Speeding Up SSIS Package (Insert and Update) - sql-server

Question

Referred here by #sqlhelp on Twitter (Solved - See the solution at the end of the post).
I'm trying to speed up an SSIS package that inserts 29 million rows of new data, then updates those rows with 2 additional columns. So far the package loops through a folder containing files, inserts the flat files into the database, then performs the update and archives the file. Added (thanks to #billinkc): the SSIS order is Foreach Loop, Data Flow, Execute SQL Task, File Task.
What doesn't take long: The loop, the file move and truncating the tables (stage).
What takes long: inserting the data, running the statement below this:
UPDATE dbo.Stage
SET Number = REPLACE(Number,',','')
## Heading ##
-- Creates temp table for State and Date
CREATE TABLE #Ref (Path VARCHAR(255))
INSERT INTO #Ref VALUES(?)
-- Variables for insert
DECLARE #state AS VARCHAR(2)
DECLARE #date AS VARCHAR(12)
SET #state = (SELECT SUBSTRING(RIGHT([Path], CHARINDEX('\', REVERSE([Path]))-1),12,2) FROM #Ref)
SET #date = (SELECT SUBSTRING(RIGHT([Path], CHARINDEX('\', REVERSE([Path]))-1),1,10) FROM #Ref)
SELECT #state
SELECT #date
-- Inserts the values into main table
INSERT INTO dbo.MainTable (Phone,State,Date)
SELECT d.Number, #state, #date
FROM Stage d
-- Clears the Reference and Stage table
DROP TABLE #Ref
TRUNCATE TABLE Stage
Note that I've toyed with upping Rows per batch on the insert and Max insert commit size, but neither have affected the package speed.
Solved and Added:
For those interested in the numbers: the OP package time was 11.75 minutes; with William's technique (see below this) it's dropped to 9.5 minutes. Granted, with 29 million rows and on a slower server, this can be expected, but hopefully that shows you the actual data behind how effective this is. The key is to keep as many processes happening on the Data Flow task as possible, as the updating data (after the data flow), consumed a signficant portion of time.
Hopefully that helps anyone else out there with a similar problem.
Update two: I added an IF statement and that reduced it from 9 minutes to 4 minutes. Final code for Execute SQL Task:
-- Creates temp table for State and Date
CREATE TABLE #Ref (Path VARCHAR(255))
INSERT INTO #Ref VALUES(?)
DECLARE #state AS VARCHAR(2)
DECLARE #date AS VARCHAR(12)
DECLARE #validdate datetime
SET #state = (SELECT SUBSTRING(RIGHT([Path], CHARINDEX('\', REVERSE([Path]))-1),12,2) FROM #Ref)
SET #date = (SELECT SUBSTRING(RIGHT([Path], CHARINDEX('\', REVERSE([Path]))-1),1,10) FROM #Ref)
SET #validdate = DATEADD(DD,-30,getdate())
IF #date < #validdate
BEGIN
TRUNCATE TABLE dbo.Stage
TRUNCATE TABLE #Ref
END
ELSE
BEGIN
-- Inserts new values
INSERT INTO dbo.MainTable (Number,State,Date)
SELECT d.Number, #state, #date
FROM Stage d
-- Clears the Reference and Stage table after the insert
DROP TABLE #Ref
TRUNCATE TABLE Stage
END

Answer 1

As I understand it, you are Reading ~ 29,000,000 rows from flat files and writing them into a staging table, then running a sql script that updates (reads/writes) the same 29,000,000 rows in the staging table, then moves those 29,000,000 records (read from staging then write to nat) to the final table.
Couldn't you Read from your flat files, use SSIS transfomations to clean your data and add your two additional columns, then write directly into the final table. You would only then work on each distinct set of data once rather than the three (six if you count reads and writes as distinct) times that your process does?
I would change your data flow to transform in process the needed items and write directly into my final table.
edit
From the SQL in your question it appears you are transforming the data by removing comma's from the PHONE field, and then retrieving the STATE and the Date from specific portions of the file path that the currently processed file is in, then storing those three data points into the NAT table. Those things can be done with the derived column transformation in your Data Flow.
For the State and Date columns, set up two new variables called State and Date. Use expressions in the variable definition to set them to the correct values (like you did in your SQL). When the Path variable updates (in your loop, I assume). the State and Date variables will update as well.
In the Derived Column Transformation, drag the State Variable into the Expression field and create a new column called State.
Repeat for Date.
For the PHONE column, in the Derived Column transforamtion create an expression like the following:
REPLACE( [Phone], ",", "" )
Set the Derived Column field to Replace 'Phone'
For your output, create a destination to your NAT table and link Phone, State, and Date columns in your data flow to the appropriate columns in the NAT table.
If there are additional columns in your input, you can choose not to bring them in from your source, since it appears that you are only acting on the Phone column from the original data.
/edit