new-data-architectures-are-too-data-store-centric 
O'Reilly on Data
OCTOBER 19, 2021
As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. The new category is often called MLOps. Just introducing a new term like MLOps doesn’t solve anything by itself, rather, it just adds to the confusion.
Data Virtualization
FEBRUARY 28, 2020
Too often the design of new data architectures is based on old principles: they are still very data-store-centric. They consist of many physical data stores in which data is stored repeatedly and redundantly. Over time, new types of data stores,
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CIO Business Intelligence
APRIL 8, 2025
Data is the foundation of innovation, agility and competitive advantage in todays digital economy. As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. Data quality is no longer a back-office concern.
DataKitchen
NOVEMBER 4, 2021
Data organizations often have a mix of centralized and decentralized activity. DataOps concerns itself with the complex flow of data across teams, data centers and organizational boundaries. It expands beyond tools and data architecture and views the data organization from the perspective of its processes and workflows.
CIO Business Intelligence
NOVEMBER 22, 2022
Digital transformation initiatives have picked up in the retail sector in recent years as store chains compete for brand awareness and sales in a rapidly evolving market. I’m also impressed with their willingness to integrate new technologies in their businesses. Are they successfully untangling their “spaghetti architectures”?
CIO Business Intelligence
AUGUST 21, 2024
It was many measurements the agents collectively decided was either too many contaminants or not.” The previous state-of-the-art sensors cost tens of thousands of dollars, adds Mattmann, who’s now the chief data and AI officer at UCLA. The systems are fed the data, and trained, and then improve over time on their own.”
Cloudera
AUGUST 21, 2021
There is an urgent need for banks to be nimble and adaptable in the thick of a multitude of industry challenges, ranging from the maze of regulatory compliance, sophisticated criminal activities, rising customer expectations and competition from traditional banks and new digital entrants. Addressing new customers and markets.
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