Collect, Combine, and Transform Data Using Power Query in Power BI and Excel
Idioma: inglés
Editorial: Pearson Education, 2025
- Tapa blanda
- Nuevo
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N° de ref. del artículo PB-9780138115791
- Título
- Collect, Combine, and Transform Data Using Power Query in Power BI and Excel
- Autor
- Daniil Maslyuk
- Editorial
- Pearson Education
- Año de publicación
- 2025
- Estado
- New
- Encuadernación
- PAP
- Idioma
- inglés
- ISBN 10
- 0138115796
- ISBN 13
- 9780138115791
- Edición
- 2ª Edición
- Peso del artículo
- 885 gramos
Transform your data analysis experience with Power Query, the ultimate tool for importing, reshaping, and cleansing data through a user-friendly interface. Whether you're using Power BI, Excel, or other Microsoft products, Power Query's capabilities are at your fingertips. Renowned Power Query experts Daniil Maslyuk and Gil Raviv guide you through mastering this indispensable tool, helping you eliminate tedious manual data preparation, tackle common issues, and avoid potential pitfalls. In this updated edition, you'll delve into comprehensive analytics challenges, seamlessly integrating your skills into a realistic, final project. By the end, you'll possess the expertise to handle any data and convert it into actionable insights.
You will learn how to:
- Effortlessly prepare data by utilizing Power Query in Power BI and Excel to transform your data quickly and efficiently
- Overcome common data preparation problems with intuitive mouse clicks and straightforward formula edits
- Combine data from various sources, multiple queries, and mismatched tables with ease
- Reshape tables to suit your analysis needs
- Use the Power Query M formula language to create flexible data mashups and tailor transformations to your requirements
- Address and overcome collaboration challenges by using Power Query's powerful features
- Gain crucial insights from text feeds by enhancing your data analysis capabilities
- Profile data, diagnose queries, improve query performance, and more!
About This Book
- For everyone who wants to get more done with Power Query in less time
- For business and financial professionals, developers, entrepreneurs, students, and others who need to efficiently manage and analyze data
“Sinopsis” puede pertenecer a otra edición de este título.
Acerca del autor
Daniil Maslyuk is an independent business intelligence consultant, trainer, and speaker who specializes in Microsoft Power BI. Daniil is the author of all official Microsoft Power BI exam reference books. For his community contributions, Daniil has been recognized as a Microsoft MVP. Daniil blogs at xxlbi.com and posts on X as @DMaslyuk.
Gil Raviv is a seasoned Data & AI expert, founder of DataChant Consulting, and the creator of BI Pixie, an enterprise solution that measures the engagement, adoption, and user satisfaction of Microsoft Power BI audiences. Gil started his Power Query journey as a senior program manager on the Microsoft Excel Product team, where he led the design and integration of Power Query as the next-generation Get Data and data-wrangling technology in Excel 2016. Since then, Gil has been a devoted Power Query practitioner. With the knowledge of Power Query at his disposal, Gil moved to consulting, and over the course of seven years he reached global leadership roles at Avanade and Amazon Web Services (AWS), where he advised Fortune 1000 enterprises in their BI migrations and Analytics centers of excellence. With two decades of software development, product management, and consulting experience at Microsoft, AWS, and other companies, Gil has always found the time to share knowledge and has received recognitions for his contributions―including a five year Microsoft MVP award, two years as a Microsoft Fast Track Solution Architect, and four U.S. patents in the fields of computer networks, cybersecurity, and analytics.
“Acerca de” puede pertenecer a otra edición de este título.
PBShop.store US
Wood Dale, IL, Estados Unidos de America
Vendedor de AbeBooks desde 7 de abril de 2005
Tarifas de envío en Estados Unidos de America
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|---|---|---|
| Primer artículo | EUR 0,00 | EUR 0,00 |
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