Data Pipelines Pocket Reference
Download Data Pipelines Pocket Reference PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Data Pipelines Pocket Reference book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Data Pipelines Pocket Reference
Author: James Densmore
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2021-02-10
Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse sources and transforming it to provide context is the difference between having data and actually gaining value from it. This pocket reference defines data pipelines and explains how they work in today's modern data stack. You'll learn common considerations and key decision points when implementing pipelines, such as batch versus streaming data ingestion and build versus buy. This book addresses the most common decisions made by data professionals and discusses foundational concepts that apply to open source frameworks, commercial products, and homegrown solutions. You'll learn: What a data pipeline is and how it works How data is moved and processed on modern data infrastructure, including cloud platforms Common tools and products used by data engineers to build pipelines How pipelines support analytics and reporting needs Considerations for pipeline maintenance, testing, and alerting
Data Pipelines Pocket Reference
Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse sources and transforming it to provide context is the difference between having data and actually gaining value from it. This pocket reference defines data pipelines and explains how they work in today's modern data stack. You'll learn common considerations and key decision points when implementing pipelines, such as batch versus streaming data ingestion and build versus buy. This book addresses the most common decisions made by data professionals and discusses foundational concepts that apply to open source frameworks, commercial products, and homegrown solutions. You'll learn: What a data pipeline is and how it works How data is moved and processed on modern data infrastructure, including cloud platforms Common tools and products used by data engineers to build pipelines How pipelines support analytics and reporting needs Considerations for pipeline maintenance, testing, and alerting
Hands-On APIs for AI and Data Science
To succeed in AI and data science, you must first master APIs. API skills are essential for AI and data science success. With this practical book, data scientists and software developers will gain hands-on experience developing and using APIs with the Python programming language and popular frameworks like FastAPI and StreamLit. Part 1 takes you step-by-step through coding projects to build APIs using Python and FastAPI and deploy them in the cloud. Part 2 teaches you to consume APIs in a data science project using industry-standard tools. And in Part 3, you'll use ChatGPT, the LangChain framework, and other tools to access your APIs with generative AI and large language models (LLMs). As you complete the chapters in the book, you'll be creating a professional online portfolio demonstrating your new skill with APIs, AI, and data science. You'll learn how to: Design APIs that data scientists and AIs love Develop APIs using Python and FastAPI Deploy APIs using multiple cloud providers Create data science projects such as visualizations and models using APIs as a data source Access APIs using generative AI and LLMs Author Ryan Day is a data scientist in the financial services industry and an open source developer.