working-with-big-data-tools-and-techniques 
O'Reilly on Data
APRIL 8, 2025
But the distinction between senior and junior software developers is built into our jobs and job titles. Whether we call it entry-level or something else, we distinguish between people who are just starting their careers and those who have been around for a while. That new role requires developing a new set of skills.
O'Reilly on Data
NOVEMBER 12, 2024
Here’s a description of some of the techniques Google puts to use to make it happen.) (Here’s a description of some of the techniques Google puts to use to make it happen.) For example, you could ask it to fill out a spreadsheet with data it collects from websites. So here’s a quick list of things that have amazed me recently.
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KDnuggets
SEPTEMBER 11, 2023
Where do you start in a field as vast as big data? Which tools and techniques to use? We explore this and talk about the most common tools in big data.
O'Reilly on Data
MARCH 25, 2025
Two big things: They bring the messiness of the real world into your system through unstructured data. When your system is both ingesting messy real-world data AND producing nondeterministic outputs, you need a different approach. Lets be real: building LLM applications today feels like purgatory. Leadership gets excited.
O'Reilly on Data
SEPTEMBER 15, 2020
AI Benefits and Stakeholders. AI is a field where value, in the form of outcomes and their resulting benefits, is created by machines exhibiting the ability to learn and “understand,” and to use the knowledge learned to carry out tasks or achieve goals. AI-generated benefits can be realized by defining and achieving appropriate goals.
O'Reilly on Data
MARCH 24, 2020
In a world focused on buzzword-driven models and algorithms, you’d be forgiven for forgetting about the unreasonable importance of data preparation and quality: your models are only as good as the data you feed them. Why is high-quality and accessible data foundational?
O'Reilly on Data
SEPTEMBER 19, 2023
It progressed from “raw compute and storage” to “reimplementing key services in push-button fashion” to “becoming the backbone of AI work”—all under the umbrella of “renting time and storage on someone else’s computers.” All they needed was a tool that could handle the massive workload.
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