O'Reilly

Data pipelines are the foundation for success in data analytics, so understanding how they work is of the utmost importance. Join us for four hours of expert-led sessions that will give you insight into how data is moved, processed, and transformed to support analytics and reporting needs. You’ll also learn how to address common challenges like monitoring and managing broken pipelines, explore considerations for choosing and connecting open source frameworks, commercial products, and homegrown solutions, and more. ...

The data pipeline has become a fundamental component of the data science, data analyst, and data engineering workflow. Pipelines serve as the glue that links together various components of the data cleansing, data validation, and data transformation process. However, despite its importance to the data ecosystem, constructing the optimal data pipeline is generally an afterthought - if it’s considered at all. This makes any changes to the central pipeline highly error-prone and cumbersome. With the ever-growing demand for new kinds of data, especially from external vendors, constructing pipelines that are scalable and that allow for monitoring is pivotal for the safe and continued use of data. ...

O’Reilly Radar: Data & AI will showcase what’s new, what’s important, and what’s coming in the field. It includes two keynotes and two concurrent three-hour tracks—designed to lay out for tech leaders the issues, tools, and best practices that are critical to an organization at any step of their data and AI journey. You’ll explore everything from prototyping and pipelines to deployment and DevOps to responsible and ethical AI. Link https://www.oreilly.com/videos/oreilly-radar-data/0636920654667/ https://www.businesswire.com/news/home/20210909005792/en/O%E2%80%99Reilly-Announces-O%E2%80%99Reilly-Radar-Data-AI-to-Help-Tech-Leaders-Drive-Innovation-and-Successful-Implementation

As the scale of data continues to grow (alongside an ever expanding ecosystem of tools to work with it), developing successful applications is an increasingly challenging proposition—and a necessity. At each stage of the process, from architecting to processing and storing data to deployment, there are a range of aspects to consider. Things like scalability, consistency, reliability, efficiency, and maintainability. It can be hard to figure out the right way forward. ...