
Practical Data Science
Description
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The data science technology stack demonstrated in Practical Data Science is built from components in general use in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable results. He shows you how to apply practical methods to extract actionable business knowledge from data lakes consisting of data from a polyglot of data types and dimensions.
What You'll Learn
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Become fluent in the essential concepts and terminology of data science and data engineering
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Build and use a technology stack that meets industry criteria
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Master the methods for retrieving actionable business knowledge
- Coordinate the handling ofpolyglot data types in a data lake for repeatable results
Data scientists and data engineers who are required to convert data from a data lake into actionable knowledge for their business, and students who aspire to be data scientists and data engineers
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Content
Chapter 1: Data Science Technology Stack.- Chapter 2: Vermeulen - Krennwallner - Hillman - Clark.- Chapter 3: Layered Framework.- Chapter 4: Business Layer.- Chapter 5: Utility Layer.- Chapter 6: Three Management Layers.- Chapter 7: Retrieve Super Step.- Chapter 8: Assess Super Step.- Chapter 9: Process Super Step.- Chapter 10: Transform Super Step.- Chapter 11: Organize and Report Super Step.-
System requirements
File format: PDF
Copy protection: Watermark-DRM (Digital Rights Management)
System requirements:
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