SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis

Teate, Renee M.

SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis

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商品描述

Jump-start your career as a data scientist--learn to develop datasets for exploration, analysis, and machine learning

SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that's dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls.

You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data.

This guide for data scientists differs from other instructional guides on the subject. It doesn't cover SQL broadly. Instead, you'll learn the subset of SQL skills that data analysts and data scientists use frequently. You'll also gain practical advice and direction on "how to think about constructing your dataset."

  • Gain an understanding of relational database structure, query design, and SQL syntax
  • Develop queries to construct datasets for use in applications like interactive reports and machine learning algorithms
  • Review strategies and approaches so you can design analytical datasets
  • Practice your techniques with the provided database and SQL code

In this book, author Renee Teate shares knowledge gained during a 15-year career working with data, in roles ranging from database developer to data analyst to data scientist. She guides you through SQL code and dataset design concepts from an industry practitioner's perspective, moving your data scientist career forward

商品描述(中文翻譯)

「跳躍式開始你的資料科學家職業生涯 - 學習開發探索、分析和機器學習的資料集」

《資料科學家的 SQL：建立分析資料集的初學者指南》是一本專注於資料科學家最常使用的結構化查詢語言（SQL）和資料集設計技能的資源。有志成為資料科學家的人將學習如何建立用於探索、分析和機器學習的資料集。您還可以了解如何進行查詢設計，並開發 SQL 代碼以提取數據洞察，同時避免常見的陷阱。

您可能是許多從各種專業和教育背景（如商業分析、社會科學、物理學、經濟學和計算機科學）進入資料科學領域的人之一。像他們中的許多人一樣，您可能曾使用電子表格作為數據來源進行分析，但從關聯式數據庫中使用 SQL 檢索和設計資料集可能是您從未嘗試過的，SQL 是一種專為管理數據庫和提取數據而設計的編程語言。

這本針對資料科學家的指南與其他教學指南有所不同。它不廣泛涵蓋 SQL。相反，您將學習資料分析師和資料科學家經常使用的 SQL 技能子集。您還將獲得關於「如何思考構建資料集」的實用建議和指導。

本書的作者 Renee Teate 在從事數據相關工作的 15 年職業生涯中積累了豐富的知識，從數據庫開發人員到數據分析師再到資料科學家的不同角色。她以業界從業者的角度指導您進行 SQL 代碼和資料集設計概念，推動您的資料科學家職業生涯向前發展。

作者簡介

RENÉE M. P. TEATE is the Director of Data Science at HelioCampus, a higher ed tech startup based in the Washington, DC area. She prepares datasets with SQL, develops predictive models with Python, and designs interactive dashboards in Tableau for university decision-makers. She created the "Becoming a Data Scientist" podcast, helped build the data science learning community on Twitter, and is a sought-after speaker at industry conferences.

作者簡介(中文翻譯)

RENÉE M. P. TEATE是華盛頓特區的高等教育科技初創公司HelioCampus的數據科學總監。她使用SQL準備數據集，使用Python開發預測模型，並使用Tableau設計互動式儀表板，以供大學決策者使用。她創建了《成為數據科學家》播客，幫助建立了Twitter上的數據科學學習社區，並受邀在行業會議上演講。

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