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9 IT resolutions for 2025

CIO Business Intelligence

Balancing the rollout with proper training, adoption, and careful measurement of costs and benefits is essential, particularly while securing company assets in tandem, says Ted Kenney, CIO of tech company Access. Our success will be measured by user adoption, a reduction in manual tasks, and an increase in sales and customer satisfaction.

IT 140
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Beyond “Prompt and Pray”

O'Reilly on Data

Instead of having LLMs make runtime decisions about business logic, use them to help create robust, reusable workflows that can be tested, versioned, and maintained like traditional software. By predefined, tested workflows, we mean creating workflows during the design phase, using AI to assist with ideas and patterns.

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Top Productivity Metrics Examples & KPIs To Measure Performance And Outcomes

datapine

2) How To Measure Productivity? For years, businesses have experimented and narrowed down the most effective measurements for productivity. Your Chance: Want to test a professional KPI tracking software? Use our 14-day free trial and start measuring your productivity today! How To Measure Productivity?

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The Race For Data Quality in a Medallion Architecture

DataKitchen

The Race For Data Quality In A Medallion Architecture The Medallion architecture pattern is gaining traction among data teams. It is a layered approach to managing and transforming data. It sounds great, but how do you prove the data is correct at each layer? How do you ensure data quality in every layer ? Bronze layers should be immutable.

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Escaping POC Purgatory: Evaluation-Driven Development for AI Systems

O'Reilly on Data

Weve seen this across dozens of companies, and the teams that break out of this trap all adopt some version of Evaluation-Driven Development (EDD), where testing, monitoring, and evaluation drive every decision from the start. What breaks your app in production isnt always what you tested for in dev! The way out?

Testing 174
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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

While there isn’t an authoritative definition for the term, it shares its ethos with its predecessor, the DevOps movement in software engineering: by adopting well-defined processes, modern tooling, and automated workflows, we can streamline the process of moving from development to robust production deployments. Why: Data Makes It Different.

IT 363
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The Quality of Auto-Generated Code

O'Reilly on Data

We know how to test whether or not code is correct (at least up to a certain limit). Given enough unit tests and acceptance tests, we can imagine a system for automatically generating code that is correct. Given enough unit tests and acceptance tests, we can imagine a system for automatically generating code that is correct.

Testing 360