Data Analysis Using SQL and Excel
暫譯: 使用 SQL 和 Excel 進行資料分析
Gordon S. Linoff
- 出版商: Wiley
- 出版日期: 2007-10-01
- 售價: $1,780
- 貴賓價: 9.5 折 $1,691
- 語言: 英文
- 頁數: 645
- 裝訂: Paperback
- ISBN: 0470099518
- ISBN-13: 9780470099513
-
相關分類:
Excel、SQL、Data Science
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商品描述
Description
* One of the leading experts on business data mining shows managers how to leverage SQL and Excel to perform sophisticated types of business analysis without the expense of data mining tools and consultants
* Explains how to use the relatively simple tools of SQL and Excel to extract useful business information from relational databases
* Each chapter discusses why and when to perform a particular type of business analysis to obtain a useful business result, how to design and perform the analysis using SQL and Excel, and what the results look like in SQL and Excel
* Presents hints, warnings, and technical asides about Excel, SQL, and data analysis/mining
Table of Contents
Introduction.1. A Data Miner Looks at SQL.
2. What's in a Table? Getting Started with Data Exploration.
3. How Different is Different?
4. Where is it all Happening? Location, Location, Location.
5. It is a Matter of Time.
6. How Long Will Customers Last? Survival Analysis to Understand Customers and Their Value.
7. Factors Affecting Survival: The What and Why of Customer Tenure.
8. Customer Purchases and Other Repeated Events.
9. What's in a Shopping Cart? Market Basket Analysis and Association Rules.
10. Data Mining Models in SQL.
11. The Best Fit Line: Linear Regression Models.
12. Building Customer Signatures for Further Analysis.
Appendix A. Equivalent Constructs Among Databases.
Index.
商品描述(中文翻譯)
**描述**
* 一位商業數據挖掘的領先專家向管理者展示如何利用 SQL 和 Excel 進行複雜的商業分析，而無需花費數據挖掘工具和顧問的費用。
* 解釋如何使用相對簡單的 SQL 和 Excel 工具從關聯數據庫中提取有用的商業信息。
* 每一章都討論為什麼以及何時執行特定類型的商業分析以獲得有用的商業結果，如何使用 SQL 和 Excel 設計和執行分析，以及結果在 SQL 和 Excel 中的呈現方式。
* 提供有關 Excel、SQL 和數據分析/挖掘的提示、警告和技術附註。
**目錄**
引言。
1. 數據挖掘者看 SQL。
2. 表格中包含什麼？開始數據探索。
3. 不同有多不同？
4. 一切發生在哪裡？位置、位置、位置。
5. 這是時間的問題。
6. 客戶會持續多久？生存分析以了解客戶及其價值。
7. 影響生存的因素：客戶任期的什麼和為什麼。
8. 客戶購買和其他重複事件。
9. 購物車中包含什麼？市場籃分析和關聯規則。
10. SQL 中的數據挖掘模型。
11. 最佳擬合線：線性回歸模型。
12. 建立客戶簽名以進行進一步分析。
附錄 A. 數據庫之間的等效結構。
索引。
