anchor.diff:  (**
   
   ##Automatic schema inference
  -Unlike some non-relational data stores, Azure Table Storage does actually maintain schema information
  -at the row level in the form of EDM metadata. This can be interrogated in order to infer a table's shape,
  -as well as help query data. Let's look at the schema of the row ``fred.1`` in the ``employee``
  -table. 
  +Unlike some non-relational data stores, Azure Table Storage *does* maintain schema information at the
  +row level in the form of EDM metadata. This can be interrogated in order to infer a table's shape, as
  +well as help query data. Let's look at the schema of the row ``fred.1`` in the ``employee`` table.
   *)
   
   (*** hide ***)
  
positive.code: type FirstTwentyRows = AzureTypeProvider<"UseDevelopmentStorage=true", schemaSize = 20>
  
  (** 
  In addition, an extra "Values" property is available which exposes all properties on the entity
  in a key/value collection - this is useful for binding scenarios or e.g. mapping in Deedle frames.
  *)
  
negative.code:     fred.Name fred.YearsWorking fred.Dob fred.Salary fred.IsManager
  (*** include-output: fred ***)
  
  (**
  ### Optional type generation
  
  The Storage Type Provider will also intelligently map fields which are not always populated in the table.
  For example, given the following rows, we can see that two columns are not always populated. *)
  
  (*** hide ***)
  