October 2015
Intermediate to advanced
50 pages
1h 2m
English
Content preview from Fast Data: Smart and at Scale
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Chapter 1. What Is Fast Data?
Into a world dominated by discussions of big data, fast data has been born with little fanfare. Yet fast data will be the agent of change in the information-management industry, as we will show in this report.
Fast data is data in motion, streaming into applications and computing environments from hundreds of thousands to millions of endpoints—mobile devices, sensor networks, financial transactions, stock tick feeds, logs, retail systems, telco call routing and authorization systems, and more. Real-time applications built on top of fast data are changing the game for businesses that are data dependent: telco, financial services, health/medical, energy, and others. It’s also changing the game for developers, who must build applications to handle increasing streams of data.1
We’re all familiar with big data. It’s data at rest: collections of structured and unstructured data, stored in Hadoop and other “data lakes,” awaiting historical analysis. Fast data, by contrast, is streaming data: data in motion. Fast data demands to be dealt with as it streams in to the enterprise in real time. Big data can be dealt with some other time—typically after it’s been stored in a Hadoop data warehouse—and analyzed via batch processing.
A stack is emerging across verticals and industries to help developers build applications to process fast streams of data. This fast data stack has a unique purpose: to process real-time data and output recommendations, analytics, and ...
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