LLMs are hugely popular with data engineers because they boost productivity. But companies must adapt their data governance programs to control risks related to data quality, privacy, intellectual property, fai-Datarness, and explainability.
Published at: https://www.eckerson.com/articles/should-ai-bots-build-your-data-pipelines-part-ii-risks-and-governance-approaches-for-data-engineers-to-use-large-language-models

Should AI Bots Build Your Data Pipelines? Part II - Audio Blog

MDM creates business value in three ways: it streamlines infrastructure, streamlines processes, and reduces risk.
Published at: https://www.eckerson.com/articles/driving-roi-with-master-data-management-part-1-build-your-business-case

Driving ROI with Master Data Management, Part 1: Build Your Business Case - Audio Blog

Dan O'Brien and Kevin Petrie discuss FinOps, which is a cost governance discipline for cloud-based analytics and operational projects.

Analyst Series: Governing Costs with FinOps for Cloud Analytics

Generative AI brings a promise to improve lives in a blistering innovation race, but also a threat to people, corporations, and even nations. Data analytics leaders must understand the risks of generative AI, both societal and business-related, to use it positively and avoid the destructive consequences seen with nuclear energy development.
Published at: https://www.eckerson.com/articles/the-opportunity-and-risk-of-generative-ai-part-i-a-nuclear-explosion

The Opportunity and Risk of Generative AI Part I: A Nuclear Explosion - Audio Blog

It's not easy being the head of data & analytics at a large organization. You must align a large team across multiple disciplines; you must deal with oodles of legacy systems and tools that hamper innovation; and you must deliver business value fast to keep executives at bay and your job intact. You also need to recruit dynamic managers who can push the envelope while meeting operational objectives. And when you falter--which you inevitably will-you have to rebound fast. 

No one knows these lessons better than Tiffany Perkins-Munn. She currently runs a 275-person data & analytics team at JP Morgan Chase that consists of data engineers, data scientists, behavioral economists, and business intelligence experts.  She thrives on versatility, having earned a Ph.D. in Social-Personality Psychology with an interdisciplinary focus on Advanced Quantitative Methods. Building on this foundation, she has accumulated vast experience in the art of managing data & analytics teams during her 23 years in technical and managerial roles in the financial services industry. 

In this interview, you’ll learn:

1. Tiffany’s secret for aligning a large data & analytics team and keep them from splitting into silos of specialization
2. Her favorite techniques for recruiting the right people to her team. 
3. How to wade through the thicket of legacy systems and deliver innovative solutions quickly. 
4. The impact of GenAI on her operations and the financial services industry. 
5. How to advance your careers in data & analytics.

Interview with Tiffany Perkins-Munn

Data engineers and data scientists must manage pipelines for unstructured data to ensure healthy inputs for language models.
Published at:
https://www.eckerson.com/articles/why-and-how-data-engineers-will-enable-the-next-phase-of-generative-ai

Why and How Data Engineers Will Enable the Next Phase of Generative AI - Audio Blog

This blog explores three criteria to evaluate tools that manage unstructured data pipelines for GenAI.
Published at:
https://www.eckerson.com/articles/data-engineering-for-genai-three-criteria-to-evaluate-pipeline-tools

Data Engineering for GenAI: Three Criteria to Evaluate Pipeline Tools - Audio Blog

Data teams must filter, blend, and refine raw data inputs to create the high-octane fuel that drives innovation with artificial intelligence and machine learning (AI/ML).
Published at:
https://www.eckerson.com/articles/refining-the-right-fuel-how-data-integration-drives-the-ai-ml-model-lifecycle

Refining the Right Fuel: How Data Integration Drives the AI/ML Model Lifecycle

As organizations grapple with data spread across various storage locations, solutions like Coginiti Hybrid Query offer a much-needed alternative to fragmented tools.
Published at:
https://www.eckerson.com/articles/a-novel-approach-for-reducing-cloud-data-warehouse-expenses-from-coginiti

A Novel Approach for Reducing Cloud Data Warehouse Expenses from Coginiti - Audio Blog

This article by Piotr Czarnas, founder of DQOps, outlines a proven, team-based approach to tackling persistent issues like invalid data, delayed reporting, and inconsistent formats.
Published at:
https://www.eckerson.com/articles/overcoming-the-challenge-of-low-data-quality

Overcoming The Challenge of Low Data Quality - Audio Blog

Listen to data and analytics leaders share the secrets of their success. Wayne Eckerson, long-time global thought leader interviews guests who run data and analytics programs at Fortune 2000 organizations around the world. Tune in to stay abreast of the latest technologies, techniques, and trends in our fast-paced industry.

New tracks tagged #DataEngineers