How To Learn Excel Power Query


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M Is for (Data) Monkey


M Is for (Data) Monkey

Author: Ken Puls

language: en

Publisher: Tickling Keys, Inc.

Release Date: 2015-06-01


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Power Query is one component of the Power BI (Business Intelligence) product from Microsoft, and "M" is the name of the programming language created by it. As more business intelligence pros begin using Power Pivot, they find that they do not have the Excel skills to clean the data in Excel; Power Query solves this problem. This book shows how to use the Power Query tool to get difficult data sets into both Excel and Power Pivot, and is solely devoted to Power Query dashboarding and reporting.

Collect, Combine, and Transform Data Using Power Query in Excel and Power BI


Collect, Combine, and Transform Data Using Power Query in Excel and Power BI

Author: Gil Raviv

language: en

Publisher: Microsoft Press

Release Date: 2018-10-08


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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.

Mastering Power Query in Power BI and Excel


Mastering Power Query in Power BI and Excel

Author: Reza Rad

language: en

Publisher: RADACAD Systems Limited

Release Date: 2021-08-27


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Any data analytics solution requires data population and preparation. With the rise of data analytics solutions these years, the need for this data preparation becomes even more essential. Power BI is a helpful data analytics tool that is used worldwide by many users. As a Power BI (or Microsoft BI) developer, it is essential to learn how to prepare the data in the right shape and format needed. You need to learn how to clean the data and build it in a structure that can be modeled easily and used high performant for visualization. Data preparation and transformation is the backend work. If you consider building a BI system as going to a restaurant and ordering food. The visualization is the food you see on the table nicely presented. The quality, the taste, and everything else come from the hard work in the kitchen. The part that you don’t see or the backend in the world of Power BI is Power Query. You may already be familiar with other data preparation and transformation technologies, such as T-SQL, SSIS, Azure Data Factory, Informatica, etc. Power Query is a data transformation engine capable of preparing the data in the format you need. The good news is that to learn Power Query; you don’t need to know programming. Power Query is for citizen data engineers. However, this doesn’t mean that Power Query is not capable of performing advanced transformation. Power Query exists in many Microsoft tools and services such as Power BI, Excel, Dataflows, Power Automate, Azure Data Factory, etc. Through the years, this engine became more powerful. These days, we can say this is essential learning for anyone who wants to do data analysis with Microsoft technology to learn Power Query and master it. We have been working with Power Query since the very early release of that in 2013, named Data Explorer, and wrote blog articles and published videos about it. The number of articles we published under this subject easily exceeds hundreds. Through those articles, some of the fundamentals and key learnings of Power Query are explained. We thought it is good to compile some of them in a book series. A good analytics solution combines a good data model, good data preparation, and good analytics and calculations. Reza has written another book about the Basics of modeling in Power BI and a book on Power BI DAX Simplified. This book is covering the data preparation and transformations aspects of it. This book series is for you if you are building a Power BI solution. Even if you are just visualizing the data, preparation and transformations are an essential part of analytics. You do need to have the cleaned and prepared data ready before visualizing it. This book is compiled into a series of two books, which will be followed by a third book later; Getting started with Power Query in Power BI and Excel (already available to be purchased separately) Mastering Power Query in Power BI and Excel (This book) Power Query dataflows (will be published later) This book deeps dive into real-world challenges of data transformation. It starts with combining data sources and continues with aggregations and fuzzy operations. The book covers advanced usage of Power Query in scenarios such as error handling and exception reports, custom functions and parameters, advanced analytics, and some helpful table and list functions. The book continues with some performance tuning tips and it also explains the Power Query formula language (M) and the structure of it and how to use it in practical solutions. Although this book is written for Power BI and all the examples are presented using the Power BI. However, the examples can be easily applied to Excel, Dataflows, and other tools and services using Power Query.