Data granularity refers to the level of detail or depth of data. It means the level at which data is stored in a fact table. For e.g. if data is stored at the Year level then it is at the lower granularity. If the data is stored at the Month or day level then it at higher granularity.
Data transformation means transforming the data from its original format. Raw data may be in a different format than required by the report or dashboard. Data transformation is required to make the data more suited for the application. An example can be, removing time information from the DateTime field.
Data can be discreet or continuous.
Discreet data contains specific categories. For example, Regions - South and North or Years like 2011, 2012.
Continuous data, on the other hand, is defined by a range and it can take any value over a continuous range.
In Tableau, Dimensions are discreet and Measures are continuous.
Workbooks can be published on Tableau Online or Tableau Server. In the absence of Tableau Server, Workbooks can also be viewed using Tableau Reader. Tableau reader accepts Tableau packaged workbook (twbx) which contains data.