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Data Engineering Podcast

Tobias Macey

Data Engineering Podcast

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A weekly Business Intelligence and Technology podcast featuring Tobias Macey
 1 person rated this podcast
Data Engineering Podcast

Tobias Macey

Data Engineering Podcast

Claimed
Episodes
Data Engineering Podcast

Tobias Macey

Data Engineering Podcast

Claimed
A weekly Business Intelligence and Technology podcast featuring Tobias Macey
 1 person rated this podcast
Rate Podcast

Episodes of Data Engineering Podcast

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SummaryDatabases come in a variety of formats for different use cases. The default association with the term "database" is relational engines, but non-relational engines are also used quite widely. In this episode Oren Eini, CEO and creator of
SummaryMaintaining a single source of truth for your data is the biggest challenge in data engineering. Different roles and tasks in the business need their own ways to access and analyze the data in the organization. In order to enable this u
SummaryWorking with data is a complicated process, with numerous chances for something to go wrong. Identifying and accounting for those errors is a critical piece of building trust in the organization that your data is accurate and up to date
SummaryA core differentiator of Dagster in the ecosystem of data orchestration is their focus on software defined assets as a means of building declarative workflows. With their launch of Dagster+ as the redesigned commercial companion to the
SummaryA significant portion of data workflows involve storing and processing information in database engines. Validating that the information is stored and processed correctly can be complex and time-consuming, especially when the source and
SummaryData 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. The primary purpose of the cat
SummaryArtificial intelligence technologies promise to revolutionize business and produce new sources of value. In order to make those promises a reality there is a substantial amount of strategy and investment required. Colleen Tartow has wor
SummaryBuilding a database engine requires a substantial amount of engineering effort and time investment. Over the decades of research and development into building these software systems there are a number of common components that are share
SummaryA data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Multiple open source projects and vendors have been working together to
SummarySharing data is a simple concept, but complicated to implement well. There are numerous business rules and regulatory concerns that need to be applied. There are also numerous technical considerations to be made, particularly if the pro
SummaryStream processing systems have long been built with a code-first design, adding SQL as a layer on top of the existing framework. RisingWave is a database engine that was created specifically for stream processing, with S3 as the storage
SummaryMonitoring and auditing IT systems for security events requires the ability to quickly analyze massive volumes of unstructured log data. The majority of products that are available either require too much effort to structure the logs, o
SummaryDatabases and analytics architectures have gone through several generational shifts. A substantial amount of the data that is being managed in these systems is related to customers and their interactions with an organization. In this ep
SummaryData processing technologies have dramatically improved in their sophistication and raw throughput. Unfortunately, the volumes of data that are being generated continue to double, requiring further advancements in the platform capabilit
SummaryWorking with financial data requires a high degree of rigor due to the numerous regulations and the risks involved in security breaches. In this episode Andrey Korchack, CTO of fintech startup Monite, discusses the complexities of desig
SummaryKafka 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-
SummaryThe "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 e
SummaryIf 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. Unfortu
SummaryThe 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
SummaryBuilding 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
SummaryThe 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 db
SummarySoftware 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 on
SummaryDatabases 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
SummaryDatabases 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 episo
SummaryThe 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 inf
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