KDnuggets

JULY 13, 2022

Learn various techniques to reduce data processing time by using multiprocessing, joblib, and tqdm concurrent.

Process 159

Process Python Data Process Data 159

Netflix Tech

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty In the inaugural blog post of this series, we introduced you to the state of our pipelines before Psyberg and the challenges with incremental processing that led us to create the Psyberg framework within Netflix’s Membership and Finance data engineering team.

Data Process 93

Data Process Process Metadata Finance 93

LinkedIn Engineering

JANUARY 19, 2024

This multi-entity handover process involves huge amounts of data updating and cloning. 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. Push for eventual success of the request.

Recruitment 88

Recruitment Data Process Process Kafka 88

DataKitchen

MARCH 20, 2025

Unlocking Data Team Success: Are You Process-Centric or Data-Centric? Over the years of working with data analytics teams in large and small companies, we have been fortunate enough to observe hundreds of companies. We want to share our observations about data teams, how they work and think, and their challenges.

Pipeline-centric 64

Pipeline-centric Database-centric Process Data 64

databricks

MARCH 4, 2024

StreamNative, a leading Apache Pulsar-based real-time data platform solutions provider, and Databricks, the Data Intelligence Platform, are thrilled to announce the enhanced Pulsar-Spark.

Data Process 126

Data Process Process Data 126

databricks

JUNE 15, 2023

We are excited to announce the official launch of the Google Pub/Sub connector for the Databricks Lakehouse Platform. This new connector adds to.

Google Cloud 119

Google Cloud Data Process Process Cloud 119

Data Engineering Podcast

JUNE 9, 2024

Summary Streaming data processing enables new categories of data products and analytics. Unfortunately, reasoning about stream processing engines is complex and lacks sufficient tooling. Support Data Engineering Podcast Summary Streaming data processing enables new categories of data products and analytics.

Process 147

Process Data Lake High Quality Data Machine Learning 147

Precisely

MARCH 3, 2025

Data and process automation used to be seen as luxury but those days are gone. Lets explore the top challenges to data and process automation adoption in more detail. Almost half of respondents (47%) reported a medium level of automation adoption, meaning they currently have a mix of automated and manual SAP processes.

Process 59

Process Government Data Finance 59

Towards Data Science

FEBRUARY 12, 2024

Let’s learn what… Continue reading on Towards Data Science » In this first article, we’re exploring Apache Beam, from a simple pipeline to a more complicated one, using GCP Dataflow.

Data Pipeline 98

Data Pipeline Data Process Process Data Science 98

Striim

MARCH 21, 2025

What is Real-Time Stream Processing? In today’s fast-moving world, companies need to glean insights from data as soon as it’s generated. To access real-time data, organizations are turning to stream processing. To access real-time data, organizations are turning to stream processing.

Process 52

Process Data Warehouse Kafka Data Pipeline 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.

Process 119

Process Lambda Architecture Kafka Machine Learning 119

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.

Google Cloud 92

Google Cloud Process Cloud Lambda Architecture 92

Analytics Vidhya

FEBRUARY 28, 2023

A collaborative and interactive workspace allows users to perform big data processing and machine learning tasks easily. Introduction Azure Databricks is a fast, easy, and collaborative Apache Spark-based analytics platform that is built on top of the Microsoft Azure cloud.

Big Data 312

Big Data Machine Learning Cloud Data Process 312

Cloudera

MARCH 2, 2023

Iceberg is a high-performance open table format for huge analytic data sets. It allows multiple data processing engines, such as Flink, NiFi, Spark, Hive, and Impala to access and analyze data in simple, familiar SQL tables. This enables you to maximize utilization of streaming data at scale. Try it out yourself!

Process 114

Process SQL Kafka Database 114

Towards Data Science

FEBRUARY 18, 2024

How to Stream and Apply Real-Time Prediction Models on High-Throughput Time-Series Data Photo by JJ Ying on Unsplash Most of the stream processing libraries are not python friendly while the majority of machine learning and data mining libraries are python based.

Kafka 98

Kafka Python Process Google Cloud 98

Jesse Anderson

FEBRUARY 11, 2025

Discover the insights he gained from academia and industry, his perspective on the future of data processing and the story behind building a next-generation graph database. Semih explains how Kuzu addresses the challenges of large graph analytics, the benefits of embeddability, and its potential for applications in AI and beyond.

Computer Science 130

Computer Science Database Design Software Engineer Software Engineering 130

Start Data Engineering

MAY 28, 2024

Building efficient data pipelines with DuckDB 4.1. 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. Processing data less than 100GB? Introduction 2. Project demo 3. Use DuckDB 4.4.

Data Pipeline 219

Data Pipeline Python Building Data 219

Analytics Vidhya

FEBRUARY 7, 2023

Introduction Data engineering is the field of study that deals with the design, construction, deployment, and maintenance of data processing systems. The goal of this domain is to collect, store, and process data efficiently and efficiently so that it can be used to support business decisions and power data-driven applications.

Data Engineering 248

Data Engineering Data Engineer Engineering Data 248

Analytics Vidhya

FEBRUARY 13, 2023

Introduction Every data scientist demands an efficient and reliable tool to process this big unstoppable data. Today we discuss one such tool called Delta Lake, which data enthusiasts use to make their data processing pipelines more efficient and reliable.

Data Process 242

Data Process Process Data Data Warehouse 242

Analytics Vidhya

FEBRUARY 23, 2023

Introduction Big Data is a large and complex dataset generated by various sources and grows exponentially. It is so extensive and diverse that traditional data processing methods cannot handle it. The volume, velocity, and variety of Big Data can make it difficult to process and analyze.

Big Data Tools 242

Big Data Tools Big Data Datasets Data 242

Analytics Vidhya

FEBRUARY 2, 2023

Introduction Big data processing is crucial today. Big data analytics and learning help corporations foresee client demands, provide useful recommendations, and more. Hadoop, the Open-Source Software Framework for scalable and scattered computation of massive data sets, makes it easy.

Hadoop 237

Hadoop Big Data Data Analytics Data Process 237

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. If greater than one, records in files are processed in parallel.

Datasets 102

Datasets Bytes Process Data Ingestion 102

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 87

Process Data Pipeline Datasets SQL 87

Robinhood

FEBRUARY 7, 2024

When dealing with large-scale data, we turn to batch processing with distributed systems to complete high-volume jobs. In this blog, we explore the evolution of our in-house batch processing infrastructure and how it helps Robinhood work smarter. Why Batch Processing is Integral to Robinhood Why is batch processing important?

Process 82

Process Hadoop Architecture Accessibility 82

Engineering at Meta

JANUARY 22, 2025

This belief has led us to developing Privacy Aware Infrastructure (PAI) , which offers efficient and reliable first-class privacy constructs embedded in Meta infrastructure to address different privacy requirements, such as purpose limitation , which restricts the purposes for which data can be processed and used.

Data Warehouse 110

Data Warehouse SQL Programming Language Data 110

Analytics Vidhya

FEBRUARY 19, 2023

Introduction Data pipelines play a critical role in the processing and management of data in modern organizations. A well-designed data pipeline can help organizations extract valuable insights from their data, automate tedious manual processes, and ensure the accuracy of data processing.

Data Pipeline 199

Data Pipeline Data Designing Data Process 199

Snowflake

APRIL 16, 2025

Process all your data where it already lives Fragmented data environments and complex cloud architectures impede efficiency and innovation. However, relying only on structured data for these models can overlook valuable signals present in unstructured sources like images, which influence user engagement.

Data Analysis 76

Data Analysis Unstructured Data Manufacturing Retail 76

Snowflake

JUNE 5, 2024

With Snowpark’s existing DataFrame API , users have access to a robust framework for lazily evaluated, relational operations on data, closely resembling Spark’s conventions. pandas is the go-to data processing library for millions worldwide, including countless Snowflake users. Why introduce a distributed pandas API?

Python 128

Python Programming Language Government SQL 128

Analytics Vidhya

APRIL 28, 2023

It is a famous Scala-coded data processing tool that offers low latency, extensive throughput, and a unified platform to handle the data in real-time. Introduction Apache Kafka is an open-source publish-subscribe messaging application initially developed by LinkedIn in early 2011.

Kafka 206

Kafka Scala Coding Data Process 206

Snowflake

MARCH 26, 2025

In this edition, we talk to Richard Meng, co-founder and CEO of ROE AI , a startup that empowers data teams to extract insights from unstructured, multimodal data including documents, images and web pages using familiar SQL queries. ROE AI solves unstructured data with zero embedding vectors. What inspires you as a founder?

Unstructured Data 98

Unstructured Data SQL Data Data Workflow 98

Edureka

APRIL 22, 2025

Exponential Growth in AI-Driven Data Solutions This approach, known as data building, involves integrating AI-based processes into the services. As early as 2025, the integration of these processes will become increasingly significant. It lets you describe data more complexly and make predictions.

Data Engineering 52

Data Engineering Data Engineer Engineering Consulting 52

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. Set Up Auto-Scaling: Configure auto-scaling for your data processing and storage resources.

Data Pipeline 52

Data Pipeline Amazon Web Services Data Integration Data 52

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 78

Architecture Raw Data Pipeline-centric Data Ingestion 78

Snowflake

MARCH 20, 2025

When they deploy Contextual AI as a Snowflake Native App , they get the peace of mind that comes with running the platform and the data processing inside their own Snowflake environment, while Snowflake manages the infrastructure complexity, including server management, scaling and maintenance.

Programming 96

Programming Certification Building Designing 96

Snowflake

APRIL 7, 2025

We identified this issue through firsthand experience, having worked for decades in food safety and quality management, where we consistently saw companies struggle with compliance and data transparency. Whats the coolest thing youre doing with data?

Food 90

Food Data Transparency Software Engineer Software Engineering 90

Snowflake

NOVEMBER 11, 2024

Here’s how Snowflake Cortex AI and Snowflake ML are accelerating the delivery of trusted AI solutions for the most critical generative AI applications: Natural language processing (NLP) for data pipelines: Large language models (LLMs) have a transformative potential, but they often batch inference integration into pipelines, which can be cumbersome.

Unstructured Data 98

Unstructured Data SQL AWS Healthcare 98

Snowflake

NOVEMBER 19, 2024

But CTC was paying $800,000 a year just to move data from Snowflake to managed Spark for processing and back again. To overcome these hurdles, CTC moved its processing off of managed Spark and onto Snowflake, where it had already built its data foundation.

Data Governance 98

Data Governance Government Healthcare Building 98