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

Data Engineering Weekly

MAY 16, 2023

I won’t bore you with the importance of data quality in the blog. Instead, Let’s examine the current data pipeline architecture and ask why data quality is expensive. Instead of looking at the implementation of the data quality frameworks, Let's examine the architectural patterns of the data pipeline.

Engineering 110

Engineering Kafka Data Pipeline Data Warehouse 110

Ascend.io

APRIL 22, 2024

This initiative is more than just an upgrade; it’s a reimagining of what a Data Automation Platform can be: dynamic, extensible, and highly intelligent. A unified platform that combines a powerful metadata core, an extensible plugin architecture, DataAware automation, and multiple AI Assistants.

Project 52

Project Metadata Data Pipeline Data Engineering 52

Data Engineering Podcast

AUGUST 28, 2022

Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. RudderStack helps you build a customer data platform on your warehouse or data lake.

Data Engineering 100

Data Engineering Data Engineer MongoDB Metadata 100

Workfall

JUNE 12, 2023

Moreover, it facilitates the implementation of microservices architectures and event-driven systems, automating reactions to data changes without manual intervention. In real-time data streaming and event-driven architectures, CDC captures data changes to trigger actions or workflows.

Telecommunication 80

Telecommunication Metadata Healthcare Finance 80

DataKitchen

OCTOBER 20, 2023

The Challenge: High Stakes in the Age of Personalized Data Observability The primary challenge stems from the requirement of Data Consumers for personalized monitoring and alerts based on their unique data processing needs. Data Observability platforms often need to deliver this level of customization.

Insurance 67

Insurance Pharmaceutical Data Data Ingestion 67

Grouparoo

OCTOBER 6, 2021

This provided a nice overview of the breadth of topics that are relevant to data engineering including data warehouses/lakes, pipelines, metadata, security, compliance, quality, and working with other teams. For example, grouping the ones about metadata, discoverability, and column naming might have made a lot of sense.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Data Engineering Podcast

OCTOBER 14, 2019

Dataform is a platform that helps you apply engineering principles to your data transformations and table definitions, including unit testing SQL scripts, defining repeatable pipelines, and adding metadata to your warehouse to improve your team’s communication. This week’s episode is also sponsored by Datacoral.

Data Warehouse 100

Data Warehouse PostgreSQL AWS Programming Language 100

Netflix Tech

MARCH 7, 2024

Data: Fast Data Our main data lake is hosted on S3, organized as Apache Iceberg tables. For ETL and other heavy lifting of data, we mainly rely on Apache Spark. In addition to Spark, we want to support last-mile data processing in Python, addressing use cases such as feature transformations, batch inference, and training.

Systems 90

Systems Media Machine Learning Data Warehouse 90

ProjectPro

FEBRUARY 16, 2023

AWS Glue is a fully managed ETL service that automates the process of cataloging, preparing, and cleaning so analysts can focus on analyzing it and not wrangling it. AWS Glue has a central metadata repository called the Glue catalog. The crawler also helps detect any changes in schema and updates metadata as required.

AWS 52

AWS Data Management ETL Tools Management 52

Data Engineering Weekly

NOVEMBER 6, 2022

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. Every data processing engine has one metadata store to integrate.

Data Engineering 40

Data Engineering Data Engineer Engineering Machine Learning 40

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Monte Carlo

APRIL 7, 2021

Data pipelines can break for a million different reasons, and there isn’t a one-size-fits all approach to understanding how or why. Here are five critical steps data engineers must take to conduct engineering root cause analysis for data quality issues. Who uses the dataset that’s experiencing the issue right now?

Data Engineering 40

Data Engineering Data Engineer Engineering Datasets 40

Knowledge Hut

OCTOBER 26, 2023

You can use AWS SES (Simple Email Service) to send emails and AWS SNS (Simple Notification Service) to trigger the email-sending process. Once you upload a CSV file to S3, an S3 event is triggered. After the file is imported, the process of mass emailing begins. Amazon Lambda is closely linked to the S3 service in this project.

AWS 52

AWS Coding Project Cloud Computing 52

ProjectPro

JULY 23, 2021

Real-time Data Processing Application 7. AWS Athena Big Data Project for Querying COVID-19 Data 25. Build an AWS ETL Data Pipeline in Python on YouTube Data 26. As soon as you upload a CSV file, it will trigger an S3 event. The process of sending the mail to the addresses provided will begin.

AWS 52

AWS Project Amazon Web Services Cloud Computing 52

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

AltexSoft

JULY 18, 2023

Its flexibility allows it to operate on single-node machines and large clusters, serving as a multi-language platform for executing data engineering , data science , and machine learning tasks. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. Big data processing.

Big Data 52

Big Data Data Process Process Hadoop 52

Cloudera

FEBRUARY 8, 2021

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. Having completed the Data Collection step in the previous blog, ECC’s next step in the data lifecycle is Data Enrichment.

Data Pipeline 114

Data Pipeline Building Manufacturing Data Warehouse 114

Netflix Tech

DECEMBER 21, 2020

On the other hand, these optimizations themselves need to be sufficiently inexpensive to justify their own processing cost over the gains they bring. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Data Warehouse 81

Data Warehouse Metadata Algorithm Data 81

Netflix Tech

NOVEMBER 20, 2023

IPS provides the incremental processing support with data accuracy, data freshness, and backfill for users and addresses many of the challenges in workflows. IPS enables users to continue to use the data processing patterns with minimal changes. Snapshots include references to the actual immutable data files.

Process 84

Process Data Pipeline Datasets Aggregated Data 84

AltexSoft

NOVEMBER 7, 2022

The platform went live in 2015 at Airbnb, the biggest home-sharing and vacation rental site, as an orchestrator for increasingly complex data pipelines. How data engineering works. Apache Airflow is an open-source Python -based workflow orchestrator that enables you to design, schedule, and monitor data pipelines.

PostgreSQL 52

PostgreSQL Metadata Python MySQL 52

Ascend.io

DECEMBER 11, 2023

Here’s the deal: for data to truly drive your business forward, you need a reliable and scalable system to keep it moving without hiccups. In other words, you need data orchestration. In this article, we’ll break down what data orchestration is, its significance, and how it differs from data pipeline orchestration.

Data Workflow 52

Data Workflow Data Pipeline Data Lake Data 52

DataKitchen

SEPTEMBER 21, 2023

L1 is usually the raw, unprocessed data ingested directly from various sources; L2 is an intermediate layer featuring data that has undergone some form of transformation or cleaning; and L3 contains highly processed, optimized, and typically ready for analytics and decision-making processes.

Raw Data 67

Raw Data Data Business Intelligence High Quality Data 67

Cloudera

AUGUST 16, 2021

Hundreds of built-in processors make it easy to connect to any application and transform data structures or data formats as needed. Since it supports both structured and unstructured data for streaming and batch integrations, Apache NiFi is quickly becoming a core component of modern data pipelines. and later).

Cloud 118

Cloud Unstructured Data Utilities Metadata 118

Rockset

NOVEMBER 28, 2022

First, CDC theoretically allows companies to analyze and react to data in real time, as it’s generated. It works with existing streaming systems like Apache Kafka, Amazon Kinesis, and Azure Events Hubs, making it easier than ever to build a real-time data pipeline. Estuary : A real-time data operations platform.

Data Warehouse 52

Data Warehouse PostgreSQL MongoDB Data Pipeline 52

ProjectPro

NOVEMBER 15, 2021

To execute pipelines, beam supports numerous distributed processing back-ends, including Apache Flink, Apache Spark , Apache Samza, Hazelcast Jet, Google Cloud Dataflow, etc. It serves as a distributed processing engine for both categories of data streams: unbounded and bounded.

Big Data 52

Big Data Project Metadata Programming Language 52

AltexSoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. Incremental extraction. Enrichment.

Process 52

Process Building Raw Data Data Lake 52

AltexSoft

OCTOBER 21, 2022

This scenario involves three main characters — publishers, subscribers, and a message or event broker. A publisher (say, telematics or Internet of Medical Things system) produces data units, also called events or messages , and directs them not to consumers but to a middleware platform — a broker. Kafka cluster and brokers.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

ProjectPro

AUGUST 11, 2021

The data warehouse layer consists of the relational database management system (RDBMS) that contains the cleaned data and the metadata, which is data about the data. The RDBMS can either be directly accessed from the data warehouse layer or stored in data marts designed for specific enterprise departments.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

AUGUST 24, 2021

Data Sourcing: Building pipelines to source data from different company data warehouses is fundamental to the responsibilities of a data engineer. So, work on projects that guide you on how to build end-to-end ETL/ELT data pipelines. Blob Storage for intermediate storage of generated predictions.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

JANUARY 31, 2022

Snowflake Data Marketplace gives users rapid access to various third-party data sources. Moreover, numerous sources offer unique third-party data that is instantly accessible when needed. Snowflake's machine learning partners transfer most of their automated feature engineering down into Snowflake's cloud data platform.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Dataquest

JANUARY 25, 2017

App analytics logs App event logs. In order to enable them to create this, you’ll need to combine information from the server access logs and the app event logs. Roughly, the operations in a data pipeline consist of the following phases: Ingestion — this involves gathering in the needed data.

Data Engineering 52

Data Engineering Data Engineer Pipeline-centric Database-centric 52

ProjectPro

OCTOBER 28, 2015

Sqoop is an effective hadoop tool for non-programmers which functions by looking at the databases that need to be imported and choosing a relevant import function for the source data. Once the input is recognized by Sqoop hadoop, the metadata for the table is read and a class definition is created for the input requirements.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

Data Engineering Podcast

JANUARY 28, 2018

Preamble Hello and welcome to the Data Engineering Podcast, the show about modern data infrastructure When you’re ready to launch your next project you’ll need somewhere to deploy it. To save 60% of your tickets go to data engineering podcast.com slash o d s c dash East dash 2018 and register.

Data 100

Data Project Electronics Data Management 100

AltexSoft

OCTOBER 8, 2021

Considered to be a leader in the field of data integration, Oracle Data Integrator (ODI) is a multi-functional solution that is part of Oracle’s data management ecosystem. The platform provides features for event-based , data-based, and service-based integration styles. Data profiling and cleansing.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

Rockset

JULY 25, 2019

This is an operational analytics query because it allows the game developer to make instant decisions based on analysis of current events. Your user-facing interactive apps query the same data engine to fetch insights from your data set in real time, and you then use that intelligence to provide a better user experience to your users.

Software Engineer 40

Software Engineer Software Engineering Engineering PostgreSQL 40

ProjectPro

OCTOBER 20, 2021

This is used in social media to better gauge sentiments towards an event or a product. Experimentation in production Big Data Data Warehouse for core ETL tasks Direct data pipelines Tiered Data Lake 4. This is because machine learning systems are highly dependent on the nature of the problem and the data.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52