Amazon S3 CSV File Connector for MS Excel Amazon S3 CSV File Connector can be used to read CSV Files stored in AWS S3 Buckets. Using this you can easily integrate AWS S3 CSV File data. It's supports latest security standards, and optimized for large data files. It also supports reading compressed files (e.g. GZip /Zip). In this article you will learn how to quickly and efficiently integrate Amazon S3 CSV File data in MS Excel without coding. We will use high-performance Amazon S3 CSV File Connector to easily connect to Amazon S3 CSV File and then access the data inside MS Excel. Let's follow the steps below to see how we can accomplish that! Download Documentation Amazon S3 CSV File Connector for MS Excel is based on ZappySys Amazon S3 CSV Driver which is part of ODBC PowerPack. It is a collection of high-performance ODBC drivers that enable you to integrate data in SQL Server, SSIS, a programming language, or any other ODBC-compatible application. ODBC PowerPack supports various file formats, sources and destinations, including REST/SOAP API, SFTP/FTP, storage services, and plain files, to mention a few.

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Create ODBC Data Source (DSN) based on ZappySys Amazon S3 CSV Driver

Step-by-step instructions

To get data from Amazon S3 CSV File using MS Excel we first need to create a DSN (Data Source) which will access data from Amazon S3 CSV File. We will later be able to read data using MS Excel. Perform these steps:

1. Download and install ODBC PowerPack.

2. Open ODBC Data Sources (x64):

   

3. Create a User data source (User DSN) based on ZappySys Amazon S3 CSV Driver

   ZappySys Amazon S3 CSV Driver

   
   • Create and use User DSN if the client application is run under a User Account. This is an ideal option in design-time, when developing a solution, e.g. in Visual Studio 2019. Use it for both type of applications - 64-bit and 32-bit.
   • Create and use System DSN if the client application is launched under a System Account, e.g. as a Windows Service. Usually, this is an ideal option to use in a production environment. Use ODBC Data Source Administrator (32-bit), instead of 64-bit version, if Windows Service is a 32-bit application.

4. Create and configure a connection for the Amazon S3 storage account.

   

5. You can use select your desired single file by clicking [...] path button.

   mybucket/dbo.tblNames.csv

   dbo.tblNames.csv

   
   
   
   ----------OR----------

   You can also read the multiple files stored in Amazon S3 Storage using wildcard pattern supported e.g. dbo.tblNames*.csv.
   

   Note: If you want to operation with multiple files then use wild card pattern as below 
   (when you use wild card pattern in source path then system will treat target path as folder regardless you end with slash)
   
   mybucket/dbo.tblNames.csv (will read only single .CSV file)
   mybucket/dbo.tbl*.csv (all files starting with file name)
   mybucket/*.csv (all files with .csv Extension and located under folder subfolder)
   

   mybucket/dbo.tblNames*.csv

   
   
   
   ----------OR----------

   You can also read the zip and gzip compressed files also without extracting it in using Amazon S3 CSV Source File Task.

   mybucket/dbo.tblNames*.gz

   

6. Navigate to the Preview Tab and let's explore the different modes available to access the data.
   

   1. --- Using Direct Query ---

      Click on Preview Tab, Select Table from Tables Dropdown and select [value] and click Preview.
      

   2. --- Using Stored Procedure ---

      Note : For this you have to Save ODBC Driver configuration and then again reopen to configure same driver. For more information click here.
      

      Click on the Custom Objects Tab, Click on Add button and select Add Procedure and Enter an appropriate name and Click on OK button to create.
      

      1. --- Without Parameters ---

         Now Stored Procedure can be created with or without parameters (see example below). If you use parameters then Set default value otherwise it may fail to compilation)
         
         

      2. --- With Parameters ---

         Note : Here you can use Placeholder with Paramters in Stored Procedure.
         Example : SELECT * FROM $ WHERE OrderID = '<@OrderID, FUN_TRIM>' or CustId = '<@CustId>' and Total >= '<@Total>'
         

         

   3. --- Using Virtual Table ---

      Note : For this you have to Save ODBC Driver configuration and then again reopen to configure same driver. For more information click here.
      

      ZappySys APi Drivers support flexible Query language so you can override Default Properties you configured on Data Source such as URL, Body. This way you don't have to create multiple Data Sources if you like to read data from multiple EndPoints. However not every application support supplying custom SQL to driver so you can only select Table from list returned from driver.

      Many applications like MS Access, Informatica Designer wont give you option to specify custom SQL when you import Objects. In such case Virtual Table is very useful. You can create many Virtual Tables on the same Data Source (e.g. If you have 50 Buckets with slight variations you can create virtual tables with just URL as Parameter setting).

      vt__Customers
      DataPath=mybucket_1/customers.csv
      
      vt__Orders
      DataPath=mybucket_2/orders.csv
      
      vt__Products
      DataPath=mybucket_3/products.csv
      

      1. Click on the Custom Objects Tab, Click on Add button and select Add Table and Enter an appropriate name and Click on OK button to create.
         
      2. Once you see Query Builder Window on screen Configure it.
         
      3. Click on Preview Tab, Select Virtual Table(prefix with vt__) from Tables Dropdown or write SQL query with Virtual Table name and click Preview.
         

7. Click OK to finish creating the data source

8. That's it; we are done. In a few clicks we configured the to Read the Amazon S3 CSV File data using ZappySys Amazon S3 CSV File Connector

Read data in Excel from the DSN

1. In Excel click Data, then select Get Data, proceed with From Other Sources and choose From ODBC item. This will get data from ODBC data source we created:

   

2. A small window opens, then simply select the data source you created in previous steps:

   AmazonS3CsvFileDSN

   

3. Most likely, you will be asked to authenticate to a newly created DSN. Just select Windows authentication option together with Use my current credentials option:

   AmazonS3CsvFileDSN

   

4. Finally, you will be asked to select a table or view to get data from. Select one and load the data!

   

5. Finally, finally, use data extracted from Amazon S3 CSV File API in an Excel worksheet:

   

Conclusion

In this article we showed you how to connect to Amazon S3 CSV File in MS Excel and integrate data without any coding, saving you time and effort. It's worth noting that ZappySys Amazon S3 CSV Driver allows you to connect not only to Amazon S3 CSV File, but to any Java application that supports JDBC (just use a different JDBC driver and configure it appropriately).

We encourage you to download Amazon S3 CSV File Connector for MS Excel and see how easy it is to use it for yourself or your team.

If you have any questions, feel free to contact ZappySys support team. You can also open a live chat immediately by clicking on the chat icon below.

Download Amazon S3 CSV File Connector for MS Excel Documentation

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