Amazon S3 CSV File Connector for Power BI In this article you will learn how to integrate Amazon S3 CSV File data in Power BI without coding in just a few clicks (live / bi-directional connection to 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).. Using Amazon S3 CSV File Connector you will be able to connect, read, and write data from within Power BI. Follow the steps below to see how we would accomplish that. Download Documentation The driver mentioned above is part of ODBC PowerPack which is a collection of high-performance Drivers for various API data source (i.e. REST API, JSON, XML, CSV, Amazon S3 and many more). Using familiar SQL query language you can make live connections and read/write data from API sources or JSON / XML / CSV Files inside SQL Server (T-SQL) or your favorite Reporting (i.e. Power BI, Tableau, Qlik, SSRS, MicroStrategy, Excel, MS Access), ETL Tools (i.e. Informatica, Talend, Pentaho, SSIS). You can also call our drivers from programming languages such as JAVA, C#, Python, PowerShell etc. If you are new to ODBC and ZappySys ODBC PowerPack then check the following links to get started. ODBC PowerPack - System Requirements and Installation Getting Started - Using ODBC PowerPack ODBC API Driver Help File

Connect to Amazon S3 CSV File in other apps Connect to Amazon S3 CSV File in SSIS Connect to Amazon S3 CSV File in SQL Server Connect to Amazon S3 CSV File in SSRS Connect to Amazon S3 CSV File in Informatica Connect to Amazon S3 CSV File in MS Access Connect to Amazon S3 CSV File in MS Excel Connect to Amazon S3 CSV File in SSAS Connect to Amazon S3 CSV File in C# Connect to Amazon S3 CSV File in Python Connect to Amazon S3 CSV File in JAVA Connect to Amazon S3 CSV File in Tableau Connect to Amazon S3 CSV File in SAP Crystal Reports Connect to Amazon S3 CSV File in Azure Data Factory (Pipeline) Connect to Amazon S3 CSV File in Azure Data Factory (SSIS) Connect to Amazon S3 CSV File in Talend Studio Connect to Amazon S3 CSV File in UiPath Connect to Amazon S3 CSV File in PowerShell Connect to Amazon S3 CSV File in ODBC

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

   
   You should create a System DSN (instead of a User DSN) if the client application is launched under a Windows System Account, e.g. as a Windows Service. If the client application is 32-bit (x86) running with a System DSN, use ODBC Data Sources (32-bit) instead of the 64-bit version.

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

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:
   

Import Amazon S3 CSV File data into Power BI from SQL Query

If you wish to import Amazon S3 CSV File data from SQL query rather than selecting table name 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.

Import Amazon S3 CSV File data into Power BI using SQL Query (ODBC Data source)

Edit Query / Using Parameters in Power BI (Dynamic Query)

let
    vKey=paraAPIKey,
    Source = Odbc.Query(
    "dsn=ZS-OData Customers", 
    "SELECT * FROM value WITH (SRC='http://httpbin.org/post'," 
    & "METHOD='POST'," 
    & "HEADER='Content-Type:application/json'," 
    & "BODY=@'{""CallerId"":1111, ""ApiKey"":""" & vKey & """}')")
in
Source

Edit Query Settings after Import

There will be a time you need to change initial Query after dataset import in Power BI. Not to worry, just follow these steps to edit your SQL.

Edit Power BI Data Source SQL after REST / SOAP Web Service Import

Working with Gateways in Power BI (Schedule Import)

1. In the last section, we Published the report. Power BI may ask you to SIGN IN.
   

   Sign in Power BI

2. Select the Workspace and select Datasets
   

   Go to workspace and dataset

3. Right-click the report and select Settings.
   

   Specify settings for the report

4. The system will ask for a Gateway. Stay here.
   

   Add Power BI Gateway

5. Use the following link to install a Data Gateway:

   https://docs.microsoft.com/en-us/power-bi/service-gateway-onprem

6. Run the installer and press Next
   

   Gateway installer

7. Select the option On-premises data gateway (recommended). This option allows access to multiple users and can be used by more applications than Power BI.
   

   Choose Power BI option

8. The installer will show a warning message.
   

   Warning message during installation

9. Select the path to install and check the I accept the terms.
   

   Accept terms

10. Specify the email address to use the gateway.
    

    Register email address

11. After entering the email, write the gateway name and a recovery key. Make sure to confirm the recovery key.
    

    Enter recovery key

Manage gateways and configure the schedule

1. The next step is to go to manage gateway
   

   Power BI - Manage Gateway Setting

2. In order to get the connection string, we will need the connection string of the ZappySys Amazon S3 CSV Driver. In the first section of this post, we explained how to configure it. Press Copy Connection String
   

   Connection properties

3. Once that the data is copied, add a New data Source. In Data Source Name, enter the Data Source Name of the ZappySys Amazon S3 CSV Driver in step 13 and in Data Source Type, select ODBC. In connection string copy and paste from the clipboard of the step 13 and press Add.
   

   ZappySys connection properties in Power BI

4. Once added the gateway. You can see the schedule refresh to On and Add another time to add the time where you want to refresh the data.
   

   Schedule gateway

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([MY_API_SERVICE], '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([MY_API_SERVICE], '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 discussed how to connect to Amazon S3 CSV File in Power BI and integrate data without any coding. Click here to Download Amazon S3 CSV File Connector for Power BI and try yourself see how easy it is. If you still have any question(s) then ask here or simply click on live chat icon below and ask our expert (see bottom-right corner of this page).

Download Amazon S3 CSV File Connector for Power BI Documentation 

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