Maxime Beauchemin

JANUARY 7, 2018

Batch data processing  — historically known as ETL —  is extremely challenging. In this post, we’ll explore how applying the functional programming paradigm to data engineering can bring a lot of clarity to the process. Late arriving facts Late arriving facts can be problematic with a strict immutable data policy.

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Data Engineering Data Engineer Data Process Process 183

DoorDash Engineering

NOVEMBER 21, 2022

While building out DashMart’s internal inventory management system to help DashMart associates manage inventory, the DashMart engineering team came to realize that since the inventory tables were so core and foundational to different operational use cases in a DashMart, some actions or code must be triggered every time the inventory level changes.

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Data Process Process Kafka Database 57

Cloudera

SEPTEMBER 11, 2018

The open data processing pipeline. IoT is expected to generate a volume and variety of data greatly exceeding what is being experienced today, requiring modernization of information infrastructure to realize value. The post Building an Open Data Processing Pipeline for IoT appeared first on Cloudera Blog.

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Data Process Process Building Machine Learning 40

DareData

JULY 5, 2023

Learn how we build data lake infrastructures and help organizations all around the world achieving their data goals. In today's data-driven world, organizations are faced with the challenge of managing and processing large volumes of data efficiently.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

Netflix Tech

OCTOBER 19, 2020

In our previous blog post we introduced Edgar, our troubleshooting tool for streaming sessions. This insight led us to build Edgar: a distributed tracing infrastructure and user experience. Our distributed tracing infrastructure is grouped into three sections: tracer library instrumentation, stream processing, and storage.

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Building Transportation Metadata Java 93

ProjectPro

JANUARY 25, 2022

Here’s What You Need to Know About PySpark This blog will take you through the basics of PySpark, the PySpark architecture, and a few popular PySpark libraries , among other things. Finally, you'll find a list of PySpark projects to help you gain hands-on experience and land an ideal job in Data Science or Big Data.

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Big Data Data Process Process Kafka 52

Confluent

JUNE 18, 2019

Software projects of all sizes and complexities have a common challenge: building a scalable solution for search. Building a resilient and scalable solution is not always easy. It involves many moving parts, from data preparation to building indexing and query pipelines. You might be wondering, is this a good solution?

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Architecture Building Kafka Database-centric 94

Christophe Blefari

APRIL 19, 2024

This blog shows how you can use Gen AI to evaluate inputs like translations with added reasons. How we build Slack AI to be secure and private — How Slack uses VPC and Amazon SageMaker with your data secured and private. — A great blog to answer a great question. This is crazy how Theseus outperform Spark.

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MySQL Data Datasets SQL 130

Data Science Blog: Data Engineering

MAY 20, 2024

CI/CD, a set of processes that help software development teams deliver code changes more frequently and reliably, is part of DevOps. As changes are made, there are automated build processes for detecting code issues. CI/CD for Data Pipelines Data pipelines provide consistency, reduce errors, and increase efficiency.

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Data Pipeline BI Data Lake Data Warehouse 52

Data Engineering Weekly

DECEMBER 10, 2023

RudderStack, one of the leading alternatives to Segment , is the Warehouse Native CDP, built to help data teams deliver value across the entire data activation lifecycle, from collection to unification and activation. I can’t wait for someone to build a bot around it!!! Visit rudderstack.com to learn more.

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Data Engineering Data Engineer Engineering Metadata 76

ProjectPro

DECEMBER 7, 2021

Table of Contents The Ultimate Guide to Build a Data Analyst Portfolio Data Analyst Portfolio Platforms Skills to Showcase On Your Data Analyst Portfolio What to Include in Your Data Analyst Portfolio? Data Analyst Portfolio Examples - What You Can Learn From Them? Wrapping Up.

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Portfolio Building Data Mining Data Analysis 52

Cloudera

MAY 28, 2024

This form of architecture can handle data in all forms—structured, semi-structured, unstructured—blending capabilities from data warehouses and data lakes into data lakehouses. Learn more about how Cloudera can help you achieve a modern data architecture.

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Data Architecture Architecture Data Lake Data Warehouse 75

Team Data Science

MAY 10, 2020

What's Next I'll be documenting how I build this setup in the AWS console (with screenshots). Kafka, while not in the top 5 most in demand skills, was still the most requested buffer technology requested which makes it worthwhile to include it. The remaining tech (stages 3, 4, 7 and 8) are all AWS technologies.

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Data Pipeline Data Ingestion AWS Kafka 130

Cloudera

OCTOBER 16, 2023

In this multi-part blog post, we’re going to show you how to use the latest Cloudera Iceberg innovation to build an Open Data Lakehouse on a private cloud. to stream ingest data sets to Iceberg. Stay tuned for part two, Data Processing with Apache Spark. and follow our Getting Started blog series.

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Cloud Kafka SQL Data 78

Engineering at Meta

MAY 22, 2024

To efficiently process data generated by billions of people, Data Infrastructure teams at Meta have built a variety of data management systems over the last decade, each targeted to a somewhat specific data processing task.

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Data Management Management Data SQL 86

Data Engineering Weekly

APRIL 28, 2024

Intuit: The Data Mesh Strategy Behind Intuit’s Global Financial Technology Platform The Data Product Builder platform is becoming increasingly important in enterprise data engineering. It offers more targeted and customized data asset building than the general-purpose data stack.

Data Engineering 52

Data Engineering Data Engineer Engineering Hospitality 52

Data Engineering Weekly

SEPTEMBER 24, 2023

Data Engineering Weekly Is Brought to You by RudderStack 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. The blog specifically focuses on the following areas of LLM implementations.

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Data Engineering Data Engineer Engineering Kafka 67

Cloudera

SEPTEMBER 26, 2023

Organizations increasingly rely on streaming data sources not only to bring data into the enterprise but also to perform streaming analytics that accelerate the process of being able to get value from the data early in its lifecycle.

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Kafka Technology IT Government 92

Data Engineering Weekly

MAY 16, 2023

In the second part, we will focus on architectural patterns to implement data quality from a data contract perspective. Why is Data Quality Expensive? I won’t bore you with the importance of data quality in the blog. Let’s talk about the data processing types.

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Engineering Kafka Data Pipeline Data Warehouse 110

Tweag

MAY 20, 2024

In this blog post, we’ll present a proof-of-concept of work-dAIgest , show you what’s under the hood and finally touch quickly on a couple lessons we learned during this short, but fun project. Even for small projects, data science and engineering is still something you have to do yourself, and we doubt that this will change any time soon.

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AWS Python Project Data Science 60

Towards Data Science

APRIL 30, 2024

Balancing correctness, latency, and cost in unbounded data processing Image created by the author. Intro Google Dataflow is a fully managed data processing service that provides serverless unified stream and batch data processing. Apache Beam lets users define processing logic based on the Dataflow model.

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Google Cloud Process Cloud Lambda Architecture 61

Data Engineering Weekly

DECEMBER 3, 2023

Github writes an excellent blog to capture the current state of the LLM integration architecture. link] Microsoft: Generative AI for Beginners Understanding Gen-AI becomes a mandatory skill for application developers and data engineers. I experienced similar drawbacks to what Lyft is talking about in Druid.

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Data Engineering Data Engineer Engineering Bytes 70

Workfall

JUNE 27, 2023

It means that there is a high risk of data loss but Apache Kafka solves this because it is distributed and can easily scale horizontally and other servers can take over the workload seamlessly. Kafka can also be used to stream data from IoT devices or sensors. Let’s get started!

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Kafka Architecture AWS Transportation 75

Data Engineering Weekly

JULY 30, 2023

Data Engineering Weekly Is Brought to You by RudderStack 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. We handle Petabytes of data!!! All our data is in S3!!! If you’re a.

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

Snowflake

MAY 23, 2024

Welcome to Snowflake’s Startup Spotlight, where we ask startup founders about the problems they’re solving, the apps they’re building and the lessons they’ve learned during their startup journey. One last question: What advice would you give to other entrepreneurs thinking about building apps on Snowflake?

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Data Pipeline Raw Data Data Schemas Technology 85

Databand.ai

AUGUST 30, 2023

Slow data processing: Due to the manual nature of many data workflows in legacy architectures, data processing can be time-consuming and resource-intensive. A DataOps architecture must consider the performance, scalability, and cost implications of the chosen data storage platform.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Databand.ai

JUNE 8, 2023

Better decision-making: Real-time insights into data processing allow for more informed decisions about resource allocation or process optimization. 5 Things You Must Monitor in a Data Pipeline To achieve observability, track specific metrics and events that provide insights into your pipeline’s functionality.

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Data Pipeline Bytes Raw Data Data Collection 52

Data Engineering Weekly

SEPTEMBER 11, 2023

Data Engineering Weekly Is Brought to You by RudderStack 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. It is an excellent read for anyone thinking of building LLM-powered product features.

Data Engineering 62

Data Engineering Data Engineer Engineering Kafka 62

Databand.ai

AUGUST 30, 2023

DataOps , short for data operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data processes across an organization. Accelerated Data Analytics DataOps tools help automate and streamline various data processes, leading to faster and more efficient data analytics.

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Data Cleanse Data Pipeline Data Ingestion Data Validation 52

LinkedIn Engineering

OCTOBER 19, 2023

Authors: Bingfeng Xia and Xinyu Liu Background At LinkedIn, Apache Beam plays a pivotal role in stream processing infrastructures that process over 4 trillion events daily through more than 3,000 pipelines across multiple production data centers.

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Process Lambda Architecture Kafka Machine Learning 119

Cloudyard

APRIL 1, 2024

This blog post introduces a solution for automated warehouse size change monitoring and email alerts using Snowflake Streams and Tasks. Imagine you’re a data analyst managing a busy Snowflake account. You rely on a designated warehouse to handle your data processing needs.

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Data Pipeline Utilities Coding Designing 52

Data Engineering Weekly

NOVEMBER 20, 2022

[link] The short YouTube video gives a nice overview of the Data Cards. We often think of AI/ ML as a complex data processing problem, but it doesn’t make any use until it is exposed to an end user or an application. The most critical work of data happens outside the data team. Not Endless DAGs!

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

Pinterest Engineering

OCTOBER 17, 2023

Charles Wu | Software Engineer; Isabel Tallam | Software Engineer; Kapil Bajaj | Engineering Manager Overview In this blog, we present a pragmatic way of integrating analytics, written in Python, with our distributed anomaly detection platform, written in Java. We have also thought of building a RESTful API endpoint in Python.

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Algorithm Java Python Software Engineer 87

Workfall

JULY 18, 2023

But then, a game-changer emerged – DBT (Data Build Tool). With DBT’s materializations, our data transformations underwent a magical transformation themselves. In this blog, we’ll whisk you away on an enchanting journey through DBT materializations. In this blog, we will cover: What is DBT?

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Datasets Entertainment Data Workflow Data 77

Data Engineering Weekly

FEBRUARY 25, 2024

If you want to shape the future of data in Europe, join our core working group. Let's build this together! Just after the DEWCon conference, we heard the data practitioners want similar events in their cities to increase knowledge sharing. Fill out the form below.

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Data Engineering Data Engineer Engineering Kafka 62

Data Engineering Weekly

JUNE 18, 2023

Data management is critical for any organization to succeed in this AI world. The blog narrates LLM training options, Storage & retrieval, and the value chain to use LLM in your private data. Join Monte Carlo, dbt, and Shiftkey's VP of Data & Analytics, John Steinmetz. I’m super thrilled to see the blog.

Data Engineering 52

Data Engineering Data Engineer Engineering MySQL 52

Cloudera

JULY 19, 2023

Introduction Ozone is an Apache Software Foundation project to build a distributed storage platform that caters to the demanding performance needs of analytical workloads, content distribution, and object storage use cases. As Ozone scales to exabytes of data, it is important to ensure that Ozone Manager can perform at scale.

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Management Metadata Datasets Architecture 70