Data Engineering Podcast

FEBRUARY 4, 2024

In this episode Yingjun Wu explains how it is architected to power analytical workflows on continuous data flows, and the challenges of making it responsive and scalable. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex.

SQL 173

SQL Data Lake High Quality Data Machine Learning 173

Data Engineering Podcast

JANUARY 21, 2024

In this episode Tasso Argyros, CEO of ActionIQ, gives a summary of the major epochs in database technologies and how he is applying the capabilities of cloud data warehouses to the challenge of building more comprehensive experiences for end-users through a modern customer data platform (CDP).

Data Lake 147

Data Lake High Quality Data NoSQL Data Warehouse 147

Data Engineering Podcast

JUNE 9, 2024

Data lakes are notoriously complex. Your host is Tobias Macey and today I'm interviewing Ronen Korman and Stav Elkayam about pulling back the curtain on your real-time data streams by bringing intuitive observability to Flink streams Interview Introduction How did you get involved in the area of data management?

Process 147

Process Data Lake High Quality Data Machine Learning 147

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. How do we build data products ? How can we interoperate between the data domains ? The data domain Discovery portal with all the metadata on the data life cycle 4.Federated

Technology 130

Technology Architecture Google Cloud Metadata 130

Monte Carlo

AUGUST 25, 2023

Different vendors offering data warehouses, data lakes, and now data lakehouses all offer their own distinct advantages and disadvantages for data teams to consider. So let’s get to the bottom of the big question: what kind of data storage layer will provide the strongest foundation for your data platform?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Monte Carlo

OCTOBER 31, 2024

There are dozens of data engineering tools available on the market, so familiarity with a wide variety of these can increase your attractiveness as an AI data engineering candidate. Data Storage Solutions As we all know, data can be stored in a variety of ways.

Data Engineering 52

Data Engineering Data Engineer Engineering Unstructured Data 52

Data Engineering Podcast

SEPTEMBER 23, 2018

Using the metaphor of a museum curator carefully managing the precious resources on display and in the vaults, he discusses the various layers of an enterprise data strategy. In terms of infrastructure, what are the components of a modern data architecture and how has that changed over the years?

Data Lake 100

Data Lake Data Warehouse Data Architecture Architecture 100

Towards Data Science

DECEMBER 4, 2023

A robust data infrastructure is a must-have to compete in the F1 business. We’ll build a data architecture to support our racing team starting from the three canonical layers : Data Lake, Data Warehouse, and Data Mart. Data Marts There is a thin line between Data Warehouses and Data Marts.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Lake 98

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake? Consistency of data throughout the data lake.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Cloudera

MAY 28, 2024

This form of architecture can handle data in all forms—structured, semi-structured, unstructured—blending capabilities from data warehouses and data lakes into data lakehouses.

Data Architecture 88

Data Architecture Architecture Data Lake Data Warehouse 88

Monte Carlo

APRIL 24, 2023

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Monte Carlo

APRIL 1, 2021

Over the past few years, data lakes have emerged as a must-have for the modern data stack. But while the technologies powering our access and analysis of data have matured, the mechanics behind understanding this data in a distributed environment have lagged behind. Data discovery tools and platforms can help.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Government 52

Monte Carlo

APRIL 4, 2023

Data mesh vs data warehouse is an interesting framing because it is not necessarily a binary choice depending on what exactly you mean by data warehouse (more on that later). Despite their differences, however, both approaches require high-quality, reliable data in order to function. What is a Data Mesh?

Data Warehouse 52

Data Warehouse Data Governance Data Architecture 52

Precisely

JUNE 24, 2024

The Precisely team recently had the privilege of hosting a luncheon at the Gartner Data & Analytics Summit in London. It was an engaging gathering of industry leaders from various sectors, who exchanged valuable insights into crucial aspects of data governance, strategy, and innovation.

Food 94

Food Data Analytics Pharmaceutical Consulting 94

DareData

JULY 5, 2023

Learn how we build data lake infrastructures and help organizations all around the world achieving their data goals. In today's data-driven world, organizations are faced with the challenge of managing and processing large volumes of data efficiently.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

Data Engineering Podcast

DECEMBER 18, 2022

Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. RudderStack helps you build a customer data platform on your warehouse or data lake. RudderStack helps you build a customer data platform on your warehouse or data lake.

Data Lake 100

Data Lake Data Warehouse Data Pipeline MongoDB 100

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. What is a data lake?

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Striim

SEPTEMBER 11, 2024

In an ETL-based architecture, data is first extracted from source systems, then transformed into a structured format, and finally loaded into data stores, typically data warehouses. This method is advantageous when dealing with structured data that requires pre-processing before storage.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Monte Carlo

JANUARY 23, 2023

When it comes to the data community, there’s always a debate broiling about something— and right now “data mesh vs data lake” is right at the top of that list. In this post we compare and contrast the data mesh vs data lake to illustrate the benefits of each and help discover what’s right for your data platform.

Data Lake 52

Data Lake Architecture Business Intelligence Unstructured Data 52

Monte Carlo

NOVEMBER 14, 2023

Apache Iceberg is an open source data lakehouse table format developed by the data engineering team at Netflix to provide a faster and easier way to process large datasets at scale. It is designed to be easily queryable with SQL even for large analytic tables (we’re talking petabytes of data). Limited data type support.

Data Lake 64

Data Lake Metadata Data Warehouse SQL 64

Monte Carlo

JANUARY 24, 2024

Data is among your company’s most valuable commodities, but only if you know how to manage it. More data, more access to data, and more regulations mean data governance has become a higher-stakes game. Data Governance Trends The biggest data governance trend isn’t really a trend at all—rather, it’s a state of mind.

Data Governance 52

Data Governance Government Data Lake Data Architecture 52

DataKitchen

DECEMBER 7, 2021

This book is not available until January 2022, but considering all the hype around the data mesh, we expect it to be a best seller. In the book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today’s organizations.

Data Governance 98

Data Governance Big Data Data Science Government 98

Data Engineering Podcast

FEBRUARY 24, 2020

Snowplow takes care of everything from installing your pipeline in a couple of hours to upgrading and autoscaling so you can focus on your exciting data projects. Your team will get the most complete, accurate and ready-to-use behavioral web and mobile data, delivered into your data warehouse, data lake and real-time streams.

IT 100

IT Data Lake Data Pipeline Media 100

Cloudera

AUGUST 20, 2024

Whether it’s rapidly rising costs, an inefficient and outdated data infrastructure, or serious gaps in data governance, there are myriad reasons why organizations are struggling to move past adoption and achieve AI at scale in their enterprises.

Government 82

Government Data Lake Data Governance Data Architecture 82

Cloudera

NOVEMBER 12, 2020

Your sunk costs are minimal and if a workload or project you are supporting becomes irrelevant, you can quickly spin down your cloud data warehouses and not be “stuck” with unused infrastructure. Cloud deployments for suitable workloads gives you the agility to keep pace with rapidly changing business and data needs.

Cloud 104

Cloud Data Warehouse Banking Data 104

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Management Data Lake Data Governance 52

Data Engineering Podcast

OCTOBER 5, 2020

Summary Analytical workloads require a well engineered and well maintained data integration process to ensure that your information is reliable and up to date. Building a real-time pipeline for your data lakes and data warehouses is a non-trivial effort, requiring a substantial investment of time and energy.

Data Integration 100

Data Integration Kafka Data Lake Machine Learning 100

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59

AltexSoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Data warehouse vs data lake vs data lakehouse: What’s the difference.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Cloudera

SEPTEMBER 15, 2022

Mark: The first element in the process is the link between the source data and the entry point into the data platform. At Ramsey International (RI), we refer to that layer in the architecture as the foundation, but others call it a staging area, raw zone, or even a source data lake. What is a data fabric?

Data Lake 83

Data Lake Analytics Application Cloud Storage Architecture 83

Data Science Blog: Data Engineering

MAY 20, 2024

Enter AnalyticsCreator AnalyticsCreator, a powerful tool for data management, brings a new level of efficiency and reliability to the CI/CD process. It offers full BI-Stack Automation, from source to data warehouse through to frontend. It supports a holistic data model, allowing for rapid prototyping of various models.

Data Pipeline 52

Data Pipeline BI Data Lake Data Warehouse 52

AltexSoft

NOVEMBER 23, 2021

Before we get into more detail, let’s determine how data virtualization is different from another, more common data integration technique — data consolidation. Data virtualization vs data consolidation. You can learn more about how such data pipelines are built in our video about data engineering.

Process 69

Process Data Lake Metadata Data Warehouse 69