图书简介
This book provides all you need to find data from external sources and load and transform that data into Power BI where you can mine it for business insights and a competitive edge. This ranges from connecting to corporate databases such as Azure SQL and SQL Server to file-based data sources, and cloud- and web-based data sources. The book also explains the use of Direct Query and Live Connect to establish instant connections to databases and data warehouses and avoid loading data. The book provides detailed guidance on techniques for transforming inbound data into normalized data sets that are easy to query and analyze. This covers data cleansing, data modification, and standardization as well as merging source data into robust data structures that can feed into your data model. You will learn how to pivot and transpose data and extrapolate missing values as well as harness external programs such as R and Python into a Power Query data flow. You also will see how to handle errors in source data and extend basic data ingestion to create robust and parameterized data load and transformation processes. Everything in this book is aimed at helping you deliver compelling and interactive insight with remarkable ease using Power BI’s built-in data load and transformation tools.What You Will LearnConnect Power BI to a range of external data sourcesPrepare data from external sources for easy analysis in Power BI Cleanse data from duplicates, outliers, and other bad valuesMake live connections from which to refresh data quickly and easilyApply advanced techniques to interpolate missing data
1. Discovering and Loading Data with Power BI Desktop.- 2. Discovering and Loading File-Based Data with Power BI Desktop.- 3. Loading Data From Databases and Data Warehouses.- 4. DirectQuery and Live Connect.- 5. Loading Data from the Web and Cloud.- 6. Loading Data from Other Data Sources.- 7. Power Query.- 8. Structuring Data.- 9. Shaping Data.- 10. Data Cleansing.- 11. Data Transformation.- 12. Complex Data Structures.- 13. Organizing, Managing, and Parameterizing Queries.- 14. The M Language.- 15. Appendix A: Sample Data.
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