Data Pipelines Pocket Reference: Moving and Processing Data for Analytics
Download three chapters for free, complements of mParticle. Learn more about modern data infrastructure, how to implement data ingestion, and how to build data validation into your pipelines.
As more stakeholders across the business begin to leverage data to make decisions, the way in which data consumers receive the data they need is becoming increasingly important.
O’Reilly’s Data Pipelines Pocket Reference, written by James Densmore, provides detailed information to help data engineers implement scalable data pipelines, as well as insights related to common considerations such as batch versus streaming data ingestion and build versus buy.
mParticle is excited to offer this three-chapter exert, including:
- Chapter 2: A Modern Data Infrastructure
Understand what makes up the modern data stack so that you can build data pipelines that meet your internal stakeholders needs.
- Chapter 5: Data Ingestion: Loading Data
Get clarity on the different means of loading data into a data warehouse, as well as when it makes sense to build versus buy.
- Chapter 8: Data Validation in Pipelines
Learn how to build validation into your data pipelines and improve data quality across the business.