insideBIGDATA’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.

Run:ai Launches Full-Stack Solution for Hyper-Optimized Enterprise AI Built on NVIDIA DGX Systems

Run:ai, a leader in compute orchestration for AI workloads, announced the launch of the Run:ai MLOps Compute Platform (MCP) powered by NVIDIA DGX™  Systems, a complete, full-stack AI solution for enterprises. Built on NVIDIA DGX systems and using Run:ai Atlas software, Run:ai MCP is an end-to-end AI infrastructure platform that seamlessly orchestrates the hardware and software complexities of AI development and deployment into a single solution, accelerating a company’s ROI from artificial intelligence. 

Podcast Highlights: “Intel on AI”: Learning with AI

With over 15 years of experience in machine learning, neural networks, and computer vision, Microsoft’s Milena Marinova knows a thing or two about using AI for professional growth. In this podcast episode of “Intel on AI,” Milena shares lessons she’s learned during her career, including the challenges of developing AI products and the importance of data policy by design.

3 SaaS Big Data Trends You Need to Know About

In this contributed article, Nikola (Nik) Mijic, CEO & co-founder of Matik, discusses three major big data trends in the SaaS industry that you need to know about now to keep your company ahead of the curve.

Why Your Call Center Needs AI-powered Conversation Intelligence

In this contributed article, Brian Steele, VP Product Management at, discusses how conversational AI tools in call centers are developing language modeling and predictive analytics to help sales representatives streamline the sales process.