Executive managers and analysts are frequently turning to Tableau to get to actionable insights stored in their business intelligence environments. In many companies, Tableau is complementing existing business intelligence tools, such as those from IBM Cognos, SAP Business Objects, Oracle and Microsoft.
In this on-demand webinar, “Tableau Zen Master” Chuck Hooper highlights the ease of use of this software for interactive data visualization and analysis.
We build an actual dashboard, and also demonstrate how this applies across multiple industries, including manufacturing, retail, healthcare, education, and banking.
For a free, 14-day full version trial of Tableau, click here.
Presenter
Chuck Hooper
Business Intelligence Consultant
Chuck Hooper is the former head of Tableau’s consulting organization. He is one of the few individuals officially designated as a “Tableau Zen Master,” and has received this recognition for the past three years, since Tableau first started bestowing this honor.
He conducts training sessions on the use of Tableau Software products and does speaking engagements on visual analytics, data warehouse design, and other business intelligence topics, at both the technical and executive levels. His career includes over five decades of business and IT experience.
Read moreWebinar demonstrations outline
Ease of Use Demo
- Tableau does automatic intelligent analysis of data files brought into the dashboard
- Example: Connect to Excel file on desktop and bring data into Tableau
- Dimensions are where Tableau categorizes and places things that are used to analyze the data (i.e. the way data is categorized)
- Measures are where Tableau puts numeric values associated with the data (i.e. areas that might require or warrant calculations)
- Simply double-click or drag and drop on dimensions and measures to bring into worksheets in dashboard, including the main shelf, side shelf, top shelf options (no need to even touch the keyboard for these purposes)
- Change data views including chart type, color coding, values, dates, etc. with simple clicks on various fields
- Create multiple sheets with different types of data charts within the same dashboard
- Creating a bar chart
- View multiple dimensions and values such as sales, profit, and product views by region, and differentiate by:
- Length of bar (sales)
- Color of bar (profit)
- Number of rows (region)
- Number of columns (product category)
- Thickness of bar (shipping dollars)
- Change from sum to average by simply clicking on field and choosing alternate view
- View multiple dimensions and values such as sales, profit, and product views by region, and differentiate by:
- Creating a scatter plot chart
- Tableau will automatically select and suggest the best way to view the data (in terms of chart type) based on the measures and dimensions selected
- View multiple dimensions and values such as sales, profit, and product views by region, and differentiate by:
- Scatter plot axis (profit)
- Color (difference in regions)
- Note: Tableau also has a “color blind” palette built in as an option
- Filter shelf (ship date)
- Shape shelf (product categories)
- Lasso data points, right click to view underlying data
- Creating a map chart
- Tableau automatically recognizes geographic dimensions (such as state and province) from your original data document, and generates latitude and longitude measures
- Alter color and size of data mark to view and differentiate between different measures, such as sales and profit
- Map options include adding view of per capita income per state; lots of demographic variables are included as part of the Tableau
- Creating a date chart
- Look at multiple years, by quarter, or drill down to monthly views of data, and add color variances for better visibility
- Multiple charts (sheets) in one interactive dashboard view
- Making one chart a driver for other charts
- Choosing a measure or dimension on the driver chart will automatically change and align the data view on all the other charts associated within the same dashboard
- Publish workbook to Tableau hosted online server (note, must extract data first)
More Advanced Capabilities Demo
- Tableau has a direct interface connection to R, a free statistical package open source
- Multi-variant outlier package (there are 7,000+ packages to choose from with R)
- Add color coding to each one of the outliers
- Tableau can also create trellis charts, as well as gauges, waterfall, and spider charts
- When you hover over any mark in Tableau, you get tool tips
- Tableau forecasting is also built in with multiple editing options in terms of forecast length, etc.
- Map ranges and masks
- Drop down view list eliminates need for tabs to change views
- Big Data Wine example
- Looking at multiple dimensions and measure (such as brand, flavor, dollars spent) all executable in sub-second response time
- Not aggregated data; looking at a lot of detailed rows of data
- Sub-second response time is coming from a Tableau data extract on notebook computer with over 1 billion rows of data
Industry Examples Demo
- Banking
- Wanted to understand why customers were leaving the bank and pulling their accounts
- Industry database outlines various reasons people leave
- Local bank data comes from SQL server
- National average comes from Excel database
- Calculations done taking data from both; two different databases on one chart
- Healthcare
- Blood supply for last 30 days
- Three types of product: red-blood cells, platelets, fresh frozen plasma
- Blue reflects where transfusion was medically indicated, red reflects where it was not medically indicated
- Why would a doctor prescribe it if not indicated?
- Click into red data to see further details (who is prescribing it, cost per unit, etc.)
- Education
- Masters program, number and percent of students studying abroad
- Sort by region via drop down options
- Manufacturing
- Manufacturing score card: KPIs performance versus target by retailer
- Yellow is neutral/ok, red is bad, green is good
- Executive dashboard that satisfies the needs of many users
- Simple clicks to gray out the data you don’t want to view, and drill down to data that matters
- Speed to shelf chart
- How many days between authorizing order to time it sold, time product actually hits the shelf to seeing first sales record, etc.
- Price elasticity models
- If I raise the price of one of my products, how does it impact the sales of my other products?
- Manufacturing score card: KPIs performance versus target by retailer