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Streaming data : concepts that drive innovative analytics / Andy Oram.
- Format:
- Book
- Author/Creator:
- Oram, Andrew, author.
- Language:
- English
- Subjects (All):
- Information technology--Management.
- Information technology.
- Decision making--Data processing.
- Decision making.
- Service-oriented architecture (Computer science).
- Data mining.
- Big data.
- Physical Description:
- 1 online resource (1 volume)
- Edition:
- First edition.
- Place of Publication:
- Sebastopol, CA : O'Reilly Media, 2019.
- System Details:
- text file
- Summary:
- Managers and staff responsible for planning, hiring, and allocating resources need to understand how streaming data can fundamentally change their organizations. Companies everywhere are disrupting business, government, and society by using data and analytics to shape their business. Even if you don’t have deep knowledge of programming or digital technology, this high-level introduction brings data streaming into focus. You won’t find math or programming details here, or recommendations for particular tools in this rapidly evolving space. But you will explore the decision-making technologies and practices that organizations need to process streaming data and respond to fast-changing events. By describing the principles and activities behind this new phenomenon, author Andy Oram shows you how streaming data provides hidden gems of information that can transform the way your business works. Learn where streaming data comes from and how companies put it to work Follow a simple data processing project from ingesting and analyzing data to presenting results Explore how (and why) big data processing tools have evolved from MapReduce to Kubernetes Understand why streaming data is particularly useful for machine learning projects Learn how containers, microservices, and cloud computing led to continuous integration and DevOps
- Notes:
- Description based on online resource; title from title page (Safari, viewed August 14, 2019).
- ISBN:
- 9781492038085
- 1492038083
- 9781492038092
- 1492038091
- OCLC:
- 1112253844
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