Christophe Blefari

JUNE 15, 2024

More than 5000 members subscribed to the newsletter and the blog generated almost 100k unique visitors. Recently a lot of people subscribed and never received a Data News, I want to give you a warm welcome and this edition marks the journey we embark together, you will enjoy what's coming next, I'm sure.

Data 100

Data Bytes Metadata SQL 100

LinkedIn Engineering

JANUARY 19, 2024

Figure 1: Talent pool report for recruiters - LinkedIn Talent Insights During mergers and acquisitions, the source company’s user licenses and data are transferred to the acquiring company. This multi-entity handover process involves huge amounts of data updating and cloning. A typical merger & acquisition scenario.

Recruitment 88

Recruitment Data Process Process Kafka 88

LinkedIn Engineering

JUNE 15, 2023

However, we found that many of our workloads were bottlenecked by reading multiple terabytes of input data. To remove this bottleneck, we built AvroTensorDataset , a TensorFlow dataset for reading, parsing, and processing Avro data. Avro serializes or deserializes data based on data types provided in the schema.

Datasets 102

Datasets Bytes Process Data Ingestion 102

Cloudera

MARCH 2, 2023

Recently, we announced enhanced multi-function analytics support in Cloudera Data Platform (CDP) with Apache Iceberg. Iceberg is a high-performance open table format for huge analytic data sets. This enables you to maximize utilization of streaming data at scale. Currently, Iceberg support in CSP is in technical preview mode.

Process 113

Process SQL Kafka Database 113

Netflix Tech

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty At Netflix, our Membership and Finance Data Engineering team harnesses diverse data related to plans, pricing, membership life cycle, and revenue to fuel analytics, power various dashboards, and make data-informed decisions. We expect complete and accurate data at the end of each run.

Data Engineering 105

Data Engineering Data Engineer Engineering Metadata 105

Data Science Blog: Data Engineering

MAY 20, 2024

Continuous Integration and Continuous Delivery (CI/CD) for Data Pipelines: It is a Game-Changer with AnalyticsCreator! The need for efficient and reliable data pipelines is paramount in data science and data engineering. As changes are made, there are automated build processes for detecting code issues.

Data Pipeline 52

Data Pipeline BI Data Lake Data Warehouse 52

Snowflake

DECEMBER 4, 2023

Apache Iceberg’s ecosystem of diverse adopters, contributors and commercial support continues to grow, establishing itself as the industry standard table format for an open data lakehouse architecture. Are you using Snowflake on AWS and already using Glue Data Catalog for your data lake?

Building 95

Building Metadata Cloud Storage AWS 95

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. The greater the claim made using analytics, the greater the scrutiny on the process should be.

Data Engineering 183

Data Engineering Data Engineer Data Process Process 183

Data Engineering Podcast

FEBRUARY 26, 2023

Summary There has been a lot of discussion about the practical application of data mesh and how to implement it in an organization. Jean-Georges Perrin was tasked with designing a new data platform implementation at PayPal and wound up building a data mesh. Is a data mesh ever "done"? We feel your pain.

Building 147

Building Metadata Machine Learning Data Integration 147

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. Lackluster AI/ML results often stem from poor data quality. Visit rudderstack.com to learn more.

Data Engineering 76

Data Engineering Data Engineer Engineering Metadata 76

Christophe Blefari

JANUARY 20, 2024

Learn data engineering, all the references ( credits ) This is a special edition of the Data News. But right now I'm in holidays finishing a hiking week in Corsica 🥾 So I wrote this special edition about: how to learn data engineering in 2024. The idea is to create a living reference about Data Engineering.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

LinkedIn Engineering

MARCH 23, 2023

Co-Authors: Yuhong Cheng , Shangjin Zhang , Xinyu Liu, and Yi Pan Efficient data processing is crucial in reducing learning curves, simplifying maintenance efforts, and decreasing operational complexity. By unifying these pipelines, we have saved 94% of processing time. Samza , Spark and Apache Flink ).

Process 97

Process Lambda Architecture Kafka Datasets 97

Netflix Tech

MARCH 10, 2023

This platform has evolved from supporting studio applications to data science applications, machine-learning applications to discover the assets metadata, and build various data facts. During this evolution, quite often we receive requests to update the existing assets metadata or add new metadata for the new features added.

Management 94

Management Kafka Metadata Media 94

Databand.ai

AUGUST 30, 2023

8 Data Quality Monitoring Techniques & Metrics to Watch Niv Sluzki August 30, 2023 What Is Data Quality Monitoring? Data quality monitoring refers to the assessment, measurement, and management of an organization’s data in terms of accuracy, consistency, and reliability.

Data Cleanse 52

Data Cleanse Metadata High Quality Data Datasets 52

Snowflake

NOVEMBER 2, 2023

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. These patterns include both centralized storage patterns like data warehouse , data lake and data lakehouse , and distributed patterns such as data mesh.

Data Lake 90

Data Lake Data Warehouse Cloud Unstructured Data 90

Airbnb Tech

NOVEMBER 28, 2023

By: Clark Wright Introduction These days, as the volume of data collected by companies grows exponentially, we’re all realizing that more data is not always better. In fact, more data, especially if you can’t rely on its quality, can hinder a company by slowing down decision-making or causing poor decisions.

Data Warehouse 98

Data Warehouse Metadata Data Certification 98

Netflix Tech

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty This blog post will cover how Psyberg helps automate the end-to-end catchup of different pipelines, including dimension tables. In the previous installments of this series, we introduced Psyberg and delved into its core operational modes: Stateless and Stateful Data Processing.

Metadata 97

Metadata Data Pipeline Scala Data Workflow 97

Rockset

MARCH 18, 2024

Flink is one of the most popular stream processing technologies, ranked as a top five Apache project and backed by a diverse committer community including Alibaba and Apple. It powers steam processing at many companies including Uber, Netflix, and Linkedin.

Cloud 64

Cloud Building Metadata Kafka 64

Snowflake

AUGUST 22, 2023

One way Honeywell “makes the future” is by developing innovative data products. Snowflake’s World of Data Collaboration, the theme of Snowflake Summit , was a world of data products—extending beyond data to include AI models and applications. A data product is built to be used and reused.

Metadata 73

Metadata Data AWS Business Analyst 73

Lyft Engineering

OCTOBER 3, 2023

High-quality data is necessary for the success of every data-driven company. It is now the norm for tech companies to have a well-developed data platform. This makes it easy for engineers to generate, transform, store, and analyze data at the petabyte scale. What and Where is Data Quality?

Big Data 85

Big Data Metadata Data Warehouse Data 85

LinkedIn Engineering

JULY 19, 2023

Co-Authors: Sumedh Sakdeo , Lei Sun , Sushant Raikar , Stanislav Pak , and Abhishek Nath Introduction At LinkedIn, we build and operate an open source data lakehouse deployment to power Analytics and Machine Learning workloads. While functional, our current setup for managing tables is fragmented.

Big Data 78

Big Data Data Management Management Metadata 78

Databand.ai

JULY 19, 2023

Data Lineage Tools: Key Capabilities and 5 Notable Solutions Ryan Yackel July 19, 2023 What Are Data Lineage Tools? Data lineage tools provide a visual representation of your data’s journey across multiple systems and transformations. Data lineage tools are not a new concept.

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52

Data Engineering Podcast

MARCH 25, 2023

Summary The promise of streaming data is that it allows you to react to new information as it happens, rather than introducing latency by batching records together. As your business adapts, so should your data. RudderStack Transformations lets you customize your event data in real-time with your own JavaScript or Python code.

MySQL 130

MySQL Python Architecture Machine Learning 130

Engineering at Meta

OCTOBER 31, 2023

Meta’s Systematic Code and Asset Removal Framework (SCARF) has a subsystem for identifying and removing unused data types. SCARF scans production data systems to identify tables or assets that are unused and safely removes them. This process can be unexpectedly difficult, because large software systems are inevitably interconnected.

Data 98

Data Metadata Coding Relational Database 98

Data Engineering Weekly

MAY 16, 2023

In the first part of this series, we talked about design patterns for data creation and the pros & cons of each system from the data contract perspective. In the second part, we will focus on architectural patterns to implement data quality from a data contract perspective. Why is Data Quality Expensive?

Engineering 110

Engineering Kafka Data Pipeline Data Warehouse 110

LinkedIn Engineering

DECEMBER 19, 2023

Co-authors: Arjun Mohnot , Jenchang Ho , Anthony Quigley , Xing Lin , Anil Alluri , Michael Kuchenbecker LinkedIn operates one of the world’s largest Apache Hadoop big data clusters. Historically, deploying code changes to Hadoop big data clusters has been complex.

Big Data 92

Big Data Hadoop Metadata Data 92

Towards Data Science

MAY 19, 2023

Data Entropy — More Data, More Problems? How to navigate and embrace complexity in a modern data organisation. Business users are unable to find and access data assets critical to their workflows. Data engineers spend countless hours troubleshooting broken pipelines. Every “minor” change upstream results in mayhem.

Pipeline-centric 103

Pipeline-centric Data Software Engineer Software Engineering 103

Snowflake

JUNE 4, 2024

Snowflake provides a strong data foundation anchored on unified data, optimal TCO and universal governance. The Snowflake platform eliminates silos to enable any architectural pattern, while supporting all data types and workloads. These capabilities can even be extended to Iceberg tables created by other engines.

Government 80

Government Data Ingestion Data PostgreSQL 80

Data Engineering Weekly

MARCH 10, 2024

Editor’s Note: Chennai Meetup Wrap-Up & Preparation work started for DEWCon I am so grateful for the enthusiastic participants who made our Chennai Data Heroes- Community for Data Folks meetup vibrant! Big thanks to our insightful speakers, Hareshkumar Selvakumar - Talks about his work on Data Products for PayPal.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

RandomTrees

FEBRUARY 6, 2024

Data engineering, the practice of collecting, transforming, and organizing data for analysis, is poised for a significant transformation with the advent of Generative Artificial Intelligence (Gen AI). Ingestion: The Art of Data Assimilation: Ensuring the digital document accurately reflects the original handwritten material.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Snowflake

JUNE 5, 2024

With the rapid adoption of generative AI (gen AI) and large language models (LLMs), organizations are racing to unlock as much business value as possible from their content across data, apps and models. Snowflake Horizon continues to innovate, allowing data teams to now collaborate in a governed way within their organization.

Government 97

Government Accessible Accessibility Metadata 97

Tweag

APRIL 19, 2023

To allow innovation in medical imaging with AI, we need efficient and affordable ways to store and process these WSIs at scale. OpenSlide test data: CMU-1.tiff Marini et al This results in a very large amount of data for a single slide, often a few gigabytes per slide, which is all stored in one big file.

Medical 59

Medical Process Cloud Bytes 59

Databand.ai

AUGUST 30, 2023

Building a Winning Data Quality Strategy: Step by Step Eitan Chazbani August 30, 2023 What Is a Data Quality Strategy? A data quality strategy details the processes, tools, and techniques employed to ensure your company’s data is accurate, consistent, complete, and up-to-date.

Building 52

Building Data Cleanse Data Governance Datasets 52

Cloudera

AUGUST 26, 2021

Ozone natively provides Amazon S3 and Hadoop Filesystem compatible endpoints in addition to its own native object store API endpoint and is designed to work seamlessly with enterprise scale data warehousing, machine learning and streaming workloads. Learn more about the impacts of global data sharing in this blog, The Ethics of Data Exchange.

Data Science 113

Data Science Cloud Hadoop Metadata 113

Workfall

JUNE 12, 2023

In this dynamic realm of data engineering, a monumental challenge takes centre stage: efficiently managing the ever-changing tides of real-time data. Data, the lifeblood of organisations, holds the key to unlocking untapped potential and propelling businesses forward. In this blog, we will cover: What Is CDC and Its Benefits?

Telecommunication 80

Telecommunication Metadata Healthcare Finance 80

Cloudera

SEPTEMBER 29, 2022

Data teams have the impossible task of delivering everything (data and workloads) everywhere (on premise and in all clouds) all at once (with little to no latency). Each of these trends claim to be complete models for their data architectures to solve the “everything everywhere all at once” problem. Data mesh defined.

Architecture 74

Architecture Data Architecture Metadata Data Warehouse 74

Data Engineering Weekly

JULY 23, 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. Overall an exciting time for a data contract in 2024. See how it works today.

Data Engineering 52

Data Engineering Data Engineer Engineering Deep Learning 52