1)
Since there is a small number of data sources judging based off the the example from the CSV file we could build our own architecture (set of scripts) for extracting the data. The data is also only updated on a daily level, so the amount for the load isn’t as great as it could be if it was, for instance, hourly. In order to increase data access I would opt for cloud storage – but I would be downloading the data to physical storage as well in case the server is unavailable, since it is stated that the API server has reliability issues. I believe together with live backup it is reliable enough to store data in cloud, but never only on the server. ETL vendors offer 1GB/sec, but I believe that we don’t need such high speeds for dealing with a data warehouse for the data from the example.

Adding date dimension to a data warehouse
CREATE TABLE dbo.Dates (
 DateID int NOT NULL IDENTITY(1, 1),
 [Date] datetime NOT NULL,
 [Year] int NOT NULL,
 [Month] int NOT NULL,
 [Day] int NOT NULL,
 [QuarterNumber] int NOT NULL,
 CONSTRAINT PK_Dates PRIMARY KEY CLUSTERED (DateID)
)
DECLARE @StartDate datetime
DECLARE @EndDate datetime

--- assign values to the start date and end date we
-- want our reports to cover (this should also take
-- into account any future reporting needs)
SET @StartDate = '01/01/2005'
SET @EndDate = '31/12/2007'

-- using a while loop increment from the start date
-- to the end date
DECLARE @LoopDate datetime
SET @LoopDate = @StartDate

WHILE @LoopDate <= @EndDate
BEGIN
 -- add a record into the date dimension table for this date
 INSERT INTO Dates VALUES (
  @LoopDate,
  Year(@LoopDate),
  Month(@LoopDate),
  Day(@LoopDate),
  CASE WHEN Month(@LoopDate) IN (1, 2, 3) THEN 1
   WHEN Month(@LoopDate) IN (4, 5, 6) THEN 2
   WHEN Month(@LoopDate) IN (7, 8, 9) THEN 3
   WHEN Month(@LoopDate) IN (10, 11, 12) THEN 4
  END

 )

 -- increment the LoopDate by 1 day before
 -- we start the loop again
 SET @LoopDate = DateAdd(d, 1, @LoopDate)
END

IF EXISTS (
 SELECT *
 FROM sysobjects
        WHERE type = 'U'
  AND ID = OBJECT_ID('[dbo].[Dates]')
)
DROP TABLE [dbo].[Dates]

2.
A)

SELECT SUM (AP Amount)
	FROM (Report_August_17) GROUP by expense area
B)
SELECT SUM (AP Amount)
	FROM (Report_August_17) GROUP by expense area AND expense type

3.
I would create a pivot table in excel, from organized data sets. Creating a pivot table in excel is straight-forward.