| Description |
xlvi, 391 pages : illustrations ; 26 cm |
| Note |
Includes index |
| Contents |
Part 1. Creating custom data visualizations using R. The grammar of graphics -- Creating R custom visuals in Power BI using ggplot2 -- Part 2. Ingesting data into the Power BI data model using R and Python. Reading CSV files -- Reading Excel files -- Reading SQL server data -- Reading data into the Power BI data model via an API -- Part 3. Transforming data using R and Python. Advanced string manipulation and pattern matching -- Calculated columns using R and Python -- Part 4. Machine learning and AI in Power BI using R and Python. Applying machine learning and AI to your Power BI data models -- Productionizing data science models and data wrangling scripts |
| Summary |
This easy-to-follow guide provides R and Python recipes to help you learn and apply the top languages in the field of data analytics to your work in Microsoft Power BI. Data analytics expert and author Ryan Wade shows you how to use R and Python to perform tasks that are extremely hard, if not impossible, to do using native Power BI tools. For example, you will learn to score Power BI data using custom data science models and powerful models from Microsoft Cognitive Services. The R and Python languages are powerful complements to Power BI. They enable advanced data transformation techniques that are difficult to perform in Power BI in its default configuration but become easier by leveraging the capabilities of R and Python. If you are a business analyst, data analyst, or a data scientist who wants to push Power BI and transform it from being just a business intelligence tool into an advanced data analytics tool, then this is the book to help you do that |
| Subject |
Microsoft Power BI (Computer file)
|
|
Big data.
|
|
Artificial intelligence.
|
|
R (Computer program language)
|
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Python (Computer program language)
|
| ISBN |
9781484258286 |
|
1484258282 |
|
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