Pro Tableau: A Step-By-Step Guide (Paperback)

Table of content Chapter 1: Introducing Visualization and Tableau Why Visualization? What is Visualization? Positioning of Tableau Tableau product lines File types in Tableau .twb .twbx .tds .tdsx .tde .tbm Chapter 2: Working with Single and Multiple Data Sources Desktop Architecture Data Connection Page Connect to a File Excel Open with legacy connection Text Microsoft Access R data file (.rdata) Connect to a Server Microsoft SQL Server MySQL NoSQL Databases (MongoDB, Cassandra) Metadata Grid Using Data Extracts All about Joins Using Custom SQL Using Data Blending Chapter 3: Simplifying and Sorting your Data Filtering on dimensions and measures Soring on single dimension - Primary sort Sorting on more than one dimension - Secondary Sort Slicing your data by date Discrete dates Continuous dates Organizing your data Groups Hierarchies Sets Static sets Dynamic sets Difference between groups and sets Chapter 4: Measure Values and Measure Names Using measure values and measure names in a view Chapter 5: Using Quick Table Calculations in Tableau Running Total Percent of Total Percentile Rank Moving average Year over Year Growth Level Of Detail (LOD) calculations Chapter 6: Customizing your Data String Calculations Number Calculations Date Calculations Logical Calculations Chapter 7: Statistics Descriptive Statistics Sum Average Min Max Count Count(distinct) Median Standard Deviation Variance Using the Analytics Pane Constant Lines Average Lines Five magical number summary Box and whisker plot Trend Lines Forecast Chapter 8: Chart Forms Bar Chart Pie chart Line graph Scatter Plot Histogram Heat Map Tree Map Highlight Table Chapter 9: Advance Visualization Methods Waterfall Charts Gantt View Bullet Graph Chapter 10: Dashboard and Stories Creating an interactive dashboard Adding Actions to your dashboard Telling stories with data Chapter 11: Integration of R with Tableau Functions such as (SCRIPT_INT(), SCRIPT_REAL(),SCRIPT_BOOL(), SCRIPT_STR()) Data Mining Affinity Analysis K-means Clustering