LinkedIn Engineering

JUNE 15, 2023

To remove this bottleneck, we built AvroTensorDataset , a TensorFlow dataset for reading, parsing, and processing Avro data. AvroTensorDataset speeds up data preprocessing by multiple orders of magnitude, enabling us to keep site content as fresh as possible for our members. avro", "part-00001.avro"], Default is zero.

Datasets 102

Datasets Bytes Process Data Ingestion 102

ProjectPro

JUNE 6, 2025

With the global data volume projected to surge from 120 zettabytes in 2023 to 181 zettabytes by 2025, PySpark's popularity is soaring as it is an essential tool for efficient large scale data processing and analyzing vast datasets. Resilient Distributed Datasets (RDDs) are the fundamental data structure in Apache Spark.

Hadoop 68

Hadoop Metadata Java Datasets 68

ProjectPro

JUNE 6, 2025

AWS DevOps offers an innovative and versatile set of services and tools that allow you to manage, scale, and optimize big data projects. With AWS DevOps, data scientists and engineers can access a vast range of resources to help them build and deploy complex data processing pipelines, machine learning models, and more.

AWS 61

AWS Project Medical Deep Learning 61

Data Engineering Weekly

MARCH 2, 2025

I found the blog to be a fresh take on the skill in demand by layoff datasets. DeepSeek’s smallpond Takes on Big Data. DeepSeek continues to impact the Data and AI landscape with its recent open-source tools, such as Fire-Flyer File System (3FS) and smallpond. link] Mehdio: DuckDB goes distributed?

Data Engineer 62

Data Engineer Data Engineering Engineering Datasets 62

ProjectPro

JUNE 6, 2025

Data professionals who work with raw data, like data engineers, data analysts, machine learning scientists , and machine learning engineers , also play a crucial role in any data science project. This project will help analyze user data for actionable insights.

Data Engineer 59

Data Engineer Data Engineering Project Engineering 59

DataKitchen

NOVEMBER 5, 2024

The Race For Data Quality In A Medallion Architecture The Medallion architecture pattern is gaining traction among data teams. It is a layered approach to managing and transforming data. By systematically moving data through these layers, the Medallion architecture enhances the data structure in a data lakehouse environment.

Architecture 79

Architecture Raw Data Pipeline-centric Data Ingestion 79

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 56

Kafka MySQL Database Software Engineer 56

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

ProjectPro

JUNE 6, 2025

Traditional databases may need help to provide the necessary performance when dealing with large datasets and complex queries. Data warehousing tools are designed to handle such scenarios efficiently, enabling faster query performance and analysis, even on massive datasets. Not designed for transactional processing.

Data Storage 58

Data Storage PostgreSQL Data Warehouse AWS 58

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 Metadata Utilities 67

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 Aggregated Data Data Pipeline Data Validation 52

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 Engineer 57

Data Engineer Data Engineering Engineering Amazon Web Services 57

ProjectPro

JUNE 6, 2025

It requires a skillful blend of data engineering expertise and the strategic use of tools designed to streamline this process. That’s where data pipeline tools come in. This blog is all about that—specifically, the top 10 data pipeline tools that data engineers worldwide rely on.

Data Pipeline 49

Data Pipeline Google Cloud Kafka AWS 49

ProjectPro

JUNE 6, 2025

This blog offers an Agentic AI learning path, explaining the core components behind AI Agents. If you’ve ever wondered how these intelligent systems work or wanted to build one, this blog is your starting point. Read more about AI agents in our latest blog: AI Agents: The New Human-Like Heroes of AI.

Deep Learning 80

Deep Learning Algorithm Machine Learning Banking 80

ProjectPro

JUNE 6, 2025

Master PySpark RDD operations and concepts with our concise and comprehensive PySpark cheat sheet, empowering you to unlock the potential of distributed data processing. Resilient Distributed Datasets (RDDs) are a fundamental abstraction in PySpark, designed to handle distributed data processing tasks.

Algorithm 40

Algorithm Datasets Utilities Big Data 40

ProjectPro

JUNE 6, 2025

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 Businesses are leveraging big data now more than ever.

AWS 66

AWS Scala Metadata Data Lake 66

ProjectPro

JUNE 6, 2025

Building data pipelines is a core skill for data engineers and data scientists as it helps them transform raw data into actionable insights. In this blog, you’ll build a complete ETL pipeline in Python to perform data extraction from the Spotify API, followed by data manipulation and transformation for analysis.

Python 40

Python Building PostgreSQL Raw Data 40

Cloudera

DECEMBER 3, 2024

You can share Iceberg table data with your clients who can then access the data using third party engines like Amazon Athena , Trino, Databricks, or Snowflake that support Iceberg REST catalog. The solution covered by this blog describes how Cloudera shares data with an Amazon Athena notebook.

Metadata 84

Metadata SQL Data Warehouse Database 84

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 Data Integration 52

ProjectPro

JUNE 6, 2025

Tired of relentlessly searching for the most effective and powerful data warehousing solutions on the internet? This blog is your comprehensive guide to Google BigQuery, its architecture, and a beginner-friendly tutorial on how to use Google BigQuery for your data warehousing activities. Search no more! Did you know ?

Bytes 40

Bytes Google Cloud Data Warehouse Cloud Storage 40

ProjectPro

JUNE 6, 2025

Read this blog further to explore the Hive Architecture and its indispensable role in the landscape of big data projects. Hive is a data warehousing and SQL-like query language system built on top of Hadoop. It is designed to facilitate querying and managing large datasets in a distributed storage environment.

Big Data 40

Big Data Architecture Project Hadoop 40

ProjectPro

JUNE 6, 2025

A data engineer can fulfill the above-mentioned responsibilities only if they possess a suitable skill set. And if you are now searching for a list of that highlights those skills, head over to the next section of this blog. as they are required for processing large datasets.

Data Engineer 49

Data Engineer Data Engineering Engineering Hadoop 49

ProjectPro

JUNE 6, 2025

This blog post provides an overview of the top 10 data engineering tools for building a robust data architecture to support smooth business operations. Table of Contents What are Data Engineering Tools? This speeds up data processing by reducing disc read and write times.

Data Engineer 45

Data Engineer Data Engineering Engineering Kafka 45

ProjectPro

JUNE 6, 2025

However, building and maintaining a scalable data science pipeline comes with challenges like data quality , integration complexity, scalability, and compliance with regulations like GDPR. Characteristics of a Data Science Pipeline A well-designed data science pipeline helps process data from source to insights seamlessly.

Data Science 40

Data Science Building Data Lake AWS 40

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

ProjectPro

JUNE 6, 2025

These platforms facilitate effective data management and other crucial Data Engineering activities. This blog will give you an overview of the GCP data engineering tools thriving in the big data industry and how these GCP tools are transforming the lives of data engineers.

Data Engineer 40

Data Engineer Data Engineering Engineering Google Cloud 40

ProjectPro

JUNE 6, 2025

This blog presents some of the most unique and exciting AWS projects from beginner to advanced levels. AWS (Amazon Web Services) is the leading global cloud platform, offering over 200 fully featured services from data centers worldwide. You can work on these AWS sample projects to expand your skills and knowledge.

AWS 60

AWS Project Food Cloud Computing 60

ProjectPro

JUNE 6, 2025

With Azure Databricks, managing and analyzing large volumes of data becomes effortlessly seamless. So, if you're a data professional ready to embark on a data-driven adventure, read this blog till the end as we unravel the secrets of Azure Databricks and discover the limitless possibilities it holds.

Data Engineer 40

Data Engineer Data Engineering Engineering Data Lake 40

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 Engineer 57

Data Engineer Data Engineering Engineering Unstructured Data 57

ProjectPro

JUNE 6, 2025

Table of Contents 20 Open Source Big Data Projects To Contribute How to Contribute to Open Source Big Data Projects? 20 Open Source Big Data Projects To Contribute There are thousands of open-source projects in action today. This blog will walk through the most popular and fascinating open source big data projects.

Big Data 49

Big Data Project Metadata Programming Language 49

ProjectPro

JUNE 6, 2025

This blog introduces five interesting AWS Lambda project ideas that will show you where and how to implement Lambda in the best possible way. Learn more about real-world big data applications with unique examples of big data projects. The dataset includes widely popular YouTube videos (in CSV files). PREVIOUS NEXT <

AWS 40

AWS Project MySQL Google Cloud 40

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

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

ProjectPro

JUNE 6, 2025

Using Artificial Intelligence (AI) in the Data Analytics process is the first step for businesses to understand AI's potential. This blog revolves around helping individuals realize this potential through its applications, advantages, and project examples. from 2022 to 2030.

Data Analytics 40

Data Analytics Healthcare Machine Learning Algorithm 40

ProjectPro

JUNE 6, 2025

So, when is it better to process data in bulk, and when should you take the plunge into real-time data streams? This blog will break down the key differences between batch and stream processing, comparing them in terms of performance, latency, scalability, and fault tolerance.

Process 40

Process Kafka Hadoop Banking 40

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