Collect, Transform and Combine Data using Power BI and Power Query in Excel
(Sprache: Englisch)
Did you know that there is a technology inside Excel, and Power BI, that allows you to create magic in your data, avoid repetitive manual work, and save you time and money?
Using Excel and Power BI, you can: ...
Using Excel and Power BI, you can: ...
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Klappentext zu „Collect, Transform and Combine Data using Power BI and Power Query in Excel “
Did you know that there is a technology inside Excel, and Power BI, that allows you to create magic in your data, avoid repetitive manual work, and save you time and money? Using Excel and Power BI, you can:
- Save time by eliminating the pain of copying and pasting data into workbooks and then manually cleaning that data.
- Gain productivity by properly preparing data yourself, rather than relying on others to do it.
- Gain effiiciency by reducing the time it takes to prepare data for analysis, and make informed decisions more quickly.
With the data connectivity and transformative technology found in Excel and Power BI, users with basic Excel skills import data and then easily reshape and cleanse that data, using simple intuitive user interfaces. Known as "Get & Transform" in Excel 2016, as the "Power Query" separate add-in in Excel 2013 and 2010, and included in Power BI, you'll use this technology to tackle common data challenges, resolving them with simple mouse clicks and lightweight formula editing. With your new data transformation skills acquired through this book, you will be able to create an automated transformation of virtually any type of data set to mine its hidden insights.
Inhaltsverzeichnis zu „Collect, Transform and Combine Data using Power BI and Power Query in Excel “
- Section 1: Transforming Data
- Chapter 1: Introduction to Power Query
- Chapter 2: Basic Data Challenges
- Chapter 3: Combining Data from Multiple Sources
- Chapter 4: Unpivoting and Transforming Data
- Chapter 5: Pivoting & Handling Multiline Records
- Section 2: Exploring Data
- Chapter 6: Ad-Hoc Analysis
- Chapter 7: Using Query Editor to Further Explore Data
- Section 3: Scaling Up Queries for Production or Larger Data Sets
- Chapter 8: Introduction to the M Query Language
- Chapter 9: Lightweight modification of M formulas to improve query robustness
- Section 4: Real Life Challenges
- Chapter 10: Solving Real-Life Data Challenges
- Chapter 11: Social Listening
- Chapter 12: Text Analytics
- Chapter 13: Concluding Exercise – Hawaii Tourism Data
Autoren-Porträt von Gil Raviv
Gil Raviv is a Microsoft MVP and a Power BI blogger at https://DataChant.com. As a Senior Program Manager on the Microsoft Excel Product team, Gil led the design and integration of Power Query as the next-generation Get Data and data-wrangling technology in Excel 2016, and he has been a devoted M practitioner ever since. With 20 years of software development experience, and four U.S. patents in the fi elds of social networks, cyber security, and analytics, Gil has held a variety of innovative roles in cyber security and data analytics, and he has delivered a wide range of software products, from advanced threat detection enterprise systems to protection of kids on Facebook.
In his blog, DataChant.com, Gil has been chanting about Power BI and Power Query since he moved to his new home in the Chicago area in early 2016. As a Group Manager in Avanade’s Analytics Practice, Gil is helping Fortune 500 clients create modern self-service analytics capability and solutions by leveraging Power BI and Azure.
You can contact Gil at gilra@datachant.com.
Bibliographische Angaben
- Autor: Gil Raviv
- 2018, XVII, 402 Seiten, Maße: 18,9 x 23 cm, Kartoniert (TB), Englisch
- Verlag: Pearson
- ISBN-10: 1509307958
- ISBN-13: 9781509307951
- Erscheinungsdatum: 25.10.2018
Sprache:
Englisch
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