Data Wrangling with SQL is a hands-on textbook designed to help students develop the practical skills needed to prepare real-world data for analysis. Because most data arrives incomplete, inconsistent, or poorly structured, data wrangling is often the most time-consuming and critical phase of the analytics process.
Using clear explanations, business-focused examples, and guided exercises, students learn how to assess data quality, clean messy datasets, handle missing values, remove duplicates, normalize formats, merge data from multiple sources, create calculated fields, and reshape data for reporting and analysis. The text introduces essential SQL concepts in the context of solving practical data preparation challenges rather than memorizing syntax.
The book also explores modern AI-assisted approaches to data cleaning, validation, and SQL query development, helping students understand how artificial intelligence can support data professionals while maintaining data quality and accuracy.
Features include:
- Seven chapters covering the complete data wrangling workflow
- Step-by-step demonstrations and guided labs
- Practice exercises and review questions
- Real-world business and analytics scenarios
- Coverage of joins, filtering, transformations, aggregation, and reshaping
- AI-assisted data preparation techniques
- Companion resources for students and instructors
Ideal for introductory data analytics, business analytics, database, data science, and information systems courses.
"Sinopsis" puede pertenecer a otra edición de este libro.
Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de America
Paperback or Softback. Condición: New. Data Wrangling with SQL. Book. Nº de ref. del artículo: BBS-9781969233425
Cantidad disponible: 5 disponibles
Librería: California Books, Miami, FL, Estados Unidos de America
Condición: New. Nº de ref. del artículo: I-9781969233425
Cantidad disponible: Más de 20 disponibles
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Paperback. Condición: new. Paperback. Data Wrangling with SQL is a hands-on textbook designed to help students develop the practical skills needed to prepare real-world data for analysis. Because most data arrives incomplete, inconsistent, or poorly structured, data wrangling is often the most time-consuming and critical phase of the analytics process.Using clear explanations, business-focused examples, and guided exercises, students learn how to assess data quality, clean messy datasets, handle missing values, remove duplicates, normalize formats, merge data from multiple sources, create calculated fields, and reshape data for reporting and analysis. The text introduces essential SQL concepts in the context of solving practical data preparation challenges rather than memorizing syntax.The book also explores modern AI-assisted approaches to data cleaning, validation, and SQL query development, helping students understand how artificial intelligence can support data professionals while maintaining data quality and accuracy.Features include: - Seven chapters covering the complete data wrangling workflow- Step-by-step demonstrations and guided labs- Practice exercises and review questions- Real-world business and analytics scenarios- Coverage of joins, filtering, transformations, aggregation, and reshaping- AI-assisted data preparation techniques- Companion resources for students and instructorsIdeal for introductory data analytics, business analytics, database, data science, and information systems courses. A practical introduction to data preparation and SQL for analytics. Students learn how to clean, transform, merge, validate, and summarize real-world data through hands-on labs, business-focused examples, and AI-assisted workflows. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9781969233425
Cantidad disponible: 1 disponibles
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Taschenbuch. Condición: Neu. Neuware - Data Wrangling with SQL is a hands-on textbook designed to help students develop the practical skills needed to prepare real-world data for analysis. Because most data arrives incomplete, inconsistent, or poorly structured, data wrangling is often the most time-consuming and critical phase of the analytics process.Using clear explanations, business-focused examples, and guided exercises, students learn how to assess data quality, clean messy datasets, handle missing values, remove duplicates, normalize formats, merge data from multiple sources, create calculated fields, and reshape data for reporting and analysis. The text introduces essential SQL concepts in the context of solving practical data preparation challenges rather than memorizing syntax.The book also explores modern AI-assisted approaches to data cleaning, validation, and SQL query development, helping students understand how artificial intelligence can support data professionals while maintaining data quality and accuracy.Features include: - Seven chapters covering the complete data wrangling workflow- Step-by-step demonstrations and guided labs- Practice exercises and review questions- Real-world business and analytics scenarios- Coverage of joins, filtering, transformations, aggregation, and reshaping- AI-assisted data preparation techniques- Companion resources for students and instructorsIdeal for introductory data analytics, business analytics, database, data science, and information systems courses. Nº de ref. del artículo: 9781969233425
Cantidad disponible: 2 disponibles
Librería: CitiRetail, Stevenage, Reino Unido
Paperback. Condición: new. Paperback. Data Wrangling with SQL is a hands-on textbook designed to help students develop the practical skills needed to prepare real-world data for analysis. Because most data arrives incomplete, inconsistent, or poorly structured, data wrangling is often the most time-consuming and critical phase of the analytics process.Using clear explanations, business-focused examples, and guided exercises, students learn how to assess data quality, clean messy datasets, handle missing values, remove duplicates, normalize formats, merge data from multiple sources, create calculated fields, and reshape data for reporting and analysis. The text introduces essential SQL concepts in the context of solving practical data preparation challenges rather than memorizing syntax.The book also explores modern AI-assisted approaches to data cleaning, validation, and SQL query development, helping students understand how artificial intelligence can support data professionals while maintaining data quality and accuracy.Features include: - Seven chapters covering the complete data wrangling workflow- Step-by-step demonstrations and guided labs- Practice exercises and review questions- Real-world business and analytics scenarios- Coverage of joins, filtering, transformations, aggregation, and reshaping- AI-assisted data preparation techniques- Companion resources for students and instructorsIdeal for introductory data analytics, business analytics, database, data science, and information systems courses. A practical introduction to data preparation and SQL for analytics. Students learn how to clean, transform, merge, validate, and summarize real-world data through hands-on labs, business-focused examples, and AI-assisted workflows. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9781969233425
Cantidad disponible: 1 disponibles