A department in my company gets a report every day as a a spreadsheet of invalid debit cards. It can contain 0 to hundreds of different clients. The client ID is a column on the spreadsheet. They have to take the records for Client A, make a spreadsheet called, say Client_A_20170602.xlsx and email that to client A. Then they have to do the same for client B. If there are just a few clients then it is not a big deal to do it manually, but today they had 115 different clients. They want to know if I can write an SSIS package that will automate this process.
I could bring the spreadsheet into an SQL table, do a SELECT DISTINCT on the Client ID, put the results into a temp table, go through each client on the temp table, get their records, and put them into a date stamped table. I could then (back in SSIS) use a FOR EACH loop to look for files that contain the date stamp and write them out to spreadsheets.
Can this work? Can somebody suggest a better solution?
Thanks,
Dick
Another solution would be an SSRS Report with each client getting a subscription that emails them their data.
Related
I need to implement batch processing in my SSIS package to send data from source to destination tables in batches. But in my source table there is no unique column that I can use for batch processing and I can't create one it is client's tables.
Also source queries contain union function as well, so how can I bring a unique column to my source table in SSIS and then implement batch processing?
is it a one time thing or regular? if there is a date you can filter on that and just batch per day, month, year, or anything. If the package runs once every day you can just filter on that.
you say there is no unique column, but isnt there a combination of factors that make it unique? those work just as well.
We have a legacy ERP system that stores data in flat files. we have replicated these flat files in SQL Server database pretty much as it is.
Some of the sales tables store historical data in multiple columns without storing any dates with them. the name of the column will tell us which month the sales data belong to. Sales01 is current month, Sales02 is previous month, Sales03 is the month before and so on. Same with sales Qty and margin. i.e. Qty01, qty02 and margin01 and margin 02 and so on. This is repeated for each customer and each item sold.
Now, I am working on a small project where I have to design a small DB for reporting with some tables that will be fed by this main database.
I want to load this data in such a way that these values from each month are stored in rows with a month-year or date from first day of the month in another column so I can use where clause with dates.
Not sure what would the be best way to go? I have written a stored proc in the past to load this data this way, but wonder if there a better way to go.
Some how I can use SSIS Pivot transformation?
or just use Pivot or similar statement to do this in an SP?
I will most likely be using this practice to built a data warehouse in future.
Do you know how to transfer only new records between two different databases (ie. Oracle and MSSQL) using SSIS? There is no problem transfering new data only between two tables in the same database and server, but is this possible to do such operation between completely different servers and databases?
Ps. I know about solution using Lookup but it is not very efficient if anybody needs to check and add a lot of records (50k and more) several times per day. I would like to operate with new data only.
You have several options:
Timestamp based solution
If you have a column which stores the insertation time in the source system, you can select only the new records created since the last load. With the same logic, you can transfer modified records too, just mark the records with the timestamp value when it change.
Sequence based solution
If there is a sequence in the source table, you can load the new records based on that sequence. Query the last value from the destination system, then load avarything which is larger than that value.
CDC based solution
If you have CDC (Change Data Capture) in your source system, you can track the changes and you can load them based on the CDC entries.
Full load
This is the most resource hungry solution: you have to copy all data from the source to the destination. If you do not have any column which marks the new records, you should use this solution.
You have several options to achieve this:
TRUNCATE the destination table and reload it from source
Use a Lookup component to determine which records are missing
Load all data from source to a temporary table and write a query which retrieves the new/changed records.
Summary
If you have at least one column, which marks the new/modified records, you can use it to implement a differential/incremental load with SSIS. If you do not have any clue, which columns/rows are changed, you have to load (or at least query) all of them.
There is no solution which enables a one-query (INSERT .. SELECT) solution using multiple servers without transferring all data. (Please note, that a multi-server query using Linked Servers are transfers the data from the source system).
What about variables? Is it possible to use the same variable between different databases and servers in SSIS?
I would like to transfer last id number from a destination table and transfer it to the source table (different server!).
I can set a variable in a database scope like this:
DECLARE #Last int
SET #Last = (SELECT TOP 1 Id FROM dbo.Table_1 ORDER BY Id DESC)
SELECT *
FROM dbo.Table_2
WHERE ID > #Last;
However it works between two tables in the same database (as a SQL command) only. I can create a variable for a entire SSIS package in Variables --> Add variable, but I don't know it is possible to use the variable in a similar way as above - to keep an information about last id in a destination table and pass it to another table on a source server as data limit.
I have a desktop application through which data is entered and it is being captured in MS Access DB. The application is being used by multiple users(at different locations). The idea is to download data entered for that particular day into an excel sheet and load it into a centralized server, which is an MSSQL server instance.
i.e. data(in the form of excel sheets) will come from multiple locations and saved into a shared folder in the server, which need to be loaded into SQL Server.
There is a ID column with IDENTITY in the MSSQL server table, which is the primary key column and there are no other columns in the table which contains unique value. Though the data is coming from multiple sources, we need to maintain single auto-updating series(IDENTITY).
Suppose, if there are 2 sources,
Source1: Has 100 records entered for the day.
Source2: Has 200 records entered for the day.
When they get loaded into Destination(SQL Server), table should have 300 records, with ID column values from 1 to 300.
Also, for the next day, when the data comes from the sources, Destination has to load data from 301 ID column.
The issue is, there may be some requests to change the data at Source, which is already loaded in central server. So how to update the data for that row in the central server as the ID column value will not be same in Source and Destination. As mentioned earlier ID is the only unique value column in the table.
Please suggest some ides to do this or I've to take up different approach to accomplish this task.
Thanks in advance!
Krishna
Okay so first I would suggest .NET and doing it through a File Stream Reader, dumping it to the disconnected layer of ADO.NET in a DataSet with multiple DataTables from the different sources. But... you mentioned SSIS so I will go that route.
Create an SSIS project in Business Intelligence Development Studio(BIDS).
If you know for a fact you are just doing a bunch of importing of Excel files I would just create many 'Data Flow Task's or many Source to Destination tasks in a single 'Data Flow Task' up to you.
a. Personally I would create tables in a database for each location of an excel file and have their columns map up. I will explain why later.
b. In a data flow task, select 'Excel Source' as the source file. Put in the appropriate location of 'new connection' by double clicking the Excel Source
c. Choose an ADO Net Destination, drag the blue line from the Excel Source to this endpoint.
d. Map your destination to be the table you map to from SQL.
e. Repeat as needed for each Excel destination
Set up the SSIS task to automate from SQL Server through SQL Management Studio. Remember you to connect to an integration instance, not a database instance.
Okay now you have a bunch of tables right instead of one big one? I did that for a reason as these should be entry points and the logic to determinate dupes and import time I would leave to another table.
I would set up another two tables for the combination of logic and for auditing later.
a. Create a table like 'Imports' or similar, have the columns be the same except add three more columns to it: 'ExcelFileLocation', 'DateImported'. Create an 'identity' column as the first column and have it seed on the default of (1,1), assign it the primary key.
b. Create a second table like 'ImportDupes' or similar, repeat the process above for the columns.
c. Create a unique constraint on the first table of either a value or set of values that make the import unique.
c. Write a 'procedure' in SQL to do inserts from the MANY tables that match up to the excel files to insert into the ONE 'Imports' location. In the many inserts do a process similar to:
Begin try
Insert into Imports (datacol1, datacol2, ExcelFileLocation, DateImported) values
Select datacol1, datacol2, (location of file), getdate()
From TableExcel1
End try
-- if logic breaks unique constraint put it into second table
Begin Catch
Insert into ImportDupes (datacol1, datacol2, ExcelFileLocation, DateImported) values
Select datacol1, datacol2, (location of file), getdate()
From TableExcel1
End Catch
-- repeat above for EACH excel table
-- clean up the individual staging tables for the next import cycle for EACH excel table
truncate TableExcel1
d. Automate the procedure to go off
You now have two tables, one for successful imports and one for duplicates.
The reason I did what I did is two fold:
You need to know more detail than just the detail a lot of times like when it came in, from what source it came from, was it a duplicate, if you do this for millions of rows can it be indexed easily?
This model is easier to take apart and automate. It may be more work to set up but if a piece breaks you can see where and easily stop the import for one location by turning off the code in a section.
I receive new data files every day. Right now, I'm building the database with all the required tables to import the data and perform the required calculations.
Should I just append each new day's data to my current tables? Each file contains a date column, which would allow for a "WHERE" query in the future if I need to analyze data for one particular day. Or should I be creating a new set of tables for every day?
I'm new to database design (coming from Excel). I will be using SQL Server for this.
Assuming that the structure of the data being received is the same, you should only need one set of tables rather than creating new tables each day.
I'd recommend storing the value of the date column from your incoming data in your database, and also having a 'CreateDate' column in your tables, with a default value of 'GetDate()' so that it automatically gets populated with the current date when the row is inserted.
You may also want to have another column to store the data filename that the row was imported from, but if you're already storing the value of the date column and the date that the row was inserted, this shouldn't really be necessary.
In the past, when doing this type of activity using a custom data loader application, I've also found it useful to create log files to log success/error/warning messages, including some type of unique key of the source data and target database - ie. if coming from an Excel file and going into a database column, you could store the row index from Excel and the primary key of the inserted row. This helps tracking down any problems later on.
You might want to consider having a look at SSIS (SqlServer Integration Services). It's the SqlServer tool for doing ETL activities.
yes, append each day's data to the tables; 1 set of tables for all data.
yes, use a date column to identify the day that the data was loaded.
maybe have another table with a date column and a clob column. The date to contain the load date and the clob to contain the file that you imported.
Good question. You most definitely should have a single set of tables and append the data daily. Consider this: if you create a new set of tables each day, what would, say, a monthly report query look like? A quarterly report query? It would be a mess, with UNIONs and JOINs all over the place.
A single set of tables with a WHERE clause makes the querying and reporting manageable.
You might do a little reading on relational database theory. Wikipedia is a good place to start. The basics are pretty straightforward if you have the knack for it.
I would have the data load into a stage table regardless and append to the main tables after. Once a week i would then refresh all data in the main table to ensure that the data remains correct as per the source.
Marcus