Data Engineering Podcast

SEPTEMBER 17, 2023

Summary A significant amount of time in data engineering is dedicated to building connections and semantic meaning around pieces of information. Linked data technologies provide a means of tightly coupling metadata with raw information. Go to dataengineeringpodcast.com/materialize today to get 2 weeks free!

Building 189

Building SQL BI Python 189

Data Engineering Weekly

NOVEMBER 3, 2024

The challenges around memory, data size, and runtime are exciting to read. Sampling is an obvious strategy for data size, but the layered approach and dynamic inclusion of dependencies are some key techniques I learned with the case study. This count helps to ensure data consistency when deleting and compacting segments.

Data Engineering 62

Data Engineering Data Engineer Engineering Pipeline-centric 62

François Nguyen

MARCH 22, 2021

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. How do we build data products ? How can we interoperate between the data domains ?

Technology 130

Technology Architecture Google Cloud Metadata 130

Ascend.io

DECEMBER 4, 2024

As we approach 2025, data teams find themselves at a pivotal juncture. The rapid evolution of technology and the increasing demand for data-driven insights have placed immense pressure on these teams. The future of data teams depends on their ability to adapt to new challenges and seize emerging opportunities.

Data Pipeline 52

Data Pipeline Metadata Data Workflow Data 52

Data Engineering Podcast

DECEMBER 18, 2022

Summary One of the reasons that data work is so challenging is because no single person or team owns the entire process. This introduces friction in the process of collecting, processing, and using data. In order to reduce the potential for broken pipelines some teams have started to adopt the idea of data contracts.

Metadata 130

Metadata Business Intelligence Data Lake BI 130

Data Engineering Podcast

JULY 17, 2022

Summary There are extensive and valuable data sets that are available outside the bounds of your organization. Whether that data is public, paid, or scraped it requires investment and upkeep to acquire and integrate it with your systems. Atlan is the metadata hub for your data ecosystem.

Data Management 130

Data Management Management Metadata MongoDB 130

Ascend.io

JULY 11, 2024

Metadata is the information that provides context and meaning to data, ensuring it’s easily discoverable, organized, and actionable. It enhances data quality, governance, and automation, transforming raw data into valuable insights. This is what managing data without metadata feels like. Chaos, right?

Metadata 52

Metadata IT Government High Quality Data 52

Data Engineering Podcast

AUGUST 28, 2022

For data engineers, this is a monumental undertaking. 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. The only thing worse than having bad data is not knowing that you have it.

Data Engineering 100

Data Engineering Data Engineer MongoDB Metadata 100

Data Engineering Podcast

NOVEMBER 26, 2023

Summary Building a data platform that is enjoyable and accessible for all of its end users is a substantial challenge. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles. Data lakes are notoriously complex. With Materialize, you can!

Architecture 147

Architecture Data Lake High Quality Data SQL 147

Data Engineering Podcast

JULY 31, 2022

Summary Data lineage is the roadmap for your data platform, providing visibility into all of the dependencies for any report, machine learning model, or data warehouse table that you are working with. Atlan is the metadata hub for your data ecosystem.

IT 100

IT Metadata MongoDB MySQL 100

Data Engineering Podcast

SEPTEMBER 18, 2022

Summary There is a constant tension in business data between growing siloes, and breaking them down. Even when a tool is designed to integrate information as a guard against data isolation, it can easily become a silo of its own, where you have to make a point of using it to seek out information.

Building 100

Building Metadata MongoDB MySQL 100

Data Engineering Podcast

AUGUST 5, 2019

Summary Data is only valuable if you use it for something, and the first step is knowing that it is available. As organizations grow and data sources proliferate it becomes difficult to keep track of everything, particularly for analysts and data scientists who are not involved with the collection and management of that information.

MongoDB 100

MongoDB PostgreSQL Metadata Data 100

Data Engineering Podcast

FEBRUARY 20, 2022

Summary The life sciences as an industry has seen incredible growth in scale and sophistication, along with the advances in data technology that make it possible to analyze massive amounts of genomic information. RudderStack’s smart customer data pipeline is warehouse-first. How does it work?

Systems 100

Systems Software Engineering Software Engineer Data Warehouse 100

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 104

Metadata Data Pipeline Scala Data Process 104

Data Engineering Podcast

JANUARY 30, 2022

Summary Pandas is a powerful tool for cleaning, transforming, manipulating, or enriching data, among many other potential uses. As a result it has become a standard tool for data engineers for a wide range of applications. Today’s episode is Sponsored by Prophecy.io – the low-code data engineering platform for the cloud.

Data Engineering 100

Data Engineering Data Engineer Engineering Python 100

Data Engineering Podcast

APRIL 5, 2021

Summary One of the biggest obstacles to success in delivering data products is cross-team collaboration. This introduces a barrier to communication that is difficult to overcome, particularly in teams that have not reached a significant level of maturity in their data journey.

Data Warehouse 100

Data Warehouse Data Pipeline BI Metadata 100

Data Engineering Weekly

DECEMBER 29, 2022

Data catalogs are the most expensive data integration systems you never intended to build. Data Catalog as a passive web portal to display metadata requires significant rethinking to adopt modern data workflow, not just adding “modern” in its prefix. How happy are you with your data catalogs?

Metadata 62

Metadata Data Warehouse ETL Tools Data Workflow 62

Netflix Tech

OCTOBER 27, 2020

By Tianlong Chen and Ioannis Papapanagiotou Netflix has more than 195 million subscribers that generate petabytes of data everyday. Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy.

Data Warehouse 103

Data Warehouse Datasets Data Big Data 103

AltexSoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Which Big Data tasks does Spark solve most effectively? How does it work? cost-effectiveness.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Data Engineering Weekly

DECEMBER 16, 2024

As we reflect on 2024, the data engineering landscape has undergone significant transformations driven by technological advancements, changing business needs, and the meteoric rise of artificial intelligence. This comprehensive analysis examines the key trends and patterns that shaped data engineering practices throughout the year.

Data Engineering 62

Data Engineering Data Engineer Engineering Unstructured Data 62

Data Engineering Podcast

MAY 3, 2021

Summary The Data industry is changing rapidly, and one of the most active areas of growth is automation of data workflows. Taking cues from the DevOps movement of the past decade data professionals are orienting around the concept of DataOps. And don’t forget to thank them for their continued support of this show!

Data Warehouse 100

Data Warehouse Data Pipeline BI Metadata 100

RandomTrees

SEPTEMBER 17, 2024

In the realm of big data and AI, managing and securing data assets efficiently is crucial. Databricks addresses this challenge with Unity Catalog, a comprehensive governance solution designed to streamline and secure data management across Databricks workspaces. What is Unity Catalog? Advantages of the Unity Catalog 1.

Data Governance 52

Data Governance Government Metadata Machine Learning 52

Data Engineering Weekly

JANUARY 15, 2023

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. 2023 predictions from the panel are; Unified metadata becomes kingmaker.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Netflix Tech

OCTOBER 18, 2022

by Jun He , Akash Dwivedi , Natallia Dzenisenka , Snehal Chennuru , Praneeth Yenugutala , Pawan Dixit At Netflix, Data and Machine Learning (ML) pipelines are widely used and have become central for the business, representing diverse use cases that go beyond recommendations, predictions and data transformations.

Java 87

Java Data Machine Learning Systems 87

Workfall

JUNE 12, 2023

In this dynamic realm of data engineering, a monumental challenge takes centre stage: efficiently managing the ever-changing tides of real-time data. Data, the lifeblood of organisations, holds the key to unlocking untapped potential and propelling businesses forward. In this blog, we will cover: What Is CDC and Its Benefits?

Telecommunication 80

Telecommunication Metadata Healthcare Finance 80

Data Engineering Weekly

OCTOBER 30, 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. The highlights are that 59% of folks think data catalogs are sometimes helpful.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 52

Hepta Analytics

FEBRUARY 14, 2022

DE Zoomcamp 2.2.1 – Introduction to Workflow Orchestration Following last weeks blog , we move to data ingestion. We already had a script that downloaded a csv file, processed the data and pushed the data to postgres database. This week, we got to think about our data ingestion design.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

Data Engineering Weekly

MARCH 11, 2023

We are back in our Data Engineering Weekly Radio for edition #120. We will take 2 or 3 articles from each week's Data Engineering Weekly edition and go through an in-depth analysis. We discuss an article by Colin Campbell highlighting the need for a data catalog and the market scope for data contract solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering High Quality Data 52

Ascend.io

DECEMBER 11, 2023

Are you dealing with a scattered data environment, with complex pipelines that seem to go everywhere and nowhere at the same time? Is your data stuck in separate areas within your company, making it hard to use effectively? In other words, you need data orchestration. What Is Data Orchestration?

Data Workflow 52

Data Workflow Data Pipeline Data Lake Data 52

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 91

Process Data Pipeline Datasets SQL 91

Cloudera

AUGUST 21, 2020

Live data-streaming offers businesses exciting new opportunities to transform the way they operate, leveraging real-time insights to drive better decision making and enhance operational efficiency. To start off, what are the advantages of a forward-looking data-in-motion strategy?

Banking 62

Banking Kafka Cloud Storage Government 62

Monte Carlo

OCTOBER 1, 2024

For the sixth consecutive quarter, Monte Carlo has been named G2’s #1 Data Observability Platform. Filling our trophy case with G2 badges is wonderful, but mostly, we’re delighted to know our products are helping our customers create more value from data and achieve their goals.

Database 52

Database Metadata Software Engineering Software Engineer 52

Cloudera

FEBRUARY 11, 2019

The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market. Moving processing to data creates the need for multi-cloud. 3. Expansion beyond core data management. Cloudera believes disruption persists around multi-cloud.

Data Management 43

Data Management Management Metadata Government 43

Monte Carlo

MAY 14, 2024

As organizations seek greater value from their data, data architectures are evolving to meet the demand — and table formats are no exception. But while the modern data stack , and how it’s structured, may be evolving, the need for reliable data is not — and that also has some real implications for your data platform.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

dbt Developer Hub

OCTOBER 14, 2021

It uses the dbt Cloud Metadata API to surface metadata from dbt right in Hex, letting you quickly get the context you need on things like data freshness without juggling multiple apps and browser tabs. Everyone is talking about the next layer of the modern data stack. Hex just launched an integration with dbt!

Metadata 52

Metadata BI Software Engineering Software Engineer 52

Monte Carlo

SEPTEMBER 20, 2022

Data teams spend millions per year tackling the persistent challenges of data downtime. However, it’s often the leanest data teams that feel the sting of poor data quality the most. Prefect, the company behind the eponymous data workflow management system, is on a mission to make coordinating data flows easier.

Big Data 52

Big Data Data Warehouse Data Data Governance 52

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows. As a result, they can be slow, inefficient, and prone to errors.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52