sharatainapur / tableau

Tableau

Superstore Sales Dataset

Day 1

• Tableau sheet to show which region made atleast 13k profit in home office segment for the superstore sales dataset. Usage of Filters.
• Bar chart to answer the same - East(26k) and West(16k) both the regions have more than 13k profit in the home-office segment.

Day 2

• Data Cleaning, using Data interpreter. Splitting columns, Renaming. Column or Bar chart for marketwise sales and profit.
• Adding appropriate format like percentage for discounts, currency for sales and profit. Saving the updated data source.

Day 3

• Combining Data, Editing Relationships, Single Data Source, Multiple Data connections and performing Table Joins,
• Performing different joins on the tables in Tableau - Inner Join, Full Outer Join, Left and Right Join.
• Unions to increase the number of rows - different months data in different sheets or tables could be combined using Unions.

Day 4

• Data Extracts - a local copy of the data source that is fast to access. (Creates .hyper file) Restricted view of the data.
• Refreshing and Filtering the Data and providing a subset of the data - hiding unused fields and updating extracts.
• Pros - Speed, Portability, Sharing, Include and Exclude subsets of Data
• Cons - Security Risk, Not a live connection, Need for Refresh.

Day 5

• Comparing Measures - Continuous fields.
• Creation of Combined Axis Chart - makes it easier for comparison and Dual Axis Chart - having different magnitudes or scale for the two measures.
• Bar in a Bar Chart - effective to depict KPI or metrics like Sales and Sales target etc. Useful for comparison and mainly in KPI trick.
• Crosstab or Highlight Table (Crosstab + Color) for visualizing data in tabular format. Identifying highest and lowest by color code and using Mark Types as square.
• Scatter plot or Bubble chart - needs 2 continous measures, use of detail and mark-type. Additionally learnt about trend line and annotations and pages to create animations.

• Added Tableau packaged workbook as it contains the data source and the worksheets.

Day 6

• Calculated Fields - to transform data and to add extra columns to data.
• String functions such as Lower and Upper , Cross Database Joins - for having matching fields in two datasets - Eg: SOUTH and INDIA-SOUTH (Split Function)
• Running Sum in Table Calculations - exists just in the view and not in data measure or dimensions.
• Quick Table calculations and Direct Table calculations. Percentage of total and *Level of Detail calculations.
• Calculate Time Directions - Date Diff Function and IF CASE calculations for profit loss.
• Text or Cross Table calculations having DIRECTIONS grand totals ACROSS, DOWN and for TABLE.

• Added Day 6 Tableau packaged workbook with 4 sheets.

Day 7

• Usage of Mapping Data in visualization. Different Types: Area Map (Marktype - MAP), Symbol Map (Pie, Scatter) - (Marktype - Pie or Automatic)
• Customise looks of maps by editing the Mapping Layers and Style.
• Using location coordinates and changing data type for plotting maps - latitude and longitude coordinates and addition of new rows by using annotations.
• Spatial Calculations - learnt about MAKEPOINT(), MAKELINE() and BUFFER() functions in calculations.
• Performed a custom split to fetch the state names from the City, State column and created charts for Sales by Segment in USA (Symbol Map).

• Added Day 7 Tableau workbook with 2 sheets.