Data Engineering Podcast

SEPTEMBER 1, 2021

Summary The Presto project has become the de facto option for building scalable open source analytics in SQL for the data lake. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform.

Data Lake 100

Data Lake Cloud AWS SQL 100

Data Engineering Podcast

SEPTEMBER 11, 2022

Summary Data engineering systems are complex and interconnected with myriad and often opaque chains of dependencies. In order to turn this into a tractable problem one approach is to define and enforce contracts between producers and consumers of data. Atlan is the metadata hub for your data ecosystem.

Systems 100

Systems Metadata Building MongoDB 100

Data Engineering Podcast

DECEMBER 19, 2021

Summary Building a well managed data ecosystem for your organization requires a holistic view of all of the producers, consumers, and processors of information. The team at Metaphor are building a fully connected metadata layer to provide both technical and social intelligence about your data. Missing data?

Systems 100

Systems Building Metadata Data Warehouse 100

Grouparoo

JANUARY 11, 2022

When it comes to storing large volumes of data, a simple database will be impractical due to the processing and throughput inefficiencies that emerge when managing and accessing big data. This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Netflix Tech

MARCH 7, 2024

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

Systems 90

Systems Media Machine Learning Data Warehouse 90

Data Engineering Podcast

APRIL 24, 2022

Summary There are very few tools which are equally useful for data engineers, data scientists, and machine learning engineers. WhyLogs is a powerful library for flexibly instrumenting all of your data systems to understand the entire lifecycle of your data from source to productionized model.

Machine Learning 100

Machine Learning Systems Data Lake Metadata 100

Data Engineering Podcast

JUNE 17, 2023

In data systems one of the core architectural exercises is data modeling, which can have significant impacts on what is and is not possible for downstream use cases. By incorporating column-level lineage in the data modeling process it encourages a more robust and well-informed design.

Data Lake 130

Data Lake Metadata Machine Learning Data Architecture 130

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

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

Data Engineering Podcast

MAY 22, 2022

Summary Machine learning has become a meaningful target for data applications, bringing with it an increase in the complexity of orchestrating the entire data flow. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform.

Machine Learning 130

Machine Learning Data Engineering Data Engineer Cloud 130

ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data Warehouse Architecture What is a Data lake?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Monte Carlo

MAY 31, 2022

When a data pipeline breaks, data engineers need to immediately understand where the rupture occurred and what has been impacted. Data downtime is costly. Field-level data lineage (not necessarily Spark lineage) with hundreds of connections between objects in upstream and downstream tables. Image courtesy of Monte Carlo.

Data Lake 52

Data Lake Building Scala Metadata 52

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

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. Metadata layer 4.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. Metadata layer 4.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Towards Data Science

FEBRUARY 9, 2024

How to build a modern, scalable data platform to power your analytics and data science projects (updated) Table of Contents: What’s changed? The Platform Integration Data Store Transformation Orchestration Presentation Transportation Observability Closing What’s changed? Over the last three years, my life has changed as well.

Building 80

Building Transportation Data Lake Metadata 80

Data Engineering Podcast

NOVEMBER 27, 2022

Summary The data ecosystem has been growing rapidly, with new communities joining and bringing their preferred programming languages to the mix. This has led to inefficiencies in how data is stored, accessed, and shared across process and system boundaries. Atlan is the metadata hub for your data ecosystem.

Data Process 100

Data Process Process Metadata Business Intelligence 100

Data Engineering Weekly

MARCH 24, 2024

link] Kai Waehner: The Data Streaming Landscape 2024 This is a comprehensive overview of the state of the data streaming landscape in 2024. The author goes beyond comparing the tools to various offerings from streaming vendors in stream processing and Kafka protocol-supported systems.

Data Engineering 62

Data Engineering Data Engineer Engineering Metadata 62

Data Engineering Podcast

DECEMBER 4, 2022

Summary Business intelligence is the foremost application of data in organizations of all sizes. Zing Data is building a mobile native platform for business intelligence. Atlan is the metadata hub for your data ecosystem. And don’t forget to thank them for their continued support of this show!

Business Intelligence 100

Business Intelligence Metadata BI MongoDB 100

Data Engineering Podcast

DECEMBER 29, 2022

Summary Making effective use of data requires proper context around the information that is being used. Rehgan Avon co-founded AlignAI to help address this challenge through a more purposeful platform designed to collect and distribute the knowledge of how and why data is used in a business. Missing data? Stale dashboards?

Management 130

Management Metadata Business Intelligence Data Lake 130

Data Engineering Podcast

DECEMBER 25, 2022

Summary Five years of hosting the Data Engineering Podcast has provided Tobias Macey with a wealth of insight into the work of building and operating data systems at a variety of scales and for myriad purposes. Atlan is the metadata hub for your data ecosystem. Missing data? Struggling with broken pipelines?

Building 100

Building Metadata Business Intelligence Data Lake 100

Ascend.io

APRIL 22, 2024

At Ascend, we believe it’s time to rethink data engineering from the ground up. As the world of data continues to evolve at a breakneck pace, we are thrilled to announce the next revolutionary step in our journey – Project Inception. Read More: The State of Data Engineering in 2023: Does Your Data Program Stack Up?

Project 52

Project Metadata Data Pipeline Data Engineering 52

Data Engineering Podcast

MARCH 27, 2022

Summary Data governance is a practice that requires a high degree of flexibility and collaboration at the organizational and technical levels. The growing prominence of cloud and hybrid environments in data management adds additional stress to an already complex endeavor.

Data Governance 130

Data Governance Government Cloud Building 130

Cloudera

DECEMBER 16, 2022

We are pleased to announce that Cloudera has been named a Leader in the 2022 Gartner ® Magic Quadrant for Cloud Database Management Systems. We’re proud to be recognized for the data management and data analytics innovations we have delivered in the new Cloudera Data Platform (CDP). This is unique.

Database 90

Database Cloud Systems Management 90

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

LinkedIn Engineering

JULY 19, 2023

Co-Authors: Sumedh Sakdeo , Lei Sun , Sushant Raikar , Stanislav Pak , and Abhishek Nath Introduction At LinkedIn, we build and operate an open source data lakehouse deployment to power Analytics and Machine Learning workloads. Unfortunately, there is currently no system in open source that unifies them through a single control plane.

Big Data 78

Big Data Data Management Management Metadata 78

Data Engineering Podcast

FEBRUARY 27, 2022

Summary Building a data platform is a complex journey that requires a significant amount of planning to do well. In this episode Tobias Macey, the host of the show, reflects on his plans for building a data platform and what he has learned from running the podcast that is influencing his choices. That’s Timescale.

Designing 100

Designing Metadata Data Lake Relational Database 100

Data Engineering Podcast

SEPTEMBER 4, 2022

Summary Data observability is a product category that has seen massive growth and adoption in recent years. Monte Carlo is in the vanguard of companies who have been enabling data teams to observe and understand their complex data systems. Atlan is the metadata hub for your data ecosystem.

IT 100

IT Metadata MongoDB MySQL 100

Cloudera

AUGUST 30, 2022

Data is the fuel that drives government, enables transparency, and powers citizen services. That should be easy, but when agencies don’t share data or applications, they don’t have a unified view of people. Legacy data sharing involves proliferating copies of data, creating data management, and security challenges.

Data Architecture 78

Data Architecture Architecture Data Lake NoSQL 78

Cloudera

JUNE 30, 2022

We are excited to announce the general availability of Apache Iceberg in Cloudera Data Platform (CDP). These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. Why integrate Apache Iceberg with Cloudera Data Platform?

Data Lake 86

Data Lake Business Intelligence Metadata Data Warehouse 86

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes. Iterations of the lakehouse.

Data Lake 92

Data Lake Data Warehouse BI SQL 92

Monte Carlo

MARCH 4, 2024

As any data engineer currently rolling their eyes would tell you, the reality has long been more nuanced. These questions just scratch the surface of the painful delightfully complex world of data engineering. These solutions also provide you the data lineage and root cause analysis insights you need to understand how to fix them.

Metadata 52

Metadata Data Lake Data Warehouse Data Engineering 52

Data Engineering Podcast

JUNE 17, 2021

Summary Working with unstructured data has typically been a motivation for a data lake. Kirk Marple has spent years working with data systems and the media industry, which inspired him to build a platform for automatically organizing your unstructured assets to make them more valuable. No more scripts, just SQL.

Unstructured Data 100

Unstructured Data Data Warehouse Metadata Media 100

Cloudera

NOVEMBER 17, 2022

We needed a solution to manage our data at scale, to provide greater experiences to our customers. With Cloudera Data Platform, we aim to unlock value faster and offer consistent data security and governance to meet this goal. HBL aims to double its banked customers by 2025. “ Smooth, hassle-free deployment in just six weeks.

Banking 84

Banking Management Data Lake Professional Services 84

Precisely

OCTOBER 16, 2023

Big data analytics, IoT, AI, and machine learning are revolutionizing the way businesses create value and competitive advantage. For organizations that continue to rely on mainframe systems to process their most mission-critical workloads, the digital revolution demands new approaches to integration.

Cloud 70

Cloud Cloud Computing Metadata Data Governance 70

AltexSoft

AUGUST 22, 2022

The landscape of enterprise data is fragmented. Organizations have data stored in public and private clouds, as well as in various on-premises data repositories. Some would say that it’s not a big deal, however, these mixed environments have resulted in the complexities of managing disjointed data and business processes.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

Cloudera

APRIL 22, 2021

Today’s enterprise data analytics teams are constantly looking to get the best out of their platforms. Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Separates control and data plane enabling high performance.

Pipeline-centric 100

Pipeline-centric Data Lake Hadoop Metadata 100