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

Striim

NOVEMBER 17, 2023

In today’s data-driven world, the ability to leverage real-time data for machine learning applications is a game-changer. Real-time data processing in the world of machine learning allows data scientists and engineers to focus on model development and monitoring.

Machine Learning 52

Machine Learning Data Process PostgreSQL Process 52

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 94

Data Process Process Data 94

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 59

Google Cloud Process Cloud Lambda Architecture 59

DoorDash Engineering

NOVEMBER 21, 2022

Subscribe for weekly updates The solution to real-time processing of inventory changes The simplest approach to propagating inventory level changes in the database to the rest of the system may have been to invoke the service code to take actions every time something that affects the inventory table is called.

Data Process 57

Data Process Process Kafka Database 57

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

ProjectPro

JANUARY 25, 2022

Did you know that, according to Linkedin, over 24,000 Big Data jobs in the US list Apache Spark as a required skill? Learning Spark has become more of a necessity to enter the Big Data industry. Python is one of the most extensively used programming languages for Data Analysis, Machine Learning , and data science tasks.

Big Data 52

Big Data Data Process Process Kafka 52

Data Science Blog: Data Engineering

NOVEMBER 15, 2023

In addition to Business Intelligence (BI), Process Mining is no longer a new phenomenon, but almost all larger companies are conducting this data-driven process analysis in their organization. This aspect can be applied well to Process Mining, hand in hand with BI and AI.

Architecture 52

Architecture Database-centric Process BI 52

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 87

Google Cloud Data Process Process Cloud 87

Christophe Blefari

APRIL 19, 2024

easy ( credits ) Hey, new Friday, new Data News. 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. This week, I feel like the selection is smaller than usual, so enjoy the links.

MySQL 130

MySQL Data Datasets SQL 130

Robinhood

FEBRUARY 7, 2024

from Robinhood Data Infrastructure Robinhood adheres to a data-first philosophy. Every decision we make here (or every decision at the company), from feature rollouts to operational changes, is backed by data. When dealing with large-scale data, we turn to batch processing with distributed systems to complete high-volume jobs.

Process 75

Process Hadoop Architecture Accessible 75

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

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

Databand.ai

JULY 19, 2023

Complete Guide to Data Ingestion: Types, Process, and Best Practices Helen Soloveichik July 19, 2023 What Is Data Ingestion? Data Ingestion is the process of obtaining, importing, and processing data for later use or storage in a database. In this article: Why Is Data Ingestion Important?

Data Ingestion 52

Data Ingestion Process Data Cleanse Data Governance 52

Analytics Vidhya

FEBRUARY 28, 2023

A collaborative and interactive workspace allows users to perform big data processing and machine learning tasks easily. In this blog post, we will take a closer look at Azure Databricks, its key features, […] The post Azure Databricks: A Comprehensive Guide appeared first on Analytics Vidhya.

Big Data 310

Big Data Machine Learning Cloud Data Process 310

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

Cloudera

SEPTEMBER 11, 2018

Last week Cloudera introduced an open end-to-end architecture for IoT and the different components needed to help satisfy today’s enterprise needs regarding operational technology (OT), information technology (IT), data analytics and machine learning (ML), along with modern and traditional application development, deployment, and integration.

Data Process 40

Data Process Process Building Machine Learning 40

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. The goal of DataOps is to help organizations make better use of their data to drive business decisions and improve outcomes.

Machine Learning 52

Machine Learning Data Preparation Government Data Analytics 52

Engineering at Meta

MAY 22, 2024

In recent years, Meta’s data management systems have evolved into a composable architecture that creates interoperability, promotes reusability, and improves engineering efficiency. Data is at the core of every product and service at Meta. We needed to change our thinking to be able to move faster.

Data Management 93

Data Management Management Data SQL 93

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

Cloudera

JULY 18, 2022

In part 1 of this blog we discussed how Cloudera DataFlow for the Public Cloud (CDF-PC), the universal data distribution service powered by Apache NiFi, can make it easy to acquire data from wherever it originates and move it efficiently to make it available to other applications in a streaming fashion. Data decays!

Process 90

Process Kafka Scala SQL 90

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

Knowledge Hut

APRIL 25, 2024

Big data in information technology is used to improve operations, provide better customer service, develop customized marketing campaigns, and take other actions to increase revenue and profits. It is especially true in the world of big data. It is especially true in the world of big data. What Are Big Data T echnologies?

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Big Data Technology NoSQL Hadoop 98

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

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

Striim

JUNE 6, 2024

For your organization’s data integration and streaming initiatives to succeed, meeting latency requirements is crucial. Low latency, defined by the rapid transmission of data with minimal delay, is essential for maximizing the effectiveness of your data strategy. Here’s what you need to know.

Data Integration 52

Data Integration Data Ingestion Healthcare Data Pipeline 52

Knowledge Hut

JUNE 11, 2024

In recent years, Machine Learning, Artificial Intelligence, and Data Science have become some of the most talked-about technologies. Companies of all sizes are investing millions of dollars in data analysis and on professionals who can build these exceptionally powerful data-driven products. So let us get to it.

Java 52

Java Data Science Programming Language Scala 52

Data Engineering Weekly

FEBRUARY 25, 2024

RudderStack is the Warehouse Native CDP, built to help data teams deliver value across the entire data activation lifecycle, from collection to unification and activation. Editor’s Note: DEWCon Europe Update & Data Hero’s Chennai Chapter Meetup Last week, we asked our readers if we should bring DEWCon to Europe.

Data Engineering 62

Data Engineering Data Engineer Engineering Kafka 62

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

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Mastering Data Production (#3) Introduction Managing the production phase of data analytics is a daunting challenge. Overseeing multi-tool, multi-dataset, and multi-hop data processes ensures high-quality outputs.

Raw Data 49

Raw Data Data Ingestion Datasets Data 49

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

Team Data Science

MAY 10, 2020

I can now begin drafting my data ingestion/ streaming pipeline without being overwhelmed. With careful consideration and learning about your market, the choices you need to make become narrower and more clear. I'll use Python and Spark because they are the top 2 requested skills in Toronto.

Data Pipeline 130

Data Pipeline Data Ingestion AWS Kafka 130

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. Airflow isn’t meant to process the data. See how it works today.

Data Engineering 67

Data Engineering Data Engineer Engineering Kafka 67

Data Engineering Weekly

DECEMBER 3, 2023

RudderStack is the Warehouse Native CDP, built to help data teams deliver value across the entire data activation lifecycle, from collection to unification and activation. Github writes an excellent blog to capture the current state of the LLM integration architecture. Lackluster AI/ML results often stem from poor data quality.

Data Engineering 70

Data Engineering Data Engineer Engineering Bytes 70

ProjectPro

FEBRUARY 16, 2023

With its easy-to-use interface and robust features, OpenCV has become the favorite of data scientists and computer vision engineers. At the core of such applications lies the science of machine learning, image processing, computer vision, and deep learning. What is OpenCV Python?

Python 98

Python Process Deep Learning Algorithm 98

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. Hence we built the data pipeline that can be used to extract the existing assets metadata and process it specifically to each new use case.

Management 94

Management Kafka Metadata Media 94

Cloudera

OCTOBER 16, 2023

Cloudera recently released a fully featured Open Data Lakehouse , powered by Apache Iceberg in the private cloud, in addition to what’s already been available for the Open Data Lakehouse in the public cloud since last year. SDX Integration: Provides common security and governance policies, as well as data lineage and auditing.

Cloud 79

Cloud Kafka SQL Data 79