Netflix Tech

FEBRUARY 14, 2025

It requires a state-of-the-art system that can track and process these impressions while maintaining a detailed history of each profiles exposure. This nuanced integration of data and technology empowers us to offer bespoke content recommendations.

Kafka 67

Kafka Datasets Utilities Metadata 67

Data Engineering Weekly

MARCH 16, 2025

link] AWS: An introduction to preparing your own dataset for LLM training Everything in AI eventually comes down to the quality and completeness of your internal data. link] Apache Arrow: Data Wants to Be Free: Fast Data Exchange with Apache Arrow Data exchange is critical when discussing AI and the need for data quality.

Data Engineering 57

Data Engineering Data Engineer Engineering Amazon Web Services 57

Ascend.io

OCTOBER 28, 2024

Data transformation helps make sense of the chaos, acting as the bridge between unprocessed data and actionable intelligence. You might even think of effective data transformation like a powerful magnet that draws the needle from the stack, leaving the hay behind.

Raw Data 52

Raw Data Datasets Aggregated Data Data Pipeline 52

LinkedIn Engineering

JANUARY 19, 2024

Data consistency, feature reliability, processing scalability, and end-to-end observability are key drivers to ensuring business as usual (zero disruptions) and a cohesive customer experience. With our new data processing framework, we were able to observe a multitude of benefits, including 99.9%

Recruitment 88

Recruitment Data Process Process Kafka 88

Pinterest Engineering

NOVEMBER 18, 2024

Liang Mou; Staff Software Engineer, Logging Platform | Elizabeth (Vi) Nguyen; Software Engineer I, Logging Platform | In today’s data-driven world, businesses need to process and analyze data in real-time to make informed decisions. What is Change Data Capture? Why is CDC Important? or its affiliates.

Kafka 50

Kafka MySQL Database Software Engineer 50

Ascend.io

NOVEMBER 14, 2024

Why Future-Proofing Your Data Pipelines Matters Data has become the backbone of decision-making in businesses across the globe. The ability to harness and analyze data effectively can make or break a company’s competitive edge. In this blog post, we’ll explore key strategies for future-proofing your data pipelines.

Data Pipeline 52

Data Pipeline Amazon Web Services Data Integration Data 52

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. Open Table Format (OTF) architecture now provides a solution for efficient data storage, management, and processing while ensuring compatibility across different platforms.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

Data Engineering Weekly

FEBRUARY 9, 2025

MoEs necessitate less compute for pre-training compared to dense models, facilitating the scaling of model and dataset size within similar computational budgets. link] QuantumBlack: Solving data quality for gen AI applications Unstructured data processing is a top priority for enterprises that want to harness the power of GenAI.

Data Engineering 57

Data Engineering Data Engineer Engineering Unstructured Data 57

Edureka

JANUARY 2, 2025

Power BI’s extensive modeling, real-time high-level analytics, and custom development simplify working with data. You will often need to work around several features to get the most out of business data with Microsoft Power BI. Additionally, it manages sizable datasets without causing Power BI to crash or perform less quickly.

BI 52

BI Datasets Business Intelligence Data Analysis 52

Ascend.io

DECEMBER 4, 2024

Automation, AI, DataOps, and strategic alignment are no longer optional —they are essential components of a successful data strategy. As we look towards 2025, it’s clear that data teams must evolve to meet the demands of evolving technology and opportunities. How effective are your current data workflows?

Data Pipeline 52

Data Pipeline Metadata Data Workflow Data 52

Cloudera

AUGUST 26, 2021

In addition to big data workloads, Ozone is also fully integrated with authorization and data governance providers namely Apache Ranger & Apache Atlas in the CDP stack. While we walk through the steps one by one from data ingestion to analysis, we will also demonstrate how Ozone can serve as an ‘S3’ compatible object store.

Data Science 113

Data Science Cloud Hadoop Metadata 113

Netflix Tech

JANUARY 2, 2025

However, due to the absence of a control group in these countries, we adopt a synthetic control framework ( blog post ) to estimate the counterfactual scenario. Before starting any math, we need to ensure a high quality historical dataset. Data quality plays a huge role in this work.

Engineering 79

Engineering Entertainment Designing Technology 79

Cloudera

FEBRUARY 8, 2021

This is part 2 in this blog series. You can read part 1, here: Digital Transformation is a Data Journey From Edge to Insight. The first blog introduced a mock connected vehicle manufacturing company, The Electric Car Company (ECC), to illustrate the manufacturing data path through the data lifecycle.

Data Pipeline 118

Data Pipeline Building Manufacturing Data Warehouse 118

Christophe Blefari

APRIL 19, 2024

It was trained on a large dataset containing 15T tokens (compared to 2T for Llama 2). This is super interesting because it details important steps of the generative process. This blog shows how you can use Gen AI to evaluate inputs like translations with added reasons. — A great blog to answer a great question.

MySQL 130

MySQL Data Datasets SQL 130

Edureka

AUGUST 2, 2023

Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly. Data processing analysts can be useful in this situation. Let’s take a deep dive into the subject and look at what we’re about to study in this blog: Table of Contents What Is Data Processing Analysis?

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Knowledge Hut

JANUARY 18, 2024

“Big data Analytics” is a phrase that was coined to refer to amounts of datasets that are so large traditional data processing software simply can’t manage them. For example, big data is used to pick out trends in economics, and those trends and patterns are used to predict what will happen in the future.

Data Process 52

Data Process Process Hadoop Scala 52

Striim

APRIL 10, 2025

As data volumes surge and the need for fast, data-driven decisions intensifies, traditional data processing methods no longer suffice. To stay competitive, organizations must embrace technologies that enable them to process data in real time, empowering them to make intelligent, on-the-fly decisions.

Data Analytics 52

Data Analytics Algorithm Datasets Data 52

Ascend.io

DECEMBER 4, 2024

Automation, AI, DataOps, and strategic alignment are no longer optional —they are essential components of a successful data strategy. As we look towards 2025, it’s clear that data teams must evolve to meet the demands of evolving technology and opportunities. How effective are your current data workflows?

Data Pipeline 52

Data Pipeline Metadata Data Workflow Data 52

Striim

NOVEMBER 17, 2023

Real-time data processing in the world of machine learning allows data scientists and engineers to focus on model development and monitoring. Striim’s strength lies in its capacity to connect to over 150 data sources, enabling real-time data acquisition from virtually any location and simplifying data transformations.

Machine Learning 52

Machine Learning Data Process PostgreSQL Process 52

Pinterest Engineering

SEPTEMBER 26, 2023

We have published a detailed blog post of its modeling architecture. At the end of this pipeline, the data with training features are ingested in the database. Figure 1: hybrid logging for features On a daily basis, the features are joined with the labels to produce the final training dataset.

Software Engineer 105

Software Engineer Software Engineering Machine Learning Datasets 105

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.

Big Data 52

Big Data Data Process Process Kafka 52

Data Engineering Weekly

JULY 14, 2024

[link] Discord: How Discord Uses Open-Source Tools for Scalable Data Orchestration & Transformation Discord writes about its migration journey from a homegrown orchestration engine to Dagster. Streaming execution to process a small chunk of data at a time. Intermediate spilling to disk while computing aggregations.

Data Engineering 98

Data Engineering Data Engineer Engineering Unstructured Data 98

Pinterest Engineering

OCTOBER 11, 2024

In Part 2 of our blog series, we described how we were able to integrate Ray(™) into our existing ML infrastructure. In this blog post, we will discuss a second type of popular application of Ray(™) at Pinterest: offline batch inference of ML models. Dataset execution is pipelined so that multiple execution stages can run in parallel.

Datasets 71

Datasets Software Engineer Software Engineering Metadata 71

LinkedIn Engineering

APRIL 4, 2023

This blog post will provide an overview of how we approached metrics selection and design, system architecture and key product features. System Architecture Overview Setup We wanted to build a single data processing pipeline that would be efficient and scalable as more metrics are added. from the metric’s processing logic (i.e.

MySQL 122

MySQL Datasets Software Engineer Software Engineering 122

DataKitchen

DECEMBER 9, 2022

DataOps involves collaboration between data engineers, data scientists, and IT operations teams to create a more efficient and effective data pipeline, from the collection of raw data to the delivery of insights and results. The data scientists and IT professionals were amazed, and they couldn’t believe their eyes.

Machine Learning 52

Machine Learning Data Preparation Government Data Analytics 52

Netflix Tech

DECEMBER 3, 2022

mock Generate or validate mock datasets. The most commonly used one is dataflow project , which helps folks in managing their data pipeline repositories through creation, testing, deployment and few other activities. " ) COMMENT "Example dataset brought to you by Dataflow. -v, --verbose Enables verbose mode.

Data Pipeline 145

Data Pipeline Scala Metadata Food 145

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. As much as possible, our focus was to use open standards in these APIs.

Data Management 106

Data Management Management Data SQL 106

Data Engineering Weekly

SEPTEMBER 18, 2024

The Rise of Data Observability Data observability has become increasingly critical as companies seek greater visibility into their data processes. This growing demand has found a natural synergy with the rise of the data lake. Visualization tools that map out pipeline dependencies are particularly helpful here.

Data Lake 98

Data Lake Data Pipeline Unstructured Data Data 98

Netflix Tech

NOVEMBER 20, 2023

by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.

Process 91

Process Data Pipeline Datasets SQL 91

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. In this blog post, we will share our progress, challenges, and lessons learned from implementing Apache Beam.

Process 97

Process Lambda Architecture Kafka Datasets 97

Pinterest Engineering

JULY 25, 2023

Soam Acharya | Data Engineering Oversight; Keith Regier | Data Privacy Engineering Manager Background Businesses collect many different types of data. Each dataset needs to be securely stored with minimal access granted to ensure they are used appropriately and can easily be located and disposed of when necessary.

Big Data 98

Big Data Accessible Accessibility Hadoop 98

Confluent

SEPTEMBER 26, 2019

® , Go, and Python SDKs where an application can use SQL to query raw data coming from Kafka through an API (but that is a topic for another blog). Let’s now dig a little bit deeper into Kafka and Rockset for a concrete example of how to enable real-time interactive queries on large datasets, starting with Kafka.

Kafka 21

Kafka SQL BI Hadoop 21

Workfall

JULY 18, 2023

Behind the scenes, a team of data wizards tirelessly crunches mountains of data to make those recommendations sparkle. As one of those wizards, we’ve seen the challenges we face: the struggle to transform massive datasets into meaningful insights, all while keeping queries fast and our system scalable.

Datasets 77

Datasets Entertainment Data Data Workflow 77

Netflix Tech

AUGUST 1, 2022

After evaluating the options , the team has decided to create Data Mesh as our next generation data pipeline solution. Last year we wrote a blog post about how Data Mesh helped our Studio team enable data movement use cases. Once deployed, the pipeline performs the actual heavy lifting data processing work.

Process 109

Process Transportation Kafka Entertainment 109

Cloudera

APRIL 1, 2024

By bringing data warehouse-like capabilities to the lake it eliminates the need for multiple data stores, simplifies data engineering pipelines, increases data reliability, and improves the efficiency of both data scientists and data analysts. Increased confidence in data results in trusted AI.

Cloud 105

Cloud Unstructured Data Metadata Government 105

Confluent

FEBRUARY 6, 2019

The blog posts How to Build and Deploy Scalable Machine Learning in Production with Apache Kafka and Using Apache Kafka to Drive Cutting-Edge Machine Learning describe the benefits of leveraging the Apache Kafka ® ecosystem as a central, scalable and mission-critical nervous system. For now, we’ll focus on Kafka.

Machine Learning 107

Machine Learning Python Kafka Java 107

Knowledge Hut

APRIL 25, 2024

It is especially true in the world of big data. If you want to stay ahead of the curve, you need to be aware of the top big data technologies that will be popular in 2024. In this blog post, we will discuss such technologies. Big data is a term that refers to the massive volume of data that organizations generate every day.

Big Data 98

Big Data Technology Hadoop NoSQL 98