Data Engineering Podcast

JUNE 25, 2023

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management RudderStack helps you build a customer data platform on your warehouse or data lake. Support Data Engineering Podcast RudderStack also supports real-time use cases.

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Start Data Engineering

MAY 11, 2022

Data lake structure 5. Loading user purchase data into the data warehouse 5.2 Loading classified movie review data into the data warehouse 5.3 Introduction 2. Objective 3. Prerequisite 4.2 AWS Infrastructure costs 4.3 Code walkthrough 5.1 Generating user behavior metric 5.4. Checking results 6.

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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. Who are the data engineers?

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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?

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U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. Essentially, this is the difference between a lake and a warehouse. On the other hand, a data warehouse contains historical data that has been cleaned and arranged. .

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Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Data Engineering Podcast

MARCH 10, 2023

In this episode Priyendra Deshwal explains how NetSpring is designed to empower your product and data teams to build and explore insights around your products in a streamlined and maintainable workflow. As a listener to the Data Engineering Podcast you can get a special discount of 20% off your ticket by using the promo code dataengpod20.

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Data Warehouse Data Lake Machine Learning Data Science 130

Data Engineering Podcast

JUNE 4, 2023

Summary A significant portion of the time spent by data engineering teams is on managing the workflows and operations of their pipelines. Agile Data Engine is a platform designed to handle the infrastructure side of the DataOps equation, as well as providing the insights that you need to manage the human side of the workflow.

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Data Engineering Podcast

FEBRUARY 5, 2023

In that time there have been a number of generational shifts in how data engineering is done. Sign up now for early access to Materialize and get started with the power of streaming data with the same simplicity and low implementation cost as batch cloud data warehouses.

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Data Engineering Podcast

FEBRUARY 18, 2024

Summary A data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Data lakes are notoriously complex. Visit: dataengineeringpodcast.com/data-council today. Your first 30 days are free!

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Analytics Vidhya

FEBRUARY 25, 2023

Introduction A data lake is a centralized and scalable repository storing structured and unstructured data. The need for a data lake arises from the growing volume, variety, and velocity of data companies need to manage and analyze.

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Data Engineering Podcast

AUGUST 3, 2021

Summary Data lake architectures have largely been biased toward batch processing workflows due to the volume of data that they are designed for. With more real-time requirements and the increasing use of streaming data there has been a struggle to merge fast, incremental updates with large, historical analysis.

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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?

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Data Engineering Weekly

JULY 7, 2024

Learn More → Notion: Building and scaling Notion’s data lake Notion writes about scaling the data lake by bringing critical data ingestion operations in-house. Hudi seems to be a de facto choice for CDC data lake features. Notion migrated the insert heavy workload from Snowflake to Hudi.

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Hevo

JULY 25, 2024

A data lake is a central storage place for an organization’s data in its original format. Unlike data warehouses, data lakes can handle all kinds of data, including unstructured and semi-structured data like images, video, audio, and documents.

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Towards Data Science

DECEMBER 4, 2023

A Glossary with Use Cases for First-Timers in Data Engineering An happy Data Engineer at work Are you a data engineering rookie interested in knowing more about modern data infrastructures? In this guide Data Engineering meets Formula 1. Data models are built around business needs.

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Data Engineering Weekly

SEPTEMBER 22, 2024

I’m fairly confident that a framework that supports a deterministic way of building a data pipeline and a conversational way of building business logic is the future of data pipeline engineering. link] Sponsored: IMPACT - Have you seen the agenda for IMPACT: The Data Observability Summit yet?

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Data Engineering Podcast

MAY 13, 2021

Summary There is a lot of attention on the database market and cloud data warehouses. While they provide a measure of convenience, they also require you to sacrifice a certain amount of control over your data. Firebolt is the fastest cloud data warehouse. Visit dataengineeringpodcast.com/firebolt to get started.

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Data Engineering Podcast

NOVEMBER 20, 2021

Summary One of the perennial challenges posed by data lakes is how to keep them up to date as new data is collected. In this episode Ori Rafael shares his experiences from Upsolver and building scalable stream processing for integrating and analyzing data, and what the tradeoffs are when coming from a batch oriented mindset.

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Data Engineering Podcast

MAY 15, 2022

Summary Designing a data platform is a complex and iterative undertaking which requires accounting for many conflicting needs. Designing a platform that relies on a data lake as its central architectural tenet adds additional layers of difficulty. Missing data? Struggling with broken pipelines? Stale dashboards?

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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).

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Data Engineering Podcast

AUGUST 31, 2020

Summary Data warehouse technology has been around for decades and has gone through several generational shifts in that time. The current trends in data warehousing are oriented around cloud native architectures that take advantage of dynamic scaling and the separation of compute and storage.

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Data Engineering Podcast

JUNE 16, 2019

Summary Building and maintaining a data lake is a choose your own adventure of tools, services, and evolving best practices. The flexibility and freedom that data lakes provide allows for generating significant value, but it can also lead to anti-patterns and inconsistent quality in your analytics.

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Data Engineering Podcast

JUNE 1, 2020

Summary Data lakes offer a great deal of flexibility and the potential for reduced cost for your analytics, but they also introduce a great deal of complexity. What used to be entirely managed by the database engine is now a composition of multiple systems that need to be properly configured to work in concert.

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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.

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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.

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Data Engineering Podcast

JUNE 9, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management This episode is supported by Code Comments, an original podcast from Red Hat. Data lakes are notoriously complex. Unfortunately, reasoning about stream processing engines is complex and lacks sufficient tooling.

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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.

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Data Engineering Podcast

JULY 22, 2019

Summary The current trend in data management is to centralize the responsibilities of storing and curating the organization’s information to a data engineering team. This organizational pattern is reinforced by the architectural pattern of data lakes as a solution for managing storage and access.

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Hepta Analytics

FEBRUARY 24, 2022

Examples of such systems are: ATM Shopping cart MoMo ticket systems OLAP on the other hand is used for data analysis. Data is aggregated from multiple sources and used by the business team to make decisions. Data structure and schema is defined in advance. The main goal is to become the single source of truth in an organization.

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Knowledge Hut

JULY 5, 2024

Large enterprises heavily rely on data for informed decision-making, and this reliance is where data engineers step in. Data engineers like myself play a pivotal role in assessing infrastructure and taking relevant actions. Looking ahead, the future of data engineering appears promising.

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Data Engineering Podcast

MAY 1, 2022

He describes how the platform is architected, the challenges related to selling cloud technologies into enterprise organizations, and how you can adopt Matillion for your own workflows to reduce the maintenance burden of data integration workflows. Missing data? Go to dataengineeringpodcast.com/atlan today and sign up for a free trial.

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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?

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Data Lake Architecture IT Amazon Web Services 52

Monte Carlo

OCTOBER 31, 2024

One job that has become increasingly popular across enterprise data teams is the role of the AI data engineer. Demand for AI data engineers has grown rapidly in data-driven organizations. But what does an AI data engineer do? Table of Contents What Does an AI Data Engineer Do?

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U-Next

MARCH 1, 2023

Introduction Data Engineer is responsible for managing the flow of data to be used to make better business decisions. A solid understanding of relational databases and SQL language is a must-have skill, as an ability to manipulate large amounts of data effectively. In 2022, data engineering will hold a share of 29.8%

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Knowledge Hut

MARCH 28, 2024

Data engineering is one of them. According to AnalytixLabs , the data science market is expected to be worth USD 230.80 All these numbers point to one thing–increased job roles and careers, especially when we talk about data engineering jobs in Azure, which are on the rise every year. Let’s get started.

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Data Engineering Podcast

APRIL 9, 2023

Now that the data warehouse has taken center stage a new approach of composable customer data platforms is emerging. In this episode Darren Haken is joined by Tejas Manohar to discuss how Autotrader UK is addressing their customer data needs by building on top of their existing data stack.

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Seattle Data Guy

FEBRUARY 10, 2024

Photo by Tiger Lily Data warehouses and data lakes play a crucial role for many businesses. It gives businesses access to the data from all of their various systems. As well as often integrating data so that end-users can answer business critical questions.

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