Amazon S3 CSV File Connector for Power BI In this article you will learn how to quickly and efficiently integrate Amazon S3 CSV File data in Power BI 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 Power BI. 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). Let's follow the steps below to see how we can accomplish that! Download Documentation Amazon S3 CSV File Connector for Power BI 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 Power BI 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 Power BI. Perform these steps:

1. Install ZappySys 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.
   Power BI uses a Service Account, when a solution is deployed to production environment, therefore for production environment you have to create and use a System DSN.

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 Amazon S3 CSV File data in Power BI using ODBC

Importing Amazon S3 CSV File data into Power BI from table or view

1. Once you open Power BI Desktop click Get Data to get data from ODBC:
   

2. A window opens, and then search for "odbc" to get data from ODBC data source:
   

3. Another window opens and asks to select a Data Source we already created. Choose AmazonS3CsvFileDSN and continue:

   AmazonS3CsvFileDSN

   

4. 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

   

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

6. Finally, finally, use extracted data from Amazon S3 CSV File in a Power BI report:
   

Importing Amazon S3 CSV File data into Power BI using SQL query

If you wish to import Amazon S3 CSV File data from SQL query rather than a table then you can use advanced options during import steps (as below). After selecting DSN you can click on advanced options to see SQL Query editor.

AmazonS3CsvFileDSN

                SELECT
                    ProductID,
                    ProductName,
                    SupplierID,
                    CategoryID,
                    QuantityPerUnit,
                    UnitPrice
                FROM _root_
                WHERE UnitPrice > 20
			

Using a full ODBC connection string

In the previous steps we used a very short format of ODBC connection string - a DSN. Yet sometimes you don't want a dependency on an ODBC data source (and an extra step). In those times, you can define a full connection string and skip creating an ODBC data source entirely. Let's see below how to accomplish that in the below steps:

1. Open ODBC data source configuration and click Copy settings:
   

   ZappySys Amazon S3 CSV Driver - Amazon S3 CSV File

   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).

   AmazonS3CsvFileDSN

   
2. The window opens, telling us the connection string was successfully copied to the clipboard:
3. Then just paste the connection string into your script:
   AmazonS3CsvFileDSN

   DRIVER={ZappySys Amazon S3 CSV Driver};DataPath='my-bucket/file-*.csv';AccessKey='MY-ACCESS-KEY';SecretKey='MY-SECRET-KEY';ColumnDelimiter=';'

   
4. You are good to go! The script will execute the same way as using a DSN.

Editing query for table in Power BI

There will be a time you need to change the initial query after importing data into Power BI. Don't worry, just right-click on your table and click Edit query menu item:

Using parameters in Power BI (dynamic query)

In the real world, many values of your REST / SOAP API call may be coming from parameters. If that's the case for you can try to edit script manually as below. In below example its calling SQL Query with POST method and passing some parameters. Notice below where paraAPIKey is Power BI Parameter (string type). You can use parameters anywhere in your script just like the normal variable.

To use a parameter in Power BI report, follow these simple steps:

1. Firstly, you need to Edit query of your table (see previous section)

2. Then just create a new parameter by clicking Manage Parameters dropdown, click New Parameter option, and use it in the query:

   						
                               = Odbc.Query("dsn=AmazonS3CsvFileDSN",
                                            "SELECT * FROM _root_ 
                                             WITH (SRC='http://my-api-provider.com/api/" & MyParameter & "/items')")
                           
                   

   
   Refer to Power Query M reference for more information on how to use its advanced features in your queries.

Using DirectQuery Option rather than Import

So far we have seen how to Import Amazon S3 CSV File data into Power BI but what if you have too much data and you don't want to import but link it. Power BI Offers very useful feature for this scenario. It's called DirectQuery Option. In this section we will explore how to use DirectQuery along with ZappySys Drivers.

Out of the box ZappySys Drivers won't work in ODBC Connection Mode so you have to use SQL Server Connection rather than ODBC if you wish to use Live data using DirectQuery option. See below step-by-step instructions to enable DirectQuery mode in Power BI for Amazon S3 CSV File data.

Basically we will use ZappySys Data Gateway its part of ODBC PowerPack. We will then use Linked Server in SQL Server to Link API Service, then issue OPENROWSET queries from Power BI to SQL Server, and it will then call Amazon S3 CSV File via ZappySys Data Gateway.

1. First, create a data source in ZappySys Data Gateway and create a Linked Server based on it.
2. Once SQL Server Linked Server is configured we are ready to issue a SQL query in Power BI.
3. Click Get Data in Power BI, select SQL Server Database
4. Enter your server name and any database name
5. Select Mode as DirectQuery
6. Click on Advanced and enter query like below (we are assuming you have created Amazon S3 CSV File Data Source in Data Gateway and defined linked server (Change name below).

   SELECT * FROM OPENQUERY([LINKED_SERVER_TO_AMAZON_S3_CSV_FILE_IN_DATA_GATEWAY], 'SELECT * FROM Customers')

   SELECT * FROM OPENQUERY([LINKED_SERVER_TO_AMAZON_S3_CSV_FILE_IN_DATA_GATEWAY], 'SELECT * FROM Customers')

   

   
   DirectQuery option for Power BI (Read Amazon S3 CSV File Data Example using SQL Server Linked Server and ZappySys Data Gateway)

7. Click OK and Load data... That's it. Now your Amazon S3 CSV File API data is linked rather than imported.

Publishing Power BI report to Power BI service

Here are the instructions on how to publish a Power BI report to Power BI service from Power BI Desktop application:

1. First of all, go to Power BI Desktop, open a Power BI report, and click Publish button:

   

2. Then select the Workspace you want to publish report to and hit Select button:

   

3. Finally, if everything went right, you will see a window indicating success:

   

   If you need to periodically refresh Power BI semantic model (dataset) to ensure data accuracy and up-to-dateness, you can accomplish that by using Microsoft On-premises data gateway. Proceed to the next section - Refreshing Power BI semantic model (dataset) using On-premises data gateway - and learn how to do that.

Refreshing Power BI semantic model (dataset) using On-premises data gateway

Power BI allows to refresh semantic models which are based on data sources that reside on-premises. This can be achieved using Microsoft On-premises data gateway. There are two types of On-premises gateways:

• Standard Mode
• Personal Mode

Standard Mode supports Power BI and other Microsoft Data Fabric services. It fits perfectly for Enterprise solutions as it installs as a Windows Service and also supports Direct Query feature.

Personal Mode, on the other hand, can be configured faster, but is designed more for home users (you cannot install it as a Windows Service and it does not support DirectQuery). You will find a detailed comparison in the link above.

We recommend to go with Personal Mode for a quick POC solution, but use Standard Mode in production environment.

Below you will find instructions on how to refresh semantic model using both types of gateways.

Refresh using On-premises data gateway (standard mode)

Here are the instructions on how to refresh a Power BI semantic model using On-premises data gateway (standard mode):

1. Go to Power BI My workspace, hover your mouse cursor on your semantic model and click Settings:

   

2. If you see this view, it means you have to install On-premises data gateway (standard mode):

   

3. Install On-premises data gateway (standard mode) and sign-in:

   
   Use the same email address you use when logging in into Power BI account.

4. Register a new gateway (or migrate an existing one):

   

5. If you are creating a new gateway, name your gateway, enter a Recovery key, and click Configure button:

   

6. Now, let's get back to your semantic model settings in Power BI portal. Refresh the page and you should see your newly created gateway. Click arrow icon and then click on Add to gateway link:

   ODBC{"connectionstring":"dsn=AmazonS3CsvFileDSN"}

   

7. Once you do that, you will create a new gateway connection. Give it a name, set Authentication method, Privacy level, and click Create button:

   dsn=AmazonS3CsvFileDSN

   
   In this example, we used the least restrictive Privacy level.

   If your connection uses a full connection string you may hit a length limitation when entering it into the field. To create the connection, you will need to shorten it manually. Check the section about the limitation of a full connection string on how to accomplish it.

   On-premises data gateway (personal mode) does not have this limitation.

8. Proceed by choosing the newly created connection:

   ODBC{"connectionstring":"dsn=AmazonS3CsvFileDSN"}

   

9. Finally, you are at the final step where you can refresh the semantic model:

   

Refresh using On-premises data gateway (personal mode)

Here are the instructions on how to refresh a Power BI semantic model using On-premises data gateway (personal mode):

1. Go to Power BI My workspace, hover your mouse cursor on your semantic model and click Settings:

   

2. If you see this view, it means you have to install On-premises data gateway (personal mode):

   

3. Install On-premises data gateway (personal mode) and sign-in:

   
   Use the same email address you use when logging in into Power BI account.

4. Again, go to your semantic model Settings, expand Data source credentials, click Edit credentials, select Authentication method together with Privacy level, and then click Sign in button:

   dsn=AmazonS3CsvFileDSN

   

5. Finally, you are ready to refresh your semantic model:

   

Advanced topics

Create Custom Stored Procedure in ZappySys Driver

You can create procedures to encapsulate custom logic and then only pass handful parameters rather than long SQL to execute your API call.

Steps to create Custom Stored Procedure in ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here

1. Go to Custom Objects Tab and Click on Add button and Select Add Procedure:
   

2. Enter the desired Procedure name and click on OK:
   

3. Select the created Stored Procedure and write the your desired stored procedure and Save it and it will create the custom stored procedure in the ZappySys Driver:
   Here is an example stored procedure for ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here
   

   CREATE PROCEDURE [usp_get_orders]
       @fromdate = '<<yyyy-MM-dd,FUN_TODAY>>'
    AS
       SELECT * FROM Orders where OrderDate >= '<@fromdate>';
   

   
   

4. That's it now go to Preview Tab and Execute your Stored Procedure using Exec Command. In this example it will extract the orders from the date 1996-01-01:
   

   Exec usp_get_orders '1996-01-01';

   
   

5. Let's generate the SQL Server Query Code to make the API call using stored procedure. Go to Code Generator Tab, select language as SQL Server and click on Generate button the generate the code.
   As we already created the linked server for this Data Source, in that you just need to copy the Select Query and need to use the linked server name which we have apply on the place of [MY_API_SERVICE] placeholder.
   

   SELECT * FROM OPENQUERY([LINKED_SERVER_TO_AMAZON_S3_CSV_FILE_IN_DATA_GATEWAY], 'EXEC usp_get_orders @fromdate=''1996-07-30''')

   
   

6. Now go to SQL served and execute that query and it will make the API call using stored procedure and provide you the response.
   

Create Custom Virtual Table in ZappySys Driver

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.

If you're dealing with Microsoft Access and need to import data from an SQL query, it's important to note that Access doesn't allow direct import of SQL queries. Instead, you can create custom objects (Virtual Tables) to handle the import process.

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 URLs with slight variations you can create virtual tables with just URL as Parameter setting.

1. Go to Custom Objects Tab and Click on Add button and Select Add Table:
   

2. Enter the desired Table name and click on OK:
   

3. And it will open the New Query Window Click on Cancel to close that window and go to Custom Objects Tab.

4. Select the created table, Select Text Type AS SQL and write the your desired SQL Query and Save it and it will create the custom table in the ZappySys Driver:
   Here is an example SQL query for ZappySys Driver. You can insert Placeholders also. Read more about placeholders here
   

   SELECT
     "ShipCountry",
     "OrderID",
     "CustomerID",
     "EmployeeID",
     "OrderDate",
     "RequiredDate",
     "ShippedDate",
     "ShipVia",
     "Freight",
     "ShipName",
     "ShipAddress",
     "ShipCity",
     "ShipRegion",
     "ShipPostalCode"
   FROM "Orders"
   Where "ShipCountry"='USA'

   
   

5. That's it now go to Preview Tab and Execute your custom virtual table query. In this example it will extract the orders for the USA Shipping Country only:
   

   SELECT * FROM "vt__usa_orders_only"

   
   

6. Let's generate the SQL Server Query Code to make the API call using stored procedure. Go to Code Generator Tab, select language as SQL Server and click on Generate button the generate the code.
   As we already created the linked server for this Data Source, in that you just need to copy the Select Query and need to use the linked server name which we have apply on the place of [MY_API_SERVICE] placeholder.
   

   SELECT * FROM OPENQUERY([LINKED_SERVER_TO_AMAZON_S3_CSV_FILE_IN_DATA_GATEWAY], 'EXEC [usp_get_orders] ''1996-01-01''')

   
   

7. Now go to SQL served and execute that query and it will make the API call using stored procedure and provide you the response.
   

Conclusion

In this article we showed you how to connect to Amazon S3 CSV File in Power BI and integrate data without any coding, saving you time and effort. We encourage you to download Amazon S3 CSV File Connector for Power BI 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 Power BI Documentation

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