Towards Data Science
OCTOBER 30, 2024
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.
Engineering at Meta
FEBRUARY 4, 2025
Here we explore initial system designs we considered, an overview of the current architecture, and some important principles Meta takes into account in making data accessible and easy to understand. Users have a variety of tools they can use to manage and access their information on Meta platforms. feature on Facebook.
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Start Data Engineering
MAY 28, 2024
Building efficient data pipelines with DuckDB 4.1. Use DuckDB to process data, not for multiple users to access data 4.2. Introduction 2. Project demo 3. Cost calculation: DuckDB + Ephemeral VMs = dirt cheap data processing 4.3. Processing data less than 100GB? Use DuckDB 4.4.
Engineering at Meta
MARCH 12, 2024
By the end of 2024, we’re aiming to continue to grow our infrastructure build-out that will include 350,000 NVIDIA H100 GPUs as part of a portfolio that will feature compute power equivalent to nearly 600,000 H100s. RSC has accelerated our open and responsible AI research by helping us build our first generation of advanced AI models.
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Organizations look to embedded analytics to provide greater self-service for users, introduce AI capabilities, offer better insight into data, and provide customizable dashboards that present data in a visually pleasing, easy-to-access format.
Snowflake
APRIL 16, 2025
Welcome to Snowflakes Startup Spotlight, where we learn about awesome companies building businesses on Snowflake. Im inspired by the idea of simplifying traditionally complex tasks like building robust data-driven applications and making them accessible to everyone. What inspires you as a founder?
Snowflake
SEPTEMBER 18, 2023
However, building such data apps has not been easy. Any data practitioner or product owner will attest to how it takes a lot of steps to build a data app. Bring data and ML models to life Interactive visualizations Data teams now have the ability to build a whole range of new and exciting applications that were not possible before.
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We hope this guide will transform how you build value for your products with embedded analytics. Access the Definitive Guide for a one-stop-shop for planning your application’s future in data.
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Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.
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Just by embedding analytics, application owners can charge 24% more for their product. How much value could you add? This framework explains how application enhancements can extend your product offerings. Brought to you by Logi Analytics.
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Organizational data literacy is regularly addressed, but it’s uncommon for product managers to consider users’ data literacy levels when building products. Product managers need to research and recognize their end users' data literacy when building an application with analytic features.
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