Summary Kafka has become a ubiquitous technology, offering a simple method for coordinating events and data across different systems. Operating it at scale, however, is notoriously challenging. Elad Eldor has experienced these challenges first-hand, leading to his work writing the book "Kafka: : Troubleshooting in Production". In this episode he highlights the sources of complexity that contribute to Kafka's operational difficulties, and some of the main ways to identify and mitiga...
Dec 24, 2023•1 hr 15 min•Ep. 406
Summary The "modern data stack" promised a scalable, composable data platform that gave everyone the flexibility to use the best tools for every job. The reality was that it left data teams in the position of spending all of their engineering effort on integrating systems that weren't designed with compatible user experiences. The team at 5X understand the pain involved and the barriers to productivity and set out to solve it by pre-integrating the best tools from each layer of the...
Dec 18, 2023•56 min•Ep. 405
Summary If your business metrics looked weird tomorrow, would you know about it first? Anomaly detection is focused on identifying those outliers for you, so that you are the first to know when a business critical dashboard isn't right. Unfortunately, it can often be complex or expensive to incorporate anomaly detection into your data platform. Andrew Maguire got tired of solving that problem for each of the different roles he has ended up in, so he created the open source Anomstack project....
Dec 11, 2023•51 min•Ep. 404
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. Andrei Tserakhau has dedicated his careeer to this problem, and in this episode he shares the lessons that he has learned and the work he is doing on his most recent data transfer system at DoubleCloud. Announcements ...
Dec 04, 2023•1 hr 4 min•Ep. 403
Summary Building a data platform that is enjoyable and accessible for all of its end users is a substantial challenge. One of the core complexities that needs to be addressed is the fractal set of integrations that need to be managed across the individual components. In this episode Tobias Macey shares his thoughts on the challenges that he is facing as he prepares to build the next set of architectural layers for his data platform to enable a larger audience to start accessing the data being ma...
Nov 27, 2023•30 min•Ep. 402
Summary The dbt project has become overwhelmingly popular across analytics and data engineering teams. While it is easy to adopt, there are many potential pitfalls. Dustin Dorsey and Cameron Cyr co-authored a practical guide to building your dbt project. In this episode they share their hard-won wisdom about how to build and scale your dbt projects. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data projects are notoriously complex. With m...
Nov 20, 2023•1 hr 16 min•Ep. 401
Summary Software development involves an interesting balance of creativity and repetition of patterns. Generative AI has accelerated the ability of developer tools to provide useful suggestions that speed up the work of engineers. Tabnine is one of the main platforms offering an AI powered assistant for software engineers. In this episode Eran Yahav shares the journey that he has taken in building this product and the ways that it enhances the ability of humans to get their work done, and when t...
Nov 13, 2023•1 hr 8 min•Ep. 400
Summary Databases are the core of most applications, but they are often treated as inscrutable black boxes. When an application is slow, there is a good probability that the database needs some attention. In this episode Lukas Fittl shares some hard-won wisdom about the causes and solution of many performance bottlenecks and the work that he is doing to shine some light on PostgreSQL to make it easier to understand how to keep it running smoothly. Announcements Hello and welcome to the Data Engi...
Nov 06, 2023•55 min•Ep. 399
Summary Databases are the core of most applications, whether transactional or analytical. In recent years the selection of database products has exploded, making the critical decision of which engine(s) to use even more difficult. In this episode Tanya Bragin shares her experiences as a product manager for two major vendors and the lessons that she has learned about how teams should approach the process of tool selection. Announcements Hello and welcome to the Data Engineering Podcast, the show ...
Oct 30, 2023•47 min•Ep. 398
Summary The primary application of data has moved beyond analytics. With the broader audience comes the need to present data in a more approachable format. This has led to the broad adoption of data products being the delivery mechanism for information. In this episode Ranjith Raghunath shares his thoughts on how to build a strategy for the development, delivery, and evolution of data products. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management...
Oct 23, 2023•1 hr 4 min•Ep. 397
Summary Building streaming applications has gotten substantially easier over the past several years. Despite this, it is still operationally challenging to deploy and maintain your own stream processing infrastructure. Decodable was built with a mission of eliminating all of the painful aspects of developing and deploying stream processing systems for engineering teams. In this episode Eric Sammer discusses why more companies are including real-time capabilities in their products and the ways th...
Oct 15, 2023•1 hr 8 min•Ep. 396
Summary The insurance industry is notoriously opaque and hard to navigate. Max Cho found that fact frustrating enough that he decided to build a business of making policy selection more navigable. In this episode he shares his journey of data collection and analysis and the challenges of automating an intentionally manual industry. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles. RudderStack Profiles takes th...
Oct 09, 2023•52 min•Ep. 395
Summary Artificial intelligence applications require substantial high quality data, which is provided through ETL pipelines. Now that AI has reached the level of sophistication seen in the various generative models it is being used to build new ETL workflows. In this episode Jay Mishra shares his experiences and insights building ETL pipelines with the help of generative AI. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderS...
Oct 01, 2023•52 min•Ep. 394
Summary The rapid growth of machine learning, especially large language models, have led to a commensurate growth in the need to store and compare vectors. In this episode Louis Brandy discusses the applications for vector search capabilities both in and outside of AI, as well as the challenges of maintaining real-time indexes of vector data. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles. RudderStack Profil...
Sep 25, 2023•59 min•Ep. 393
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. In this episode Brian Platz explains how JSON-LD can be used as a shared representation of linked data for building semantic data products. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management This episode is brou...
Sep 17, 2023•1 hr 2 min•Ep. 392
Summary Data systems are inherently complex and often require integration of multiple technologies. Orchestrators are centralized utilities that control the execution and sequencing of interdependent operations. This offers a single location for managing visibility and error handling so that data platform engineers can manage complexity. In this episode Nick Schrock, creator of Dagster, shares his perspective on the state of data orchestration technology and its application to help inform its im...
Sep 10, 2023•1 hr 1 min•Ep. 391
Summary Cloud data warehouses and the introduction of the ELT paradigm has led to the creation of multiple options for flexible data integration, with a roughly equal distribution of commercial and open source options. The challenge is that most of those options are complex to operate and exist in their own silo. The dlt project was created to eliminate overhead and bring data integration into your full control as a library component of your overall data system. In this episode Adrian Brudaru ex...
Sep 04, 2023•42 min•Ep. 390
Summary Data persistence is one of the most challenging aspects of computer systems. In the era of the cloud most developers rely on hosted services to manage their databases, but what if you are a cloud service? In this episode Vignesh Ravichandran explains how his team at Cloudflare provides PostgreSQL as a service to their developers for low latency and high uptime services at global scale. This is an interesting and insightful look at pragmatic engineering for reliability and scale. Announce...
Aug 28, 2023•1 hr 1 min•Ep. 389
Summary Generative AI has unlocked a massive opportunity for content creation. There is also an unfulfilled need for experts to be able to share their knowledge and build communities. Illumidesk was built to take advantage of this intersection. In this episode Greg Werner explains how they are using generative AI as an assistive tool for creating educational material, as well as building a data driven experience for learners. Announcements Hello and welcome to the Data Engineering Podcast, the s...
Aug 20, 2023•55 min•Ep. 388
Summary Data pipelines are the core of every data product, ML model, and business intelligence dashboard. If you're not careful you will end up spending all of your time on maintenance and fire-fighting. The folks at Rivery distilled the seven principles of modern data pipelines that will help you stay out of trouble and be productive with your data. In this episode Ariel Pohoryles explains what they are and how they work together to increase your chances of success. Announcements Hello and ...
Aug 14, 2023•47 min•Ep. 387
Summary As businesses increasingly invest in technology and talent focused on data engineering and analytics, they want to know whether they are benefiting. So how do you calculate the return on investment for data? In this episode Barr Moses and Anna Filippova explore that question and provide useful exercises to start answering that in your company. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles. RudderSta...
Aug 06, 2023•1 hr 2 min•Ep. 386
Summary All software systems are in a constant state of evolution. This makes it impossible to select a truly future-proof technology stack for your data platform, making an eventual migration inevitable. In this episode Gleb Mezhanskiy and Rob Goretsky share their experiences leading various data platform migrations, and the hard-won lessons that they learned so that you don't have to. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Int...
Jul 31, 2023•1 hr 10 min•Ep. 385
Summary Real-time data processing has steadily been gaining adoption due to advances in the accessibility of the technologies involved. Despite that, it is still a complex set of capabilities. To bring streaming data in reach of application engineers Matteo Pelati helped to create Dozer. In this episode he explains how investing in high performance and operationally simplified streaming with a familiar API can yield significant benefits for software and data teams together. Announcements Hello a...
Jul 24, 2023•41 min•Ep. 384
Summary Data has been one of the most substantial drivers of business and economic value for the past few decades. Bob Muglia has had a front-row seat to many of the major shifts driven by technology over his career. In his recent book "Datapreneurs" he reflects on the people and businesses that he has known and worked with and how they relied on data to deliver valuable services and drive meaningful change. Announcements Hello and welcome to the Data Engineering Podcast, the show abou...
Jul 17, 2023•55 min•Ep. 383
Summary For business analytics the way that you model the data in your warehouse has a lasting impact on what types of questions can be answered quickly and easily. The major strategies in use today were created decades ago when the software and hardware for warehouse databases were far more constrained. In this episode Maxime Beauchemin of Airflow and Superset fame shares his vision for the entity-centric data model and how you can incorporate it into your own warehouse design. Announcements He...
Jul 09, 2023•1 hr 13 min•Ep. 382
Summary Feature engineering is a crucial aspect of the machine learning workflow. To make that possible, there are a number of technical and procedural capabilities that must be in place first. In this episode Razi Raziuddin shares how data engineering teams can support the machine learning workflow through the development and support of systems that empower data scientists and ML engineers to build and maintain their own features. Announcements Hello and welcome to the Data Engineering Podcast,...
Jul 03, 2023•1 hr 4 min•Ep. 381
Summary Data transformation is a key activity for all of the organizational roles that interact with data. Because of its importance and outsized impact on what is possible for downstream data consumers it is critical that everyone is able to collaborate seamlessly. SQLMesh was designed as a unifying tool that is simple to work with but powerful enough for large-scale transformations and complex projects. In this episode Toby Mao explains how it works, the importance of automatic column-level li...
Jun 25, 2023•50 min•Ep. 380
Summary Architectural decisions are all based on certain constraints and a desire to optimize for different outcomes. 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. In this episode Satish Jayanthi explores the benefits of incorporating column-aware tooling in ...
Jun 18, 2023•46 min•Ep. 379
Summary Data engineering is all about building workflows, pipelines, systems, and interfaces to provide stable and reliable data. Your data can be stable and wrong, but then it isn't reliable. Confidence in your data is achieved through constant validation and testing. Datafold has invested a lot of time into integrating with the workflow of dbt projects to add early verification that the changes you are making are correct. In this episode Gleb Mezhanskiy shares some valuable advice and insi...
Jun 11, 2023•48 min•Ep. 378
Summary A significant portion of the time spent by data engineering teams is on managing the workflows and operations of their pipelines. DataOps has arisen as a parallel set of practices to that of DevOps teams as a means of reducing wasted effort. 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. In this episode Tevje Olin explains how the platform is impl...
Jun 04, 2023•54 min•Ep. 377
