Data Engineering Podcast

DECEMBER 3, 2023

Summary The first step of data pipelines is to move the data to a place where you can process and prepare it for its eventual purpose. Data transfer systems are a critical component of data enablement, and building them to support large volumes of information is a complex endeavor.

Systems 130

Systems Designing Data Lake SQL 130

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]([link] and use code *depod20* to register today!

Data Lake 262

Data Lake High Quality Data Data Warehouse Google Cloud 262

Snowflake

NOVEMBER 2, 2023

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. These patterns include both centralized storage patterns like data warehouse , data lake and data lakehouse , and distributed patterns such as data mesh.

Data Lake 115

Data Lake Data Warehouse Cloud Unstructured Data 115

Data Engineering Podcast

DECEMBER 24, 2023

Summary Kafka has become a ubiquitous technology, offering a simple method for coordinating events and data across different systems. Data lakes are notoriously complex. Operating it at scale, however, is notoriously challenging. Go to dataengineeringpodcast.com/materialize today to get 2 weeks free!

Kafka 245

Kafka Data Lake High Quality Data SQL 245

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.

Data Lake 100

Data Lake Data Integration Lambda Architecture Process 100

Data Engineering Podcast

DECEMBER 25, 2022

Recognizing this shortcoming and the capabilities that could be unlocked by a robust solution Rishabh Poddar helped to create Opaque Systems as an outgrowth of his PhD studies. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows.

Machine Learning 130

Machine Learning Systems Data Lake Data Warehouse 130

Snowflake

NOVEMBER 26, 2024

Today we’re focusing on customers who migrated from a cloud data warehouse to Snowflake and some of the benefits they saw. A consolidated data system to accommodate a big(ger) WHOOP When a company experiences exponential growth over a short period, it’s easy for its data foundation to feel a bit like it was built on the fly.

Data Warehouse 105

Data Warehouse Cloud PostgreSQL Hadoop 105

Cloudera

JUNE 2, 2022

In a recent customer workshop with a large retail data science media company, one of the attendees, an engineering leader, made the following observation: “Everytime I go to your competitor website, they only care about their system. How to onboard data into their system? I don’t care about their system.

Systems 104

Systems Data Lake Google Cloud Data Collection 104

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. Another area that has been seeing a lot of activity is data lakes and projects to make them more manageable and feature complete (e.g. Hudi, Delta Lake, Iceberg, Nessie, LakeFS, etc.).

Data Lake 100

Data Lake Cloud AWS SQL 100

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. When is a data lake architecture the wrong choice?

Data Lake 100

Data Lake Building Architecture BI 100

Data Engineering Podcast

APRIL 21, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Data Lake 182

Data Lake High Quality Data Machine Learning Data Pipeline 182

Data Engineering Podcast

FEBRUARY 4, 2024

Summary Stream processing systems have long been built with a code-first design, adding SQL as a layer on top of the existing framework. 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.

SQL 173

SQL Data Lake High Quality Data Machine Learning 173

Snowflake

DECEMBER 4, 2024

Beyond working with well-structured data in a data warehouse, modern AI systems can use deep learning and natural language processing to work effectively with unstructured and semi-structured data in data lakes and lakehouses.

Unstructured Data 97

Unstructured Data Data Lake Deep Learning Structured Data 97

Data Engineering Podcast

MAY 5, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Building 147

Building Data Lake High Quality Data Machine Learning 147

Snowflake

NOVEMBER 11, 2024

This reduces the overall complexity of getting streaming data ready to use: Simply create external access integration with your existing Kafka solution. SnowConvert is an easy-to-use code conversion tool that accelerates legacy relational database management system (RDBMS) migrations to Snowflake.

Data Architecture 105

Data Architecture Architecture Data Lake Kafka 105

Data Engineering Podcast

APRIL 7, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Data Lake 162

Data Lake High Quality Data BI Data Workflow 162

Data Engineering Podcast

JUNE 30, 2024

Petr shares his journey from being an engineer to founding Synq, emphasizing the importance of treating data systems with the same rigor as engineering systems. He discusses the challenges and solutions in data reliability, including the need for transparency and ownership in data systems.

Pipeline-centric 147

Pipeline-centric Engineering Data Lake High Quality Data 147

Data Engineering Podcast

MARCH 3, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Programming 162

Programming Data Lake High Quality Data Machine Learning 162

Data Engineering Podcast

JANUARY 7, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data.

Data Process 147

Data Process Process Data Lake High Quality Data 147

Data Engineering Podcast

JUNE 9, 2024

To address this shortcoming Datorios created an observability platform for Flink that brings visibility to the internals of this popular stream processing system. 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.

Process 147

Process Data Lake High Quality Data Machine Learning 147

Snowflake

JUNE 21, 2024

Snowflake is now making it even easier for customers to bring the platform’s usability, performance, governance and many workloads to more data with Iceberg tables (now generally available), unlocking full storage interoperability. Iceberg tables provide compute engine interoperability over a single copy of data.

Data Lake 124

Data Lake BI Business Intelligence Metadata 124

Data Engineering Podcast

JUNE 16, 2024

In this episode Kevin Liu shares some of the interesting features that they have built by combining those technologies, as well as the challenges that they face in supporting the myriad workloads that are thrown at this layer of their data platform. What are the other systems that feed into and rely on the Trino/Iceberg service?

Data Lake 147

Data Lake High Quality Data Metadata Machine Learning 147

Data Engineering Podcast

MARCH 24, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Data Lake 162

Data Lake High Quality Data Hadoop Machine Learning 162

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.

Data Lake 162

Data Lake Data Warehouse Data Accessibility 162

Confessions of a Data Guy

JANUARY 12, 2023

Anyone who’s been roaming around the forest of Data Engineering has probably run into many of the newish tools that have been growing rapidly around the concepts of Data Warehouses, Data Lakes, and Lake Houses … the merging of the old relational database functionality with TB and PB level cloud-based file storage systems.

Data Lake 162

Data Lake Relational Database Data Warehouse Data Engineering 162

Data Engineering Podcast

FEBRUARY 25, 2024

Over the decades of research and development into building these software systems there are a number of common components that are shared across implementations. Data lakes are notoriously complex. Summary Building a database engine requires a substantial amount of engineering effort and time investment.

Database 162

Database Technology Data Lake High Quality Data 162

Data Engineering Podcast

JUNE 2, 2024

Summary Modern businesses aspire to be data driven, and technologists enjoy working through the challenge of building data systems to support that goal. Data governance is the binding force between these two parts of the organization. What are some of the misconceptions that you encounter about data governance?

Data Governance 147

Data Governance Government Data Lake High Quality Data 147

Data Engineering Podcast

FEBRUARY 11, 2024

In this episode Andrew Jefferson explains the complexities of building a robust system for data sharing, the techno-social considerations, and how the Bobsled platform that he is building aims to simplify the process.

Data Lake 147

Data Lake High Quality Data Government Machine Learning 147

Data Engineering Podcast

JANUARY 21, 2024

A substantial amount of the data that is being managed in these systems is related to customers and their interactions with an organization. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex.

Data Lake 147

Data Lake High Quality Data NoSQL Data Warehouse 147

Data Engineering Podcast

DECEMBER 19, 2021

In the same way that application performance monitoring ensures reliable software and keeps application downtime at bay, Monte Carlo solves the costly problem of broken data pipelines. Start trusting your data with Monte Carlo today! Supercharge your business teams with customer data using Hightouch for Reverse ETL today.

Systems 100

Systems Building Metadata Data Warehouse 100

Data Engineering Podcast

APRIL 24, 2022

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. Acryl Data provides DataHub as an easy to consume SaaS product which has been adopted by several companies.

Machine Learning 100

Machine Learning Systems Data Lake Java 100

Netflix Tech

MARCH 7, 2024

The Machine Learning Platform (MLP) team at Netflix provides an entire ecosystem of tools around Metaflow , an open source machine learning infrastructure framework we started, to empower data scientists and machine learning practitioners to build and manage a variety of ML systems. ETL workflows), as well as downstream (e.g.

Systems 94

Systems Media Machine Learning Data Warehouse 94

Data Engineering Podcast

MAY 12, 2024

Summary Building a data platform is a substrantial engineering endeavor. The services and systems need to be kept up to date, but so does the code that controls their behavior. Data lakes are notoriously complex. Support Data Engineering Podcast Summary Building a data platform is a substrantial engineering endeavor.

Management 147

Management Data Lake High Quality Data Machine Learning 147

DataKitchen

DECEMBER 9, 2024

They opted for Snowflake, a cloud-native data platform ideal for SQL-based analysis. The team landed the data in a Data Lake implemented with cloud storage buckets and then loaded into Snowflake, enabling fast access and smooth integrations with analytical tools. Here is another example.

Pharmaceutical 64

Pharmaceutical Data Lake Cloud Storage Project 64

Data Engineering Podcast

MARCH 10, 2024

Summary Data lakehouse architectures are gaining popularity due to the flexibility and cost effectiveness that they offer. The link that bridges the gap between data lake and warehouse capabilities is the catalog. Data lakes are notoriously complex. What is involved in integrating Nessie into a given data stack?

Data Lake 147

Data Lake High Quality Data Architecture Machine Learning 147

Sync Computing

NOVEMBER 7, 2024

While data warehouses are still in use, they are limited in use-cases as they only support structured data. Data lakes add support for semi-structured and unstructured data, and data lakehouses add further flexibility with better governance in a true hybrid solution built from the ground-up.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Unstructured Data 52

Towards Data Science

FEBRUARY 6, 2024

ERP and CRM systems are designed and built to fulfil a broad range of business processes and functions. This generalisation makes their data models complex and cryptic and require domain expertise. As you do not want to start your development with uncertainty, you decide to go for the operational raw data directly.

Systems 98

Systems Raw Data Metadata Data Cleanse 98