December 2020
Beginner to intermediate
52 pages
1h 19m
English
Content preview from Managing Data Orchestration and Integration at Scale
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Chapter 1. Data Integration at Enterprise Scale
The world is shifting to an interconnected, circular economy that requires all industries to be networked across the end-to-end supply and value chain. Companies need to apply advanced technologies with best practices to create an agile, integrated business process that is more resilient, profitable, and sustainable. The push to drive cost-effective transformation and sustainable growth requires that insights from all available data are integrated and embedded across every business process as quickly and seamlessly as possible.
We are writing this report because today’s approaches to enterprise data integration are no longer sufficient to enable you to run at your best where you can operate profitably, adapt continuously, and make a difference in your industry. The requirements of data integration have stretched and moved beyond the traditional approaches that have worked so well in the past. These additional requirements are evolving traditional data integration to data orchestration.
Before we get started, let’s first define what we mean by data integration and data orchestration, as well as why we are discussing the role of open source in transforming data.
Data integration is the process of combining and transforming data from multiple different sources and data domains to impact a business outcome. Common use cases for data integration include data warehousing, receiving data from partners or suppliers, creating a single customer-view, ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.