語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Advanced analytics in power BI with ...
~
Wade, Ryan.
FindBook
Google Book
Amazon
博客來
Advanced analytics in power BI with R and Python = ingesting, transforming, visualizing /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Advanced analytics in power BI with R and Python/ by Ryan Wade.
其他題名:
ingesting, transforming, visualizing /
作者:
Wade, Ryan.
出版者:
Berkeley, CA :Apress : : 2020.,
面頁冊數:
xlvi, 391 p. :ill., digital ;24 cm.
內容註:
Part I. Creating Custom Data Visualizations using R -- 1. The Grammar of Graphics -- 2. Creating R custom visuals in Power BI using ggplot2 -- Part II. Ingesting Data into the Power BI Data Model using R and Python -- 3. Reading CSV Files -- 4. Reading Excel Files -- 5. Reading SQL Server Data -- 6. Reading Data into the Power BI Data Model via an API -- Part III. Transforming Data using R and Python -- 7. Advanced String Manipulation and Pattern Matching -- 8. Calculated Columns using R and Python -- Part IV. Machine Learning & AI in Power BI using R and Python -- 9. Applying Machine Learning and AI to your Power BI Data Models -- 10. Productionizing Data Science Models and Data Wrangling Scripts.
Contained By:
Springer Nature eBook
標題:
Information visualization. -
電子資源:
https://doi.org/10.1007/978-1-4842-5829-3
ISBN:
9781484258293
Advanced analytics in power BI with R and Python = ingesting, transforming, visualizing /
Wade, Ryan.
Advanced analytics in power BI with R and Python
ingesting, transforming, visualizing /[electronic resource] :by Ryan Wade. - Berkeley, CA :Apress :2020. - xlvi, 391 p. :ill., digital ;24 cm.
Part I. Creating Custom Data Visualizations using R -- 1. The Grammar of Graphics -- 2. Creating R custom visuals in Power BI using ggplot2 -- Part II. Ingesting Data into the Power BI Data Model using R and Python -- 3. Reading CSV Files -- 4. Reading Excel Files -- 5. Reading SQL Server Data -- 6. Reading Data into the Power BI Data Model via an API -- Part III. Transforming Data using R and Python -- 7. Advanced String Manipulation and Pattern Matching -- 8. Calculated Columns using R and Python -- Part IV. Machine Learning & AI in Power BI using R and Python -- 9. Applying Machine Learning and AI to your Power BI Data Models -- 10. Productionizing Data Science Models and Data Wrangling Scripts.
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 to do, if not impossible, using native Power BI tools without Power BI Premium capacity. For example, you will learn to score Power BI data using custom data science models, including 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 through the application of data wrangling features that languages such as R and Python support. If you are a BI developer, 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 to do that. You will: Create advanced data visualizations through R using the ggplot2 package Ingest data using R and Python to overcome the limitations of Power Query Apply machine learning models to your data using R and Python Incorporate advanced AI in Power BI via Microsoft Cognitive Services, IBM Watson, and pre-trained models in SQL Server Machine Learning Services Perform string manipulations not otherwise possible in Power BI using R and Python.
ISBN: 9781484258293
Standard No.: 10.1007/978-1-4842-5829-3doiSubjects--Uniform Titles:
Microsoft .NET Framework.
Subjects--Topical Terms:
615673
Information visualization.
LC Class. No.: QA76.9.I52
Dewey Class. No.: 001.4226
Advanced analytics in power BI with R and Python = ingesting, transforming, visualizing /
LDR
:03255nmm a2200325 a 4500
001
2256704
003
DE-He213
005
20210205100900.0
006
m d
007
cr nn 008maaau
008
220420s2020 cau s 0 eng d
020
$a
9781484258293
$q
(electronic bk.)
020
$a
9781484258286
$q
(paper)
024
7
$a
10.1007/978-1-4842-5829-3
$2
doi
035
$a
978-1-4842-5829-3
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA76.9.I52
072
7
$a
UMP
$2
bicssc
072
7
$a
COM051380
$2
bisacsh
072
7
$a
UMP
$2
thema
082
0 4
$a
001.4226
$2
23
090
$a
QA76.9.I52
$b
W119 2020
100
1
$a
Wade, Ryan.
$3
3527235
245
1 0
$a
Advanced analytics in power BI with R and Python
$h
[electronic resource] :
$b
ingesting, transforming, visualizing /
$c
by Ryan Wade.
260
$a
Berkeley, CA :
$b
Apress :
$b
Imprint: Apress,
$c
2020.
300
$a
xlvi, 391 p. :
$b
ill., digital ;
$c
24 cm.
505
0
$a
Part I. Creating Custom Data Visualizations using R -- 1. The Grammar of Graphics -- 2. Creating R custom visuals in Power BI using ggplot2 -- Part II. Ingesting Data into the Power BI Data Model using R and Python -- 3. Reading CSV Files -- 4. Reading Excel Files -- 5. Reading SQL Server Data -- 6. Reading Data into the Power BI Data Model via an API -- Part III. Transforming Data using R and Python -- 7. Advanced String Manipulation and Pattern Matching -- 8. Calculated Columns using R and Python -- Part IV. Machine Learning & AI in Power BI using R and Python -- 9. Applying Machine Learning and AI to your Power BI Data Models -- 10. Productionizing Data Science Models and Data Wrangling Scripts.
520
$a
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 to do, if not impossible, using native Power BI tools without Power BI Premium capacity. For example, you will learn to score Power BI data using custom data science models, including 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 through the application of data wrangling features that languages such as R and Python support. If you are a BI developer, 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 to do that. You will: Create advanced data visualizations through R using the ggplot2 package Ingest data using R and Python to overcome the limitations of Power Query Apply machine learning models to your data using R and Python Incorporate advanced AI in Power BI via Microsoft Cognitive Services, IBM Watson, and pre-trained models in SQL Server Machine Learning Services Perform string manipulations not otherwise possible in Power BI using R and Python.
630
0 0
$a
Microsoft .NET Framework.
$3
3270493
650
0
$a
Information visualization.
$3
615673
650
0
$a
Python (Computer program language)
$3
729789
650
0
$a
R (Computer program language)
$3
784593
650
0
$a
Big data.
$3
2045508
650
1 4
$a
Microsoft and .NET.
$3
3134847
650
2 4
$a
Big Data/Analytics.
$3
2186785
650
2 4
$a
Big Data.
$3
3134868
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer Nature eBook
856
4 0
$u
https://doi.org/10.1007/978-1-4842-5829-3
950
$a
Professional and Applied Computing (SpringerNature-12059)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9412339
電子資源
11.線上閱覽_V
電子書
EB QA76.9.I52
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入