Books like Data Engineering by Brian Shive


First publish date: 2013
Authors: Brian Shive
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Data Engineering by Brian Shive

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Books similar to Data Engineering (5 similar books)

Designing Data-Intensive Applications by 11833484|Martin Kleppmann book cover

πŸ“˜ Designing Data-Intensive Applications

An authoritative guide that explains how to build reliable, scalable, and maintainable data‑intensive systems, covering data models, storage engines, distributed systems, and batch and stream processing.

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Fundamentals of Data Engineering by 428086|Joe Reis book cover

πŸ“˜ Fundamentals of Data Engineering
 by Joe Reis


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The data warehouse ETL toolkit by 7142481|Ralph  Kimball book cover

πŸ“˜ The data warehouse ETL toolkit

Cowritten by Ralph Kimball, the world's leading data warehousing authority, whose previous books have sold more than 150,000 copies Delivers real-world solutions for the most time- and labor-intensive portion of data warehousing-data staging, or the extract, transform, load (ETL) process Delineates best practices for extracting data from scattered sources, removing redundant and inaccurate data, transforming the remaining data into correctly formatted data structures, and then loading the end product into the data warehouse Offers proven time-saving ETL techniques, comprehensive guidance on building dimensional structures, and crucial advice on ensuring data quality

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Data Pipelines with Apache Airflow by 12723547|Bas P. Harenslak book cover

πŸ“˜ Data Pipelines with Apache Airflow


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Data Analytics and Decision Making by 399199|Ali AbdulHussein book cover

πŸ“˜ Data Analytics and Decision Making

Data analytics is a rapidly evolving field. In today’s labour market, knowing how to acquire, process, and interpret large amounts of data to make optimal decisions is crucial for many professionals, especially those in business and engineering. This open textbook, β€œa new online course” if you will, focuses on three key concept areas: data acquisition, data processing, and decision-making models. In this course, students will be able to develop advanced knowledge and skills to acquire related data for operations of business or projects; apply quantitative literacy skills such as statistics and machine learning; and use predictive or prescriptive modeling to make timely, actionable, and meaningful decisions.

Data analytics is a rapidly evolving field. In today's labour market, knowing how to acquire, process, and interpret large amounts of data to make optimal decisions is crucial for many professionals, especially those in business and engineering. This open textbook, "a new online course" if you will, focuses on three key concept areas: data acquisition, data processing, and decision-making models. In this course, students will be able to develop advanced knowledge and skills to acquire related data for operations of business or projects; apply quantitative literacy skills such as statistics and machine learning; and use predictive or prescriptive modeling to make timely, actionable, and meaningful decisions.

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Some Other Similar Books

Streaming Systems: The What, Where, When, and How of Large-Scale Data Processing by Mike L Compton, Stefan NT and others
Data Engineering with Python by Paul T. D. Lo
Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling by Ralph Kimball, Margy Ross
Fundamentals of Data Engineering by Anil Batra
Data Engineering Teams: Building the Modern Data Stack by Ravi Murthy
Big Data Processing with Apache Spark by M. Z. Ali, F. R. Seida

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