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Using COD and CML to build applications that predict stock data

Cloudera

This is purely an example of how to develop a solution using Cloudera’s software. . CML is designed for data scientists and ML engineers, enabling them to create and manage ML projects from code to production. Production ML Toolkit – Deploying, Serving, Monitoring, and Governance of ML models. Main features of CML: .

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The evolution of Facebook’s iOS app architecture

Engineering at Meta

As more and more products were integrated into the app, its launch time began to degrade, and people began to notice. For the sake of brevity, we’ll focus only on the ones that had a long-term effect on the app’s architecture: The app’s ‘pre-main’ time was growing at an unbounded rate, as the app’s size grew with each product.

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Product Owner vs Business Owner: A Detailed Comparison

Knowledge Hut

Differentiating between a Product Owner and Business Owner can be a challenge, as their roles and responsibilities sometimes overlap. Business owners and product owners are two key stakeholders who envision, create and take the product and the business forward. Who is a Product Owner? So, let’s begin!

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13 Best Product Owner Tools You Should Master in 2023

Knowledge Hut

The product owner prioritizes backlogs, plans product development stages, interprets, and works up to customers’ requirements. A fundamental part of the agile methodology, the product owner curates and handles the vision board. But with this role comes an amalgamation of principles and some undeniable product owner tools.

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A Day in the Life of a Palantir Incident Management Engineer

Palantir

The Incident Response team must be ready to handle any problem that arises, and to work efficiently and effectively across the business, coordinating with stakeholders while navigating documentation, metrics, and software operations interfaces. If the product team needed to un-recall it for some reason, they could do so in just a few clicks.

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How to Build a Mature dbt Project from Scratch

dbt Developer Hub

From this vantage point, we have gained a unique understanding of the dbt adoption curve - how companies actually implement and expand their usage of dbt. Walking along this matrix we can watch a teeny tiny baby project grow into a fully mature production grade dbt pipeline. How do we do this?

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10 DataOps Principles for Overcoming Data Engineer Burnout

DataKitchen

Data from New Vantage partners showed that the number of data-driven organizations has actually declined to 24% from 37% several years ago and that only 29% of organizations are achieving transformational outcomes from their data. . This transformation has already taken place in software engineering.