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03197nam a22004095i 4500 |
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978-1-4842-2352-9 |
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DE-He213 |
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20171103192206.0 |
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cr nn 008mamaa |
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161223s2017 xxu| s |||| 0|eng d |
| 020 |
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|a 9781484223529
|9 978-1-4842-2352-9
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7 |
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|a 10.1007/978-1-4842-2352-9
|2 doi
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| 040 |
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|d GrThAP
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| 100 |
1 |
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|a Acharya, Seema.
|e author.
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| 245 |
1 |
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|a Pro Tableau
|h [electronic resource] :
|b A Step-by-Step Guide /
|c by Seema Acharya, Subhashini Chellappan.
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| 264 |
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|a Berkeley, CA :
|b Apress :
|b Imprint: Apress,
|c 2017.
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| 300 |
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|a XXIII, 845 p. 1063 illus., 1032 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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|a text file
|b PDF
|2 rda
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| 505 |
0 |
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|a Chapter 1: Introducing Visualization and Tableau -- Chapter 2: Working with Single and Multiple Data Sources -- Chapter 3: Simplifying and sorting your data -- Chapter 4: Measure Values and Measure Names -- Chapter 5: Using Quick Table Calculations in Tableau.- Chapter 6: Customizing your data -- Chapter 7: Statistics -- Chapter 8: Chart Forms -- Chapter 9: Advance Visualization Methods -- Chapter 10:Dashboard and Stories -- Chapter 11:Integration of R with Tableau.
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|a Leverage the power of visualization in business intelligence and data science to make quicker and better decisions. Use statistics and data mining to make compelling and interactive dashboards. This book will help those familiar with Tableau software chart their journey to being a visualization expert. Pro Tableau demonstrates the power of visual analytics and teaches you how to: • Connect to various data sources such as spreadsheets, text files, relational databases (Microsoft SQL Server, MySQL, etc.), non-relational databases (NoSQL such as MongoDB, Cassandra), R data files, etc. • Write your own custom SQL, etc. • Perform statistical analysis in Tableau using R • Use a multitude of charts (pie, bar, stacked bar, line, scatter plots, dual axis, histograms, heat maps, tree maps, highlight tables, box and whisker, etc.) What you’ll learn: • How to connect to various data sources such as relational databases (Microsoft SQL Server, MySQL), non-relational databases (NoSQL such as MongoDB, Cassandra), write your own custom SQL, join and blend data sources, etc. • How to leverage table calculations (moving average, year over year growth, LOD (Level of Detail), etc. • How to integrate Tableau with R • How to tell a compelling story with data by creating highly interactive dashboards.
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| 650 |
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|a Computer science.
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| 650 |
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|a Computer programming.
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| 650 |
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|a Database management.
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| 650 |
1 |
4 |
|a Computer Science.
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| 650 |
2 |
4 |
|a Big Data.
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| 650 |
2 |
4 |
|a Programming Techniques.
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| 650 |
2 |
4 |
|a Database Management.
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| 700 |
1 |
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|a Chellappan, Subhashini.
|e author.
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
0 |
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|t Springer eBooks
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| 776 |
0 |
8 |
|i Printed edition:
|z 9781484223512
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| 856 |
4 |
0 |
|u http://dx.doi.org/10.1007/978-1-4842-2352-9
|z Full Text via HEAL-Link
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| 912 |
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|a ZDB-2-CWD
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| 950 |
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|a Professional and Applied Computing (Springer-12059)
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