Monte Carlo
JUNE 6, 2023
Generative AI is taking the world by storm – here’s what it means for data engineering and why data observability is critical for this groundbreaking technology to succeed. Maybe you’ve noticed the world has dumped the internet, mobile, social, cloud and even crypto in favor of an obsession with generative AI. But is there more to generative AI than a fancy demo on Twitter?
Medium Data Engineering
JUNE 6, 2023
“The measure of intelligence is the ability to change” — Albert Einstein Continue reading on Medium »
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Analytics Vidhya
JUNE 20, 2023
Introduction In today’s data-driven world, organizations across industries are dealing with massive volumes of data, complex pipelines, and the need for efficient data processing. Traditional data engineering solutions, such as Apache Airflow, have played an important role in orchestrating and controlling data operations in order to tackle these difficulties.
The Pragmatic Engineer
JUNE 1, 2023
👋 Hi, this is Gergely with a bonus, free issue of the Pragmatic Engineer Newsletter. We cover one out of four topics in today’s subscriber-only The Scoop issue. If you’re not yet a full subscriber, you missed this week’s deep-dive on Agoda’s private cloud setup. To get the full issues, twice a week, subscribe here.
Speaker: Dr. Greg Loughnane and Chris Alexiuk
Technology professionals developing generative AI applications are finding that there are big leaps from POCs and MVPs to production-ready applications. They're often developing using prompting, Retrieval Augmented Generation (RAG), and fine-tuning (up to and including Reinforcement Learning with Human Feedback (RLHF)), typically in that order. However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are le
Data Engineering Podcast
JUNE 25, 2023
Summary Data transformation is a key activity for all of the organizational roles that interact with data. Because of its importance and outsized impact on what is possible for downstream data consumers it is critical that everyone is able to collaborate seamlessly. SQLMesh was designed as a unifying tool that is simple to work with but powerful enough for large-scale transformations and complex projects.
Data Engineering Digest brings together the best content for data engineering professionals from the widest variety of industry thought leaders.
Netflix Tech
JUNE 14, 2023
By Jennifer Shin , Tejas Shikhare , Will Emmanuel In 2022, a major change was made to Netflix’s iOS and Android applications. We migrated Netflix’s mobile apps to GraphQL with zero downtime, which involved a total overhaul from the client to the API layer. Until recently, an internal API framework, Falcor , powered our mobile apps. They are now backed by Federated GraphQL , a distributed approach to APIs where domain teams can independently manage and own specific sections of the API.
Confluent
JUNE 8, 2023
ChatGPT and data streaming can work together for any company. Learn a basic framework for using GPT-4 and streaming to build a real-world production application.
Analytics Vidhya
JUNE 12, 2023
Introduction Meet Tajinder, a seasoned Senior Data Scientist and ML Engineer who has excelled in the rapidly evolving field of data science. Tajinder’s passion for unraveling hidden patterns in complex datasets has driven impactful outcomes, transforming raw data into actionable intelligence. In this article, we explore Tajinder’s inspiring success story.
The Pragmatic Engineer
JUNE 22, 2023
👋 Hi, this is Gergely with a bonus, free issue of the Pragmatic Engineer Newsletter. In every issue, I cover topics related to Big Tech and startups through the lens of engineering managers and senior engineers. In this article, we cover one out of five topics from today’s subscriber-only The Scoop issue. To get full issues twice a week, subscribe here.
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databricks
JUNE 29, 2023
Introduction We are thrilled to unveil the English SDK for Apache Spark, a transformative tool designed to enrich your Spark experience. Apache Spark™.
KDnuggets
JUNE 8, 2023
This article discusses the significance of large language and visual models in AI, their capabilities, potential synergies, challenges such as data bias, ethical considerations, and their impact on the market, highlighting their potential for advancing the field of artificial intelligence.
Netflix Tech
JUNE 1, 2023
By Jose Fernandez , Ed Barker , Hank Jacobs Introduction In November 2022, we introduced a brand new tier — Basic with ads. This tier extended existing infrastructure by adding new backend components and a new remote call to our ads partner on the playback path. As we were gearing up for launch, we wanted to ensure it would go as smoothly as possible.
LinkedIn Engineering
JUNE 20, 2023
Co-authors: Shivansh Mundra , Gonzalo Aniano Porcile , Smit Marvaniya , Hany Farid A core part of what we do on the Trust Data Team at LinkedIn is create, deploy, and maintain models that detect and prevent many types of abuse. This spans the detection and prevention of fake accounts, account takeovers, and policy-violating content. We are constantly working to improve and increase the effectiveness of our anti-abuse defenses to protect the experiences of our members and customers.
Analytics Vidhya
JUNE 25, 2023
In a data-driven world, behind-the-scenes heroes like data engineers play a crucial role in ensuring smooth data flow. Imagine being an online shopper who suddenly receives irrelevant recommendations. A data engineer investigates the issue, identifies a glitch in the e-commerce platform’s data funnel, and swiftly implements seamless data pipelines.
The Pragmatic Engineer
JUNE 13, 2023
👋 Hi, this is Gergely with the monthly, free issue of the Pragmatic Engineer Newsletter. In every issue, I cover challenges at Big Tech and startups through the lens of engineering managers and senior engineers. If you’re not a subscriber, you missed the issue on Shopify’s leveling split and a few others. Subscribe to get two full issues every week.
Lyft Engineering
JUNE 6, 2023
Discover how Lyft identified and fixed performance issues in our streaming pipelines. Background Every streaming pipeline is unique. When reviewing a pipeline’s performance, we ask the following questions: “Is there a bottleneck?”, “Is the pipeline performing optimally?”, “Will it continue to scale with increased load?” Regularly asking these questions are vital to avoid scrambling to fix performance issues at the last minute.
KDnuggets
JUNE 15, 2023
Discover the full potential of the Julia programming language for data analysis and modeling with a comprehensive guide that covers everything from its syntax to advanced techniques.
Netflix Tech
JUNE 5, 2023
by Akshay Garg , Roger Quero Introduction Maximizing immersion for our members is an important goal for the Netflix product and engineering teams to keep our members entertained and fully engaged in our content. Leveraging a good mix of mature and cutting-edge client device technologies to deliver a smooth playback experience with glitch-free in-app transitions is an important step towards achieving this goal.
LinkedIn Engineering
JUNE 26, 2023
For the last several years, internal infrastructure at LinkedIn has been built around a self-service model, enabling developers to onboard themselves with minimal support. We have various user experiences that let application teams provision their own resources and infrastructure, generally by filling out forms or using command-line tools. For example, developers can provision Kafka topics, Espresso tables, Venice stores and more via Nuage , our internal cloud-like infra management platform.
Analytics Vidhya
JUNE 24, 2023
Introduction In the era of data-driven decision-making, having accurate data modeling tools is essential for businesses aiming to stay competitive. As a new developer, a robust data modeling foundation is crucial for effectively working with databases. Properly configured data structures ensure a smoother workflow and prevent data loss or misplacement.
The Pragmatic Engineer
JUNE 15, 2023
GitHub surveyed 500 developers in the US for a sense of how they use AI coding tools. I examine the results and add context on how the survey was conducted.
Lyft Engineering
JUNE 28, 2023
Written by Konstantin Gizdarski and Martin Liu at Lyft. In early 2022, Lyft already had a comprehensive Machine Learning Platform called LyftLearn composed of model serving , training , CI/CD, feature serving , and model monitoring systems. On the real-time front, LyftLearn supported real-time inference and input feature validation. However, streaming data was not supported as a first-class citizen across many of the platform’s systems — such as training, complex monitoring, and others.
KDnuggets
JUNE 15, 2023
Everyone seems to have gone crazy about ChatGPT, which has become a cultural phenomenon. If you’re not on the ChatGPT train yet, this article might help you better understand the context and excitement around this innovation.
Netflix Tech
JUNE 13, 2023
Migrating Critical Traffic At Scale with No Downtime — Part 2 Shyam Gala , Javier Fernandez-Ivern , Anup Rokkam Pratap , Devang Shah Picture yourself enthralled by the latest episode of your beloved Netflix series, delighting in an uninterrupted, high-definition streaming experience. Behind these perfect moments of entertainment is a complex mechanism, with numerous gears and cogs working in harmony.
databricks
JUNE 9, 2023
Today, we are excited to announce the preview of a Hive Metastore (HMS) interface for Databricks Unity Catalog, which allows any software compatible.
Analytics Vidhya
JUNE 24, 2023
Introduction We had an amazing opportunity to learn from Mr. Pavan. He is an experienced data engineer with a passion for problem-solving and a drive for continuous growth. Throughout the conversation, Mr. Pavan shares his journey, inspirations, challenges, and accomplishments. Thus, providing valuable insights into the field of data engineering. As we explore Mr.
Engineering at Meta
JUNE 27, 2023
Every day, thousands of developers at Meta are working in repositories with millions of files. Those developers need tools that help them at every stage of the workflow while working at extreme scale. In this article we’ll go through a few of the tools in the development process. And, as an added bonus, those we talk about below are open source so you can try them yourself.
FreshBI
JUNE 16, 2023
Switching from Tableau to PowerBI is just the first step. At our company, we don't just transition you to a new data visualization tool. We connect you to an entire ecosystem of powerful, user-friendly solutions: the Microsoft Power Platform. Here's how we do it and why it's a game changer. The Starting Point: A Power-Packed Punch The Power Platform is Microsoft's suite of business analytics tools, which includes PowerBI , Power Apps , Power Automate , and Power Virtual Agents.
KDnuggets
JUNE 15, 2023
For an overview of what we believe to be the 10 of the best ChatGPT plugins for data science, check out our latest cheat sheet.
Confluent
JUNE 28, 2023
Get an introduction into the world of events and event-driven architecture in Apache Kafka. Learn what events are and the role they play in event design, event streaming, and event-driven design.
databricks
JUNE 27, 2023
Generative AI will have a transformative impact on every business. Databricks has been pioneering AI innovations for a decade, actively collaborating with thousands.
Analytics Vidhya
JUNE 5, 2023
Introduction Welcome back to the success story interview series with a successful data scientist and our DataHour Speaker, Vidhya Chandrasekaran! In today’s data-driven world, data scientists play a crucial role in helping businesses make informed decisions by analyzing and interpreting data. With their expertise in statistics, machine learning, AI, and programming, they are able to […] The post Data Scientist’s Insights: Strategies for Innovation and Leadership appeared first
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