Data Engineering Podcast

DECEMBER 3, 2023

Data transfer systems are a critical component of data enablement, and building them to support large volumes of information is a complex endeavor. RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles so you can quickly ship actionable, enriched data to every downstream team.

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Systems Designing Data Lake SQL 130

Start Data Engineering

MAY 28, 2024

Building efficient data pipelines with DuckDB 4.1. Distributed systems are scalable, resilient to failures, & designed for high availability 4.5. Introduction 2. Project demo 3. Use DuckDB to process data, not for multiple users to access data 4.2. Cost calculation: DuckDB + Ephemeral VMs = dirt cheap data processing 4.3.

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Data Pipeline Python Building Data 219

Confluent

FEBRUARY 24, 2022

A few years ago I helped build an event-driven system for gym bookings. The pitch was that we were building a better experience for both the gym members booking different […].

Systems 124

Systems Building Data 124

databricks

JUNE 12, 2024

Over the last year, we have seen a surge of commercial and open-source foundation models showing strong reasoning abilities on general knowledge tasks.

Systems 144

Systems Building Data Science Data 144

Data Engineering Podcast

MAY 18, 2024

Summary The purpose of business intelligence systems is to allow anyone in the business to access and decode data to help them make informed decisions. The team at Zenlytic have leaned on the promise of large language models to build an AI agent that lets you converse with your data. Are data agents harder to build?

Building 278

Building Data Lake High Quality Data Business Intelligence 278

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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Building Portfolio Utilities Data Storage 145

Monte Carlo

FEBRUARY 23, 2024

And this renewed focus on data quality is bringing much needed visibility into the health of technical systems. In addition, Snow f lake Cortex enables organizations to quickly analyze data and build AI applications directly within Snowflake. The old familiar adage rings as true as ever when it comes to GenAI: garbage in, garbage out.

Systems 64

Systems Building Retail Data Lake 64

Data Engineering Podcast

JANUARY 21, 2019

Summary Building internal expertise around big data in a large organization is a major competitive advantage. They discuss the challenges of being at global scale from the start, hiring and training talented engineers, prototyping and deploying new systems in the cloud, and what they have learned in the process.

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Big Data Systems Building Hadoop 100

Data Engineering Podcast

DECEMBER 19, 2021

Summary Building a well managed data ecosystem for your organization requires a holistic view of all of the producers, consumers, and processors of information. The team at Metaphor are building a fully connected metadata layer to provide both technical and social intelligence about your data. No more scripts, just SQL.

Systems 100

Systems Building Metadata Data Warehouse 100

Lyft Engineering

APRIL 25, 2023

Building a large scale unsupervised model anomaly detection system — Part 2 Building ML Models with Observability at Scale By Rajeev Prabhakar , Han Wang , Anindya Saha Photo by Octavian Rosca on Unsplash In our previous blog we discussed the different challenges we faced for model monitoring and our strategy for addressing some of these problems.

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Systems Building Machine Learning Datasets 76

Data Engineering Podcast

JULY 27, 2020

Summary A majority of the scalable data processing platforms that we rely on are built as distributed systems. Kyle Kingsbury created the Jepsen framework for testing the guarantees of distributed data processing systems and identifying when and why they break. What are the pros and cons of using Clojure for building Jepsen?

Systems 100

Systems Building Scala Java 100

Knowledge Hut

FEBRUARY 1, 2024

Not only could this recommendation system save time browsing through lists of movies, it can also give more personalized results so users don’t feel overwhelmed by too many options. What are Movie Recommendation Systems? Recommender systems have two main categories: content-based & collaborative filtering.

Systems 98

Systems Entertainment Algorithm Datasets 98

Data Engineering Podcast

SEPTEMBER 17, 2023

Summary A significant amount of time in data engineering is dedicated to building connections and semantic meaning around pieces of information. In this episode Brian Platz explains how JSON-LD can be used as a shared representation of linked data for building semantic data products. Hex brings everything together.

Building 189

Building SQL BI Python 189

Netflix Tech

MARCH 7, 2024

The Machine Learning Platform (MLP) team at Netflix provides an entire ecosystem of tools around Metaflow , an open source machine learning infrastructure framework we started, to empower data scientists and machine learning practitioners to build and manage a variety of ML systems. ETL workflows), as well as downstream (e.g.

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Systems Media Machine Learning Data Warehouse 93

Data Engineering Podcast

MAY 5, 2024

In this episode he explains his approach to building AI in a more human-like fashion and the emphasis on learning rather than statistical prediction. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Dagster offers a new approach to building and running data platforms and data pipelines.

Building 147

Building Data Lake High Quality Data Machine Learning 147

Rockset

MARCH 28, 2024

Overview In this guide, you will: Gain a high-level understanding of vectors, embeddings, vector search, and vector databases, which will clarify the concepts we will build upon. Build a dynamic web application using vanilla CSS, HTML, JavaScript, and Flask, seamlessly integrating with the Rockset API and the OpenAI API.

Systems 52

Systems Building Database Utilities 52

Monte Carlo

FEBRUARY 23, 2024

And this renewed focus on data quality is bringing much needed visibility into the health of technical systems. In addition, Snow f lake Cortex enables organizations to quickly analyze data and build AI applications directly within Snowflake. The old familiar adage rings as true as ever when it comes to GenAI: garbage in, garbage out.

Systems 52

Systems Building Retail Data Lake 52

Netflix Tech

FEBRUARY 18, 2022

To this end, we developed a Rapid Event Notification System (RENO) to support use cases that require server initiated communication with devices in a scalable and extensible manner. In this blog post, we will give an overview of the Rapid Event Notification System at Netflix and share some of the learnings we gained along the way.

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Systems Architecture Portfolio Designing 133

Teradata

MAY 5, 2020

This post describes an analytics prototype to build an early warning system for COVID-19. Advanced analytics & AI techniques can help in curtailing the COVID-19 pandemic.

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Systems Building 118

Data Engineering Podcast

APRIL 28, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Dagster offers a new approach to building and running data platforms and data pipelines. Go to dataengineeringpodcast.com/dagster today to get started. Your first 30 days are free! Data lakes are notoriously complex.

Building 147

Building Data Lake High Quality Data Machine Learning 147

Data Engineering Podcast

SEPTEMBER 11, 2022

Summary Data engineering systems are complex and interconnected with myriad and often opaque chains of dependencies. Prefect is the modern Dataflow Automation platform for the modern data stack, empowering data practitioners to build, run and monitor robust pipelines at scale. Can you describe what Schemata is and the story behind it?

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Systems Metadata Building MongoDB 100

Monte Carlo

AUGUST 17, 2022

Over the years, I’ve helped companies of all sizes build and maintain data systems—from my days as a data engineer at Facebook to my current role as an end-to-end data solutions consultant. It’s never too early to start building reliability into your data system. The stakes also get higher.

Systems 52

Systems Building Data Data Engineer 52

Precisely

NOVEMBER 7, 2024

Key Takeaways: In the face of ransomware attacks, a resilience strategy for IBM i systems must include measures for prevention, detection, and recovery. No platform is immune, not even the reliable and secure IBM i systems. So, how can you keep your IBM i systems resilient even as ransomware risks are on the rise?

Systems 59

Systems Accessible Accessibility Programming 59

Knowledge Hut

MARCH 22, 2024

I have comprehensively analyzed the area of physical security, particularly the ongoing discussion surrounding fail safe vs fail-safe secure electric strike locking systems. These two distinct approaches offer unique strategies for securing buildings and valuables. What are Fail-Safe Door Locks?

Systems 105

Systems Electronics Hospitality Architecture 105

Knowledge Hut

MAY 6, 2024

Applying systems thinking views a system as a set of interconnected and interdependent components defined by its limits and more than the sum of their parts (subsystems). When one component of a system is altered, the effects frequently spread across the entire system. are the main objectives of systems thinking.

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Systems Transportation Certification Healthcare 98

Data Engineering Podcast

FEBRUARY 26, 2023

Jean-Georges Perrin was tasked with designing a new data platform implementation at PayPal and wound up building a data mesh. It's supposed to make building smarter, faster, and more flexible data infrastructures a breeze. What are the technical systems that you are relying on to power the different data domains?

Building 147

Building Machine Learning Metadata Data Integration 147

phData: Data Engineering

NOVEMBER 8, 2024

The world we live in today presents larger datasets, more complex data, and diverse needs, all of which call for efficient, scalable data systems. These systems are built on open standards and offer immense analytical and transactional processing flexibility. These formats are transforming how organizations manage large datasets.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

KDnuggets

FEBRUARY 9, 2023

I built a recommender system for Amazon’s electronics category.

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Systems Electronics Python Building 106

Data Engineering Podcast

OCTOBER 15, 2023

Summary Building streaming applications has gotten substantially easier over the past several years. Decodable was built with a mission of eliminating all of the painful aspects of developing and deploying stream processing systems for engineering teams. How can you get the best results for your use case? Rudderstack : ![Rudderstack]([link]

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Process Building SQL BI 182

Lyft Engineering

APRIL 3, 2023

This blog post focuses on the scope and the goals of the recommendation system, and explores some of the most recent changes the Rider team has made to better serve Lyft’s riders. Introduction: Scope of the Recommendation System The recommendation system covers user experiences throughout the ride journey.

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Systems Pipeline-centric Machine Learning Transportation 87

Pinterest Engineering

JANUARY 10, 2023

Liang Ma | Software Engineer, Core Eng; Wei Zhu | Software Engineer, Observability In early 2020, during a critical iOS out of memory incident (we have a blogpost for that), we realized that we didn’t have much visibility of how the app is running or a good system to look up for monitoring and troubleshooting.

Systems 57

Systems Building Software Engineering Software Engineer 57

Zalando Engineering

MAY 13, 2024

As a design system evolves alongside with the brand it represents, there are often multiple occasions when a need to introduce variations arises. The previous article on this blog gives a wider overview of the Zalando Design System. The previous article on this blog gives a wider overview of the Zalando Design System.

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Designing Systems Architecture Coding 59

Rockset

SEPTEMBER 2, 2022

I recently had the good fortune to host a small-group discussion on personalization and recommendation systems with two technical experts with years of experience at FAANG and other web-scale companies. Nikhil Garg is CEO and co-founder of Fennel AI , a startup working on building the future of real-time machine learning infrastructure.

Systems 52

Systems Building Machine Learning NoSQL 52

Data Engineering Podcast

JANUARY 28, 2024

Summary Monitoring and auditing IT systems for security events requires the ability to quickly analyze massive volumes of unstructured log data. The majority of products that are available either require too much effort to structure the logs, or aren't fast enough for interactive use cases.

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Data Lake Building High Quality Data AWS 147