AI

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. ...

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

Databricks Sr. Staff Developer Advocate, Denny Lee, Citadel Head of Business Engineering, Vinoo Ganesh, and Databand.ai Co-Founder & CEO, Josh Benamram, discuss the complexities and business necessity of setting clear data service-level agreements (SLAs). They share their experiences around the importance of contractual expectations and why data delivery success criteria are prone to disguise failures as success in spite of our best intentions. Denny, Vinoo, and Josh challenge businesses of all industries to see themselves as data companies by driving home a costly reality – what do businesses have to lose when their data is wrong? A lot more than they’d like to believe. ...