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Securely Scaling Big Data Access Controls At Pinterest

Pinterest Engineering

Each dataset needs to be securely stored with minimal access granted to ensure they are used appropriately and can easily be located and disposed of when necessary. Consequently, access control mechanisms also need to scale constantly to handle the ever-increasing diversification.

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A Year of Modern: Our Top 2022 Blog Posts — Chosen by You

The Modern Data Company

In 2023, The Modern Data Company (Modern) hopes to reach more companies and organizations with our data operating system, build incredible value from existing and upcoming data assets, and share insights into major shifts in what it means to be data-driven. These were our most popular blog posts in 2022 according to reader statistics. .

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Building a Machine Learning Application With Cloudera Data Science Workbench And Operational Database, Part 1: The Set-Up & Basics

Cloudera

Python is used extensively among Data Engineers and Data Scientists to solve all sorts of problems from ETL/ELT pipelines to building machine learning models. Apache HBase is an effective data storage system for many workflows but accessing this data specifically through Python can be a struggle. Example Operations . Put Operations.

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Building Trust in Public Sector AI Starts with Trusting Your Data

Cloudera

It focuses on five key pillars: investing in research and development; unleashing government AI resources; setting standards and policy; building the AI workforce; and advancing trust and security. The post Building Trust in Public Sector AI Starts with Trusting Your Data appeared first on Cloudera Blog.

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Building Pinterest’s new wide column database using RocksDB

Pinterest Engineering

This blog post goes into the details of how we built this massively scalable, highly available wide column database using RocksDB, and provides information about the data model, APIs, and key features. It is written in C++ and offers bindings for several programming languages, making it accessible for developers in different environments.

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Building a Media Understanding Platform for ML Innovations

Netflix Tech

We build creator tooling to enable these colleagues to focus their time and energy on creativity. We knew we could leverage learnings from our colleagues who are responsible for building and innovating in this space. Thus, we didn’t build all the modules completely. Artists and video editors must create them.

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Demystifying Azure Storage Account network access

Towards Data Science

Demystifying Azure Storage Account Network Access Service endpoints and private endpoints hands-on: including Azure Backbone, storage account firewall, DNS, VNET and NSGs Connected Network — image by Nastya Dulhiier on Unsplash 1. This setup empowers consumers to perform data science tasks and build machine learning (ML) models.