

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.
Meer over Gil RavivCollect, Combine, and Transform Data Using Power Query in Excel and Power BI
Paperback Engels 2018 1e druk 9781509307951Samenvatting
Using Power Query, you can import, reshape, and cleanse any data from a simple interface, so you can mine that data for all of its hidden insights. Power Query is embedded in Excel, Power BI, and other Microsoft products, and leading Power Query expert Gil Raviv will help you make the most of it. Discover how to eliminate time-consuming manual data preparation, solve common problems, avoid pitfalls, and more.
Then, walk through several complete analytics challenges, and integrate all your skills in a realistic chapter-length final project. By the time you're finished, you'll be ready to wrangle any data-and transform it into actionable knowledge.
- Prepare and analyze your data the easy way, with Power Query
- Quickly prepare data for analysis with Power Query in Excel (also known as Get & Transform) and in Power BI
- Solve common data preparation problems with a few mouse clicks and simple formula edits
- Combine data from multiple sources, multiple queries, and mismatched tables
- Master basic and advanced techniques for unpivoting tables
- Customize transformations and build flexible data mashups with the M formula language
- Address collaboration challenges with Power Query
- Gain crucial insights into text feeds
- Streamline complex social network analytics so you can do it yourself
For all information workers, analysts, and any Excel user who wants to solve their own business intelligence problems.
Specificaties
Lezersrecensies
Inhoudsopgave
1: Introduction to Power Query
2: Basic Data Challenges
3: Combining Data from Multiple Sources
4: Unpivoting and Transforming Data
5: Pivoting & Handling Multiline Records
Section 2: Exploring Data
6: Ad-Hoc Analysis
7: Using Query Editor to Further Explore Data
Section 3: Scaling Up Queries for Production or Larger Data Sets
8: Introduction to the M Query Language
9: Lightweight modification of M formulas to improve query robustness
Section 4: Real Life Challenges
10: Solving Real-Life Data Challenges
11: Social Listening
12: Text Analytics
13: Concluding Exercise - Hawaii Tourism Data
Rubrieken
- advisering
- algemeen management
- coaching en trainen
- communicatie en media
- economie
- financieel management
- inkoop en logistiek
- internet en social media
- it-management / ict
- juridisch
- leiderschap
- marketing
- mens en maatschappij
- non-profit
- ondernemen
- organisatiekunde
- personal finance
- personeelsmanagement
- persoonlijke effectiviteit
- projectmanagement
- psychologie
- reclame en verkoop
- strategisch management
- verandermanagement
- werk en loopbaan