June, 2023

article thumbnail

Generative AI and the Future of Data Engineering

Monte Carlo

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?

article thumbnail

Modern Data Engineering with MAGE: Empowering Efficient Data Processing

Analytics Vidhya

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.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

An educational side project

The Pragmatic Engineer

👋 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.

Education 363
article thumbnail

Seamless SQL And Python Transformations For Data Engineers And Analysts With SQLMesh

Data Engineering Podcast

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.

article thumbnail

15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

article thumbnail

A Comprehensive Guide to Convolutional Neural Networks

KDnuggets

Artificial Intelligence has been witnessing monumental growth in bridging the gap between the capabilities of humans and machines. Researchers and enthusiasts alike, work on numerous aspects of the field to make amazing things happen. One of many such areas is the domain of Computer Vision.

article thumbnail

Migrating Netflix to GraphQL Safely

Netflix Tech

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.

Utilities 142

More Trending

article thumbnail

The Journey of a Senior Data Scientist and Machine Learning Engineer at Spice Money

Analytics Vidhya

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.

article thumbnail

Google Domains to shut down

The Pragmatic Engineer

👋 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.

article thumbnail

Introducing English as the New Programming Language for Apache Spark

databricks

Introduction We are thrilled to unveil the English SDK for Apache Spark, a transformative tool designed to enrich your Spark experience. Apache Spark™.

article thumbnail

AI: Large Language & Visual Models

KDnuggets

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.

Data 154
article thumbnail

Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

article thumbnail

Ensuring the Successful Launch of Ads on Netflix

Netflix Tech

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.

Algorithm 138
article thumbnail

New Approaches For Detecting AI-Generated Profile Photos

LinkedIn Engineering

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.

Media 132
article thumbnail

What Data Engineers Really Do?

Analytics Vidhya

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.

article thumbnail

Inside Agoda’s Private Cloud - Exclusive

The Pragmatic Engineer

👋 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.

Cloud 197
article thumbnail

How to Drive Cost Savings, Efficiency Gains, and Sustainability Wins with MES

Speaker: Nikhil Joshi, Founder & President of Snic Solutions

Is your manufacturing operation reaching its efficiency potential? A Manufacturing Execution System (MES) could be the game-changer, helping you reduce waste, cut costs, and lower your carbon footprint. Join Nikhil Joshi, Founder & President of Snic Solutions, in this value-packed webinar as he breaks down how MES can drive operational excellence and sustainability.

article thumbnail

Gotchas of Streaming Pipelines: Profiling & Performance Improvements

Lyft Engineering

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.

Utilities 123
article thumbnail

5 Free Julia Books For Data Science

KDnuggets

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.

article thumbnail

Native Frame Rate Playback

Netflix Tech

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.

Algorithm 124
article thumbnail

Meta developer tools: Working at scale

Engineering at Meta

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.

Java 122
article thumbnail

Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

article thumbnail

Top 10 Powerful Data Modeling Tools to Know in 2023

Analytics Vidhya

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.

Database 211
article thumbnail

An explosion in software engineers using AI coding tools?

The Pragmatic Engineer

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.

article thumbnail

Building Real-time Machine Learning Foundations at Lyft

Lyft Engineering

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.

article thumbnail

10 ChatGPT Plugins for Data Science Cheat Sheet

KDnuggets

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.

article thumbnail

The Ultimate Guide To Data-Driven Construction: Optimize Projects, Reduce Risks, & Boost Innovation

Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network

In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.

article thumbnail

Migrating Critical Traffic At Scale with No Downtime?—?Part 2

Netflix Tech

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.

Systems 113
article thumbnail

Declarative Data Pipelines with Hoptimator

LinkedIn Engineering

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.

article thumbnail

Mr. Pavan’s Data Engineering Journey Drives Business Success

Analytics Vidhya

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.

article thumbnail

Should you optimize for all-cash compensation, if possible?

The Pragmatic Engineer

👋 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 high-growth startups through the lens of engineering managers and senior engineers. In this article, we cover one out of four topics from today’s subscriber-only The Scoop issue. If you’re not a full subscriber yet, you missed this week’s deep-dive on Shopify’s leveling split.

article thumbnail

Driving Responsible Innovation: How to Navigate AI Governance & Data Privacy

Speaker: Aindra Misra, Senior Manager, Product Management (Data, ML, and Cloud Infrastructure) at BILL

Join us for an insightful webinar that explores the critical intersection of data privacy and AI governance. In today’s rapidly evolving tech landscape, building robust governance frameworks is essential to fostering innovation while staying compliant with regulations. Our expert speaker, Aindra Misra, will guide you through best practices for ensuring data protection while leveraging AI capabilities.

article thumbnail

Extending Databricks Unity Catalog with an Open Apache Hive Metastore API

databricks

Today, we are excited to announce the preview of a Hive Metastore (HMS) interface for Databricks Unity Catalog, which allows any software compatible.

126
126
article thumbnail

Your Ultimate Guide to Chat GPT and Other Abbreviations

KDnuggets

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.

135
135
article thumbnail

Announcing halide-haskell - a Haskell interface for the Halide image and array processing language

Tweag

The availability of deep learning frameworks like PyTorch or JAX has revolutionized array processing, regardless of whether one is working on machine learning tasks or other numerical algorithms. The Haskell library ecosystem has been catching up as well, and there are now multiple good array libraries. However, writing high-performance array processing code in Haskell is still a non-trivial endeavor.

Process 112
article thumbnail

What Is an Event in the Apache Kafka Ecosystem?

Confluent

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.

Kafka 111
article thumbnail

What Is Entity Resolution? How It Works & Why It Matters

Entity Resolution Sometimes referred to as data matching or fuzzy matching, entity resolution, is critical for data quality, analytics, graph visualization and AI. Learn what entity resolution is, why it matters, how it works and its benefits. Advanced entity resolution using AI is crucial because it efficiently and easily solves many of today’s data quality and analytics problems.