Are you trying to import an Excel file into SQL Server using SQL Server Integration services…And ran into error that has words like “Non unicode” and “unicode”? Then this blog is for you.
Why does this error occur?
Well it turns out that things like SQL Server and Excel have encoding standards that they follow which provides them a way to process, exchange & store data. BUT turns out that SQL Server and Excel use different standards.
So, the solution is simple right? Import the data from Excel into non-Unicode format because that’s what you need for SQL Server.
So how do you that? Between your Source and Destination tasks, include a task called “Data conversion” and do the following for all columns that have text:
And in the destination task, you’ll have to make sure that the mapping section using the new output aliases that you defined in the “data conversion” step.
In this post, we learned about how to solve a common error that pops up when you try to import excel file to sql server using SSIS. Hope that helps.
As a part of Business Intelligence projects, we spend a significant amount in extracting, transforming and loading data from source systems. So it’s always helpful to know as much as you can about the data sources like NULLS, keys, statistics among other things. One of the things that I like to do if the data is unknown is to make sure that I get the candidate keys correct to make sure the key used can uniquely identify the rows in the data. It’s really helpful if you do this upfront because it would avoid a lot of duplicate value errors in your projects.
So here’s a quick tutorial on how you can check the candidate key profile using data profiling task in SSIS, You need to perform two main tasks: 1. Generate the xml file using the Data profiling task in SSIS 2. View the content of the xml file using the Data Profile Viewer Tool or using the Open Profile Viewer option in the Data Profiling task editor in SSIS.
Here are the steps: 1a. Open SQL Server Data Tools (Visual Studio/BIDS) and the SSIS project type 1b. Bring in Data Profiling Task on Control Flow 1c. Open the Data Profiler Task editor and configure the destination folder that the tasks uses to create the XML file. You can either create a new connection or use an existing one. If you use an existing connection, make sure that you are setting the OverwriteDestination property to True if you want the file to be overwritten at the destination.
1d. Click on Quick Profile to configure the data source for the data profiler task
1e. In the quick profile form, you’ll need to select the connection, table/view and also specify what you to need to computer. For candidate key profile, make sure that the candidate key profile box is checked.
1f. Run the Task and a XML file should be placed at the destination you specified in step 1C.
Now, It’s time to view what profiler captured.
2a. you can open “Data Profile Viewer” by searching for its name in the start button.
2b. once it opens up, click on open and browse to the xml file generated by the data profiling task.
2c. once the file opens up, you can the candidate key profiles.
2d. Alternatively, You can also open the data profile viewer from the “Data Profiling Task” in SSIS. Go to the Editor > Open Profile Viewer:
Conclusion: In this post, you saw how to profile data using the Data Profiling Task in SSIS.
How to use Execute SQL Task in SSIS to assign value to a variable?
This is a beginner level post so I’ll show you how you can use Execute SQL Task to assign a value to a variable. Note that variables can also be given full result set. With that said, here are the steps:
1. Create the query against the source system
Example: ((Note the column name, this will be handy later!)
2. Open SSIS Project > Create the variable
3. Now, drag a Execute SQL Task to Control Flow. Rename it. And go to Edit. Configure SQL Statement Section
4. Now, since we want to store a value to the variable, change the Result Set property to Single Row
5. One last step, go to result set section and map Result Name (remember the column name from #1?!) with Variable Name:
This is a beginner level post targeted at Developers who are new to SSIS and may not have worked on making a SSIS staging load package incremental. In this post, I’ll share a design pattern that I’ve used to make staging loads incremental which pulls in just new or changed rows from source system.
Before we begin, why would you want to make a staging load incremental when pulling data from source systems? Two main reasons: 1) the source system may not keep historical data but your Business Intelligence system needs to have it 2) it is also faster and puts less strain on source system while doing data pull.
since this is a beginner’s level, I am going to show you a design pattern when you have a column in the source system that can identify New or Changed Rows. If you do not have a column in the source system that identifies new or changed rows then this topic becomes an advanced level and is out of scope for now.
with that said, let’s see the steps involved.
1) I’ve this kill and fill (a.k.a Full Load) package in my SSIS dev environment:
2) now, let’s make this incremental. so I’ll go ahead and delete the Execute SQL Task that truncates the data.
3) Now, we need a way to be able to pass in the query in our DFT that gets only the new or changed rows. The source system that I am using has a field called modified date and that’s what I’ll be using to pull in new or changed data.
4) Let’s create the query using the help of variables, execute sql task and script task. (Later, we’ll store in the query in a variable and use that variable in the Data Flow Task)
4a) create ModfiedDate and Query variables
4b) create an Execute SQL Task to run the query to get the max ModifiedDate and write it in the ModifiedDate variable that you created.
4c) create a Script Task to get the query using the ModifiedDate variable. This query will extract only new or changed rows from your source system
Dim ModifiedDate As String Dim sQuery As String ModifiedDate = Dts.Variables("ModifiedDate").Value.ToString sQuery = String.Concat("SELECT [SalesOrderID],[SalesOrderDetailID],[CarrierTrackingNumber],[OrderQty],[ProductID],[SpecialOfferID],[UnitPrice],[ModifiedDate] FROM [sales].[SalesOrderDetail] where [ModifiedDate] >= ‘", String.Concat(ModifiedDate, "’")) MsgBox(String.Concat(" ", sQuery)) Dts.Variables("Query").Value = sQuery
5) Now, go to variables section and give a default value to user::Query variable because if you do not do this you won’t be able to go to next steps.
6) Go to Data Flow and change the OLEDB source to use the SQL Command from variable and use the user::Query variable
7) Switch to Control flow and Make sure your precedence constraints are set to run Execute SQL Task > Script Task > Data Flow Task
8) Run the package and you should see the dynamic query that gets generated. Tip: sometimes it’s helpful to run this query that’s generated against the source system for troubleshooting purpose.
9) On the successful run of the package verify that only new rows got added to the staging table. Also, if there are duplicate rows in the staging table, this might need to handled during the dimension load or fact load. you can also consider having the logic in place here to avoid duplicate records in your staging table.
In this post, you saw how to make a staging load package incremental.
you are working on an SSIS package to load a table from a source system and you get an error “The value violated the integrity constraints for the column error” – how do you solve it?
one the things that the error message should also tell you would be column name. What you want to do is check the table definition of the destination table for any integrity constraints like NOT NULL or PRIMARY KEY. Now once you have that information, go back to your source and figure out if it’s trying to add NULL values in a column that has NOT NULL integrity constraint. Or may be ETL logic is trying to insert duplicate value to the column that has primary key constraint.
Also, the don’t alter the destination table to accept NULL’s or remove integrity constraint. You want to put a logic in your ETL OR fix the data integrity at source. You can use TSQL functions like NULLIF to handle NULL values while querying source systems.
Conclusion: In this post, we saw how to solve the “The value violated the integrity constraints for the column” error in SSIS.
if you’ve a sizable number of rows that need update in SSIS, then you don’t want to do a row based update commands because it won’t be efficient. if you’ve good number of rows that need to be updated then you can use the SET Based updates. it’s a common design pattern for loading dimensions in a data warehouse.
Find the steps below:
There are two main steps to achieve this:
1) Populate the “update” table with rows that have been changed. Note that a new table needs to be created.
2) Run the SQL command to do a SET based update
Let’s see each step in detail:
1) Populate the “update” table with rows that have changed.
For this step, first make sure that you have a table that can hold the rows that have been updated.
Then create a Data Flow that take the source data and lookups the data that has changed and puts it in an update/staging table:
Note: I’ve used a small table for demo purpose but you won’t use this method if you don’t have a more rows to update because as you can see this method adds an overhead of putting the data in the update table first.
2) Run the SQL command to do a SET based update
Here’s the sample query:
[code language=”sql”] — run the update command Update Dim Set [Column1]=Upd.[Column1] [Column2]=Upd.[Column2] — [Column3]=Upd.[Column3] — … From dbo.DimDestination Dim Inner Join dbo.Destination_update Upd on Dim.Destination_sk=Upd.Destination_sk
Visualizing stuff is powerful – if you have visualized something then you can remember it for a longer period of time. So in this post, we will visualize what the Merge Transformation in SQL Server Integration services (SSIS) Does:
1) Do not Confuse it with Merge Join Tranformation. “Merge Join” is NOT same as “Merge”
2) Merge Transformation can accept only TWO (sorted) data sources. Whereas if you want to “combine” more than two data-sets, then go for Union ALL tranformation