Netflix Tech

NOVEMBER 14, 2023

In the previous installments of this series, we introduced Psyberg and delved into its core operational modes: Stateless and Stateful Data Processing. Pipelines After Psyberg Let’s explore how different modes of Psyberg could help with a multistep data pipeline. Audit Run various quality checks on the staged data.

Metadata 97

Metadata Data Pipeline Scala Data Workflow 97

Snowflake

JANUARY 23, 2024

Behind the scenes, Snowpark ML parallelizes data processing operations by taking advantage of Snowflake’s scalable computing platform. For Snowpark ML Operations, the Snowpark Model Registry allows customers to securely manage and execute models in Snowflake, regardless of origin.

Machine Learning 120

Machine Learning Metadata Python Telecommunication 120

Netflix Tech

DECEMBER 14, 2023

Engineers from across the company came together to share best practices on everything from Data Processing Patterns to Building Reliable Data Pipelines. The result was a series of talks which we are now sharing with the rest of the Data Engineering community!

Data Engineering 103

Data Engineering Data Engineer Engineering Metadata 103

Snowflake

NOVEMBER 29, 2023

Also, the associated business metadata for omics, which make it findable for later use, are dynamic and complex and need to be captured separately. Additionally, the fact that they need to be standardized makes the data discovery effort challenging for downstream analysis.

Metadata 84

Metadata Healthcare Medical Data Storage 84

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

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

Rockset

MARCH 18, 2024

That’s because successfully deploying an AI application requires retrieval augmented generation or “RAG” pipelines, processing real-time data streams, chunking data, generating embeddings, storing embeddings and running vector search. LLMs like ChatGPT are trained on vast amounts of text data available up to a cutoff date.

Cloud 64

Cloud Building Metadata Kafka 64

Netflix Tech

DECEMBER 3, 2022

Obviously not all tools are made with the same use case in mind, so we are planning to add more code samples for other (than classical batch ETL) data processing purposes, e.g. Machine Learning model building and scoring. The main workflow definition file holds the logic of a single run, in this case one day-worth of data.

Data Pipeline 143

Data Pipeline Scala Metadata Food 143

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

RandomTrees

APRIL 18, 2024

By leveraging Python’s capabilities, we can create scripts that analyze Informatica workflows, extract relevant metadata, and generate equivalent Talend jobs. Analysing Informatica Workflows : The first step in the conversion process is to analyze Informatica workflows to extract essential metadata and transformation logic.

Coding 52

Coding Retail Metadata Python 52

Databand.ai

AUGUST 30, 2023

Data Performance Testing Data performance testing is the process of evaluating the efficiency, effectiveness, and scalability of your data processing systems and infrastructure. To perform data performance testing, you should first establish performance benchmarks and targets for your data processing systems.

Data Cleanse 52

Data Cleanse Metadata High Quality Data Datasets 52

Striim

FEBRUARY 5, 2024

Data Fabric is a comprehensive data management approach that goes beyond traditional methods , offering a framework for seamless integration across diverse sources. By upholding data quality, organizations can trust the information they rely on for decision-making, fostering a data-driven culture built on dependable insights.

Pharmaceutical 52

Pharmaceutical Data Cleanse Metadata Medical 52

Knowledge Hut

MARCH 7, 2024

The year 2024 saw some enthralling changes in volume and variety of data across businesses worldwide. The surge in data generation is only going to continue. Foresighted enterprises are the ones who will be able to leverage this data for maximum profitability through data processing and handling techniques.

Big Data 98

Big Data Bytes Data Governance Raw Data 98

Data Engineering Weekly

DECEMBER 10, 2023

[link] Netflix: Diving Deeper into Psyberg: Stateless vs Stateful Data Processing Netflix wrote a deep-dive article about Psyberg’s incremental data processing pipeline framework. The blog discusses Psyberg’s two operational models, stateless & stateful data processing.

Data Engineering 76

Data Engineering Data Engineer Engineering Metadata 76

Towards Data Science

NOVEMBER 4, 2023

The data engineering landscape is constantly changing but major trends seem to remain the same. How to Become a Data Engineer As a data engineer, I am tasked to design efficient data processes almost every day. It was created by Spotify to manage massive data processing workloads.

Data Engineering 86

Data Engineering Data Engineer Engineering BI 86

Marc Lamberti

SEPTEMBER 22, 2023

Airflow stores metadata in it (DAG runs, XComs, Task instances, etc. It is also essential to understand what Airflow is not – it’s neither a streaming solution nor a data processing framework. The Meta database: Database compatible with SqlAlchemy.

Data Pipeline 130

Data Pipeline Python Metadata Database 130

LinkedIn Engineering

JULY 19, 2023

Open source data lakehouse deployments are built on the foundations of compute engines (like Apache Spark, Trino, Apache Flink), distributed storage (HDFS, cloud blob stores), and metadata catalogs / table formats (like Apache Iceberg, Delta, Hudi, Apache Hive Metastore). Tables are governed as per agreed upon company standards.

Big Data 78

Big Data Data Management Management Metadata 78

RandomTrees

FEBRUARY 6, 2024

Serving: Delivering Data with Precision: The seamless process significantly enhances the user experience, allowing for intuitive data exploration and decision-making without requiring technical query language knowledge. The significance of GenAI 1.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Cloudera

APRIL 1, 2024

We scored the highest in hybrid, intercloud, and multi-cloud capabilities because we are the only vendor in the market with a true hybrid data platform that can run on any cloud including private cloud to deliver a seamless, unified experience for all data, wherever it lies.

Cloud 103

Cloud Unstructured Data Metadata Datasets 103

Cloudera

JULY 19, 2023

It is a replicated, highly-available service that is responsible for managing the metadata for all objects stored in Ozone. As Ozone scales to exabytes of data, it is important to ensure that Ozone Manager can perform at scale. The tool reads only the metadata for objects in a cluster with around 100 million keys.

Management 70

Management Metadata Datasets Architecture 70

Ascend.io

APRIL 19, 2023

The “modern data stack” has become increasingly prominent in recent years, promising a streamlined approach to data processing. Intelligent pipelines : Reducing dependencies and enabling more efficient data processing, intelligent pipelines allow teams to focus on what truly matters: creating impactful data products.

Metadata 52

Metadata Business Analyst Hadoop Software Engineer 52

The Modern Data Company

APRIL 15, 2024

The Role of a Data Model Explained Think of a data model as the ultimate organizer in the vast library of your company’s data. Its job, from its position near the end of the data processing line, is similar to that of a librarian who: Answers queries from various departments looking for specific insights.

Government 52

Government Metadata Data Data Lake 52

Cloudera

DECEMBER 15, 2022

With in-place table migration, you can rapidly convert to Iceberg tables since there is no need to regenerate data files. Only metadata will be regenerated. Newly generated metadata will then point to source data files as illustrated in the diagram below. . Data quality using table rollback. Metadata management .

Cloud 77

Cloud Metadata Google Cloud Data Warehouse 77

Databand.ai

JULY 19, 2023

This capability is particularly useful in complex data landscapes, where data may pass through multiple systems and transformations before reaching its final destination Impact analysis: When changes are made to data sources or data processing systems, it’s critical to understand the potential impact on downstream processes and reports.

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52

Cloudyard

APRIL 4, 2024

However, the volume of daily transaction data poses challenges in effectively segmenting customers and optimizing engagement. This blog post explores how Snowpark, a powerful tool for data processing within Snowflake, can be used to perform RFM segmentation and unlock actionable customer insights.

Retail 40

Retail Data Ingestion Metadata Datasets 40

ProjectPro

FEBRUARY 8, 2023

AWS Glue is a widely-used serverless data integration service that uses automated extract, transform, and load ( ETL ) methods to prepare data for analysis. It offers a simple and efficient solution for data processing in organizations. Then, Glue writes the job's metadata into the embedded AWS Glue Data Catalog.

AWS 98

AWS Scala Metadata Data Lake 98

Precisely

SEPTEMBER 11, 2023

By 2025, 80% of mainstream data quality vendors will expand their product capabilities to provide greater data insights by discovering patterns, trends, data relationships, and error resolution. Context-based bots expedite information retrieval from documentation, knowledge bases, or metadata.

Metadata 52

Metadata Data Integration Datasets Data Analysis Tools 52

Data Engineering Weekly

MAY 16, 2023

Architectural Patterns for Data Quality Now we understand the trade-off between speed & correctness and the difference between data testing and observability. Let’s talk about the data processing types. Two-Phase WAP The Two-Phase WAP, as the name suggests, follows two copy processes.

Engineering 110

Engineering Kafka Data Pipeline Data Warehouse 110

Cloudera

OCTOBER 7, 2021

Application Logic: Application logic refers to the type of data processing, and can be anything from analytical or operational systems to data pipelines that ingest data inputs, apply transformations based on some business logic and produce data outputs.

Architecture 123

Architecture Metadata Government Kafka 123

Ascend.io

FEBRUARY 28, 2024

Metadata Management for Enhanced Machine Interpretation Data engineering extends its importance to the realm of metadata management, providing AI models with essential context about data definitions, classifications, and governance policies.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Monte Carlo

MAY 30, 2023

What makes Iceberg tables so appealing is they can store raw data at scale to support typical data lake use cases, but they also have data lakehouse-like properties as well such as well-organized metadata, ACID transactions, and critical features like time travel.

Metadata 52

Metadata Raw Data Data Lake Data 52

AltexSoft

AUGUST 22, 2022

Support for different data types and use cases. A data fabric supports structured, unstructured, and semi-structured data whether it comes in real-time or generated in batches. It is also driven by metadata, which it uses to recognize patterns, map data, and perform continuous analysis. How data fabric works.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

Snowflake

NOVEMBER 1, 2023

We recently announced Snowpark ML Modeling API (generally available soon), which enables the use of popular ML frameworks such as Scikit-learn and XGBoost for feature engineering and model training without moving data out of Snowflake. Snowpark ML enables intuitive model development using these frameworks through familiar Python APIs.

Building 105

Building Python SQL Programming Language 105

Data Engineering Podcast

JANUARY 30, 2022

Matt Harrison is a Python expert with a long history of working with data who now spends his time on consulting and training. You can observe your pipelines with built in metadata search and column level lineage. What are some of the utility features that you have found most helpful for data processing?

Data Engineering 100

Data Engineering Data Engineer Engineering Data Pipeline 100

Monte Carlo

FEBRUARY 12, 2024

Monte Carlo has been the leader in data observability to improve the data reliability of structured and unstructured data processed by modern data platforms built around warehouses, lakes, and lakehouses. The category was introduced with five original pillars: Freshness : Did the data arrive when expected?

Database 72

Database Unstructured Data Data Pipeline Metadata 72

Monte Carlo

FEBRUARY 21, 2023

In this post, we’ll discuss what, exactly, a data fabric is, how other companies have used it, and how you can build one at your company. Table of Contents What is a data fabric? Reduced reliance on IT Integral to a data fabric is a set of pre-built models and algorithms that expedite data processing.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Monte Carlo

FEBRUARY 21, 2023

In this post, we’ll discuss what, exactly, a data fabric is, how other companies have used it, and how you can build one at your company. Table of Contents What is a data fabric? Reduced reliance on IT Integral to a data fabric is a set of pre-built models and algorithms that expedite data processing.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52