In our previous blog post we saw how to import rest API in SQL Server. Using same concepts lets look at how to import Amazon MWS Data into SQL Server. We will explore many techniques to call Amazon MWS API and learn how to automate Amazon MWS data extraction without doing any ETL. We will call MWS XML or CSV API just using T-SQL code. We will also learn how to Download Reports from by calling MWS API.

You can also refer other articles here (Power BI) and here (SSIS)

About Amazon MWS  API

If you want to sell something on Amazon you can use their e-commerce platform with some monthly fee. You can setup your entire online store / inventory using admin interface.

Amazon Marketplace Web Service (Amazon MWS) is an integrated web service API that helps Amazon sellers to programmatically exchange data on listings, orders, payments, reports, and more. Using these API you can read or write data from your Seller account and integrate it inside your own Systems (e.g. Reporting / ETL / BI tools).

Obtain MWS API Access Key / Secret and Seller ID

Very first thing to call any MWS API is to obtain Access Key, Secret Key and Seller ID (i.e. Merchant ID). To obtain this you first have to register a developer.

Here is where to look for your Merchant ID and Key / Secret.  Here is direct link to User Permissions page.

How to get Amazon MWS developer keys and know your Merchant ID (i.e. Seller ID)

Getting Started

Now let’s look at step by step instructions on how to call Amazon MWS API and then import into Power BI. In below steps we will use  ZappySys ODBC PowerPack so make sure it’s installed first.

Using ScratchPad to Test Amazon MWS API

Each MWS API has set of required and optional parameters. You can refer each API page for details. For example ListMatchingProducts API which we will use as an example. To make MWS API testing / learning easy, Amazon provides online testing tool called MWS ScratchPad. We will use this tool to craft API requests and use that information in ODBC driver SQL queries and later import data in Power BI.

1. Open MWS ScratchPad  by vising https://mws.amazonservices.com/scratchpad/index.html
2. Select Products API category and pick ListMatchingProducts API
3. Enter your SellerID (i.e. Merchant ID), Developer AccessKey (i.e. AWSAccessKeyId) and Secret Key we obtained in the previous section. Enter MarketId (e.g. ATVPDKIKX0DER for USA Market) and other parameters as below and Click Submit to see response.
   

   Using Amazon MWS ScratchPad (API Testing Tool – Created by Amazon)

4. Click on the Response Details Tab to extract some important information we will use for ODBC configuration. Notice attributes in red rectangles. They are the ones which we will need in the POST request Body. ZappySys Drivers supply many common parameters automatically but any API endpoint specific parameter must be supplied in the Request Body. For example you dont have to supply SignatureVersion, Timestamp, Signature or SignatureMethod
   

   Calling Amazon MWS API in Scratchpad Testing Tool (Response Details Tab) – ListMatchingProducts Example

This API requires Market ID parameter so enter it as per your Market where you selling. For example USA marketplaceid = ATVPDKIKX0DER. You can lookup correct MarketplaceId by checking this help (endpoints / marketplaces).

Setup Amazon MWS API Connections

Create XML Driver Connection for Amazon MWS API (e.g. RequestReport )

Some APIs we need to call in this article is XML format and some API (e.g. GetReport) is CSV format – Tab delimited so we need to create 2 different connections using CSV driver and XML driver. So lets get started with Amazon MWS Connection for XML API.

1. Click on Add New Data source. Name as AMAZON-MWS-XML and select Native – ZappySys XML Driver option.
   

   Add Gateway Data Source

2. Now click Edit to Configure Settings. For now we will only care OAuth Connection settings. All other options are overwritten in SQL Query.
   

   Edit Gateway Data Source Settings

3. When UI opens for Driver Enter MWS API Service URL as below. Notice that we added /Products/2011-10-01 (This was extracted from previous section). You can check full list of Amazon MWS Endpoints here. Because we are connecting to USA region we will use below URL.
   

   https://mws.amazonservices.com/Products/2011-10-01

4. Select OAuth from the Connection dropdown and Click Configure Settings
5. On the Connection UI, Select OAuth Provider Amazon Market Web Service (MWS)
6. Enter your API Access Key and Secret Key (obtained from here)
7. Your connection will look like below.
   

   ODBC Connection Credentials for Amazon MWS API (Access Key, Secret Key, URL Endpoint)

8. Also configure Retry options to handle API limit reached error when you call API too often. For Amazon MWS we get Status code 503 when request is throttled so lets narrow down on which error we want to retry.
   

   Retry Options

9. Click OK to save OAuth Connection UI to go back to main UI
10. Now Go to Throttling Tab and enter some delay (e.g. enter 20000 for 20sec delay after each request). This will slow down API calls so we don’t face errors about API Limit reached.
11. Click OK to Save UI
12. Click Save button on Gateway UI to save and restart

Create CSV Driver Connection for Amazon MWS API (e.g. GetReport )

Now lets create a connection CSV API (e.g. GetReport ).

Follow almost same steps as previous section except use CSV Driver when you click on Add new Data source select Native – ZappySys CSV Driver and name data source as AMAZON-MWS-CSV . As we mentioned for now we mostly want to setup Connection and not worry about Request Body, Pagination etc.

Create Linked Server for SQL Server

Run following Script in SSMS to create Linked servers. Change ######## with Your gateway password. Change localhost with machine name or IP where ZappySys Gateway Is running. Use localhost if SQL Server and Gateway both on the same machine.

USE [master]
GO

EXEC master.dbo.sp_addlinkedserver @server = N'AMAZON-MWS-XML', @srvproduct=N'', @provider=N'SQLNCLI', @datasrc=N'localhost,5000', @catalog=N'AMAZON-MWS-XML'
EXEC master.dbo.sp_addlinkedsrvlogin @rmtsrvname=N'AMAZON-MWS-XML',@useself=N'False',@locallogin=NULL,@rmtuser=N'tdsuser',@rmtpassword='########'
GO

EXEC master.dbo.sp_addlinkedserver @server = N'AMAZON-MWS-CSV', @srvproduct=N'', @provider=N'SQLNCLI', @datasrc=N'localhost,5000', @catalog=N'AMAZON-MWS-CSV'
EXEC master.dbo.sp_addlinkedsrvlogin @rmtsrvname=N'AMAZON-MWS-CSV',@useself=N'False',@locallogin=NULL,@rmtuser=N'tdsuser',@rmtpassword='########'
GO

If you want to know how to configure Linked Server using UI then check this article.

Amazon MWS ListOrders Example

Now lets look at how to call ListOrders request with pagination in SQL Server. Create a following Stored Procedure to List MWS Orders. If you want to extract many orders then call Report rather than this proc (See next section for generating reports)

USE MyDatabase
GO
/*
Example: 
 exec usp_MWS_ListOrders @SellerId='Axxxxxxx', @MarketplaceId ='Bxxxxxxx',@CreatedAfter='2019-01-01'  
*/
Create proc [dbo].[usp_MWS_ListOrders]
	@SellerId varchar(100),
	@MarketplaceId varchar(100),
	@CreatedAfter varchar(100),
	@CreatedBefore varchar(100)=null,
	@MaxRows int=0
as
declare @sql varchar(max) 
declare @limitClase varchar(100)=''
if(@MaxRows>0)
	set @limitClase	=' LIMIT ' + cast(@MaxRows as varchar(20))

--//Confirm ISO Date format 2019-06-01T04%3A00%3A00Z  rather 2019-06-01T04:00:00Z
if(isnull(@CreatedAfter,'')<>'')
begin
	set @CreatedAfter='&CreatedAfter=' + @CreatedAfter
	set @CreatedAfter=replace(@CreatedAfter,':','%3A')
	if(@CreatedAfter NOT LIKE @CreatedAfter + 'T%')
		set @CreatedAfter=@CreatedAfter + 'T00%3A00%3A00Z'
	if(@CreatedAfter NOT LIKE @CreatedAfter + '%Z')
		set @CreatedAfter=@CreatedAfter + 'Z'
	--//T04%3A00%3A00Z
end
if(isnull(@CreatedBefore,'')<>'')
begin
	set @CreatedBefore='&CreatedBefore=' + @CreatedBefore
	set @CreatedBefore=replace(@CreatedBefore,':','%3A')
	if(@CreatedBefore NOT LIKE @CreatedBefore + 'T%')
		set @CreatedBefore=@CreatedBefore + 'T00%3A00%3A00Z'
	if(@CreatedBefore NOT LIKE @CreatedBefore + '%Z')
		set @CreatedBefore=@CreatedBefore + 'Z'
end

set @CreatedAfter = isnull(@CreatedAfter,'')
set @CreatedBefore = isnull(@CreatedBefore,'')


set @sql = 'SELECT * FROM OPENQUERY([AMAZON-MWS-XML]
, ''
SELECT ReportRequestId FROM $
' + @limitClase +' 
WITH(
     Src=''''https://mws.amazonservices.com/Orders/2013-09-01''''
	,Filter=''''$.RequestReportResponse.RequestReportResult.ReportRequestInfo''''
	,ElementsToTreatAsArray=''''Order''''
	,RequestData=''''Action=ListOrders[$tag$]' + @CreatedAfter + @CreatedBefore + '&MarketplaceId.Id.1='+ @MarketplaceId +'&SellerId='+ @SellerId +'''''
	,RequestMethod=''''POST''''
	,NextUrlAttributeOrExpr=''''$.ListOrders[$tag$]Response.ListOrders[$tag$]Result.NextToken''''
	,NextUrlSuffix=''''&NextToken=<%nextlink_encoded%>''''
	,WaitTimeMs=20000 -- slow down to avoid throttling. 6 requests per min
	,HasDifferentNextPageInfo=''''True''''
	,EnablePageTokenForBody=''''True''''
	,PagePlaceholders=''''body=|ByNextToken;filter=|ByNextToken''''
	--,DataConnectionType=''''OAuth''''
	--,ScopeSeparator=''''{space}''''
	--,ServiceProvider=''''AmazonMWS''''
	--,ClientId=''''AKIxxxxxx''''
	--,ClientSecret=''''AKIxxxxxx''''
	--,UseCustomApp=''''True''''
	,CacheFileLocation=''''c:\temp\mws-orders.cache''''
	,CacheEntryTtl=300 --send every 5 mins else use from cache
	,IncludeParentColumns=''''False''''
)
'')'
print @sql

EXECUTE( @sql)

Here is how to call this proc. Change SellerId, MarketplaceId and Date.

exec usp_MWS_ListOrders @SellerId='Axxxxxxx', @MarketplaceId ='Bxxxxxxx',@CreatedAfter='2019-01-01'

Download Amazon MWS Report data in SQL Server (CSV / XML Format)

Now lets look at how to extract data from Custom Report API (You must need ODBC PowerPack v1.1.1 or higher). However reading data from Reports not single step process because report generation is Job style API. Which means you send report request and wait  until its done. Once Report ready you have to read in CSV format or XML. Some Reports only available in CSV format. Check this post to understand how complex it can be to get data. We will make it simple for you to understand this in 3 steps. Basically calling reports requires minimum 3 API calls (see below)

1. Create a new report request – Cal RequestReport API . It returns ReportRequestId (You can use it in the next step)
2. Check Report Status see its done – Call GetReportRequestList API (Pass ReportRequestId got in the previous step to get data for only one Report request we care). Keep checking Report Status every few seconds until you get _DONE_  or _DONE_NO_DATA_ status in response.
3. Read Report Data – Call GetReport. This API call returns CSV or XML data. So use correct Driver for this step. If CSV data is returned then we must use CSV Driver rather than XML Driver.

Method 1 – Single query approach (New Driver)

In new driver ZappySys added few new features which makes it possible to call above 3 steps process in a single query. New query syntax offers StatusCheck and Mixing Content Formats using same driver. Because Most MWS Reports are in CSV Format we have to use CSV Driver but oddly first 2 steps listed in above sections are in XML Format so we have to use XML driver. Technically we need atleast 2 steps (i.e 2 queries) but we will show you how to achieve using single query as below.

1. Assuming you have followed steps to create a linked server AMAZON-MWS-CSV (see previous section)
2. Run below query. Replace necessary parameters as per your need. (i.e MarketplaceId , SellerId, CreatedAfter date)
   

   --- //////////////////////////////////////////////////////////////////////////
   -- Change _GET_MERCHANT_LISTINGS_DATA_ to something else if you need different report type (all 3 steps) -- https://docs.developer.amazonservices.com/en_US/reports/Reports_ReportType.html
   -- Replace MarketplaceId in all 3 steps (i.e for USA use ATVPDKIKX0DER) --https://docs.developer.amazonservices.com/en_US/dev_guide/DG_Endpoints.html
   -- Replace SellerId in all 3 steps
   -- Remove or Change CreatedAfter in first step (or use CreatedBefore parameter instread of CreatedAfter)
   --- //////////////////////////////////////////////////////////////////////////
   select * into tmpMWS_Report from OPENQUERY([AMAZON-MWS-CSV],
   '
   SELECT s3.* FROM $
   WITH(
   Src=''https://mws.amazonservices.com/Reports/2009-01-01'',RequestMethod=''POST''
   ,RequestData=''Action=RequestReport&ReportType=_GET_MERCHANT_LISTINGS_DATA_&MarketplaceId=ATVPDKIKX0DER&SellerId=Axxxxxxxxxx&CreatedAfter=2017-12-31T04%3A00%3A00Z''
   ,IncludeParentColumns=''False''
   ,EnableRawOutputModeSingleRow=''True''
   ,RawOutputFilterExpr=''//*[local-name()="ReportRequestId"]'' 
   ,RawOutputDataRowTemplate=''{ReportRequestId:"[$1]"}'' 
   ,RawOutputExtractMode=''Xml'' 
   ,WaitTimeMs=5000
   ,Meta=''[{"Name": "ReportRequestId","Type": "Int64"}]''
   ,Alias=''s1''
   
   ,Join1_alias=''s2''	
   ,Join1_Src=''https://mws.amazonservices.com/Reports/2009-01-01'',Join1_RequestMethod=''POST''
   ,Join1_RequestData=''Action=GetReportRequestList&ReportRequestIdList.Id.1=[$s1.ReportRequestId$]&MarketplaceId=ATVPDKIKX0DER&SellerId=Axxxxxxxxxxxxx''
   ,Join1_EnableRawOutputModeSingleRow=''True''
   ,Join1_RawOutputFilterExpr=''//*[local-name()="ReportProcessingStatus"]||//*[local-name()="GeneratedReportId"]'' 
   ,Join1_RawOutputDataRowTemplate=''{ReportProcessingStatus:"[$1]",GeneratedReportId:"[$2]"}'' 
   ,Join1_RawOutputExtractMode=''Xml'' 
   ,Join1_EnableStatusCheck=''True'', 
   ,Join1_StatucCheckMaxWaitSeconds=300,
   ,Join1_StatucCheckIterationWaitSeconds=25,
   ,Join1_StatusSuccessValue=''_DONE_''
   ,Join1_StatusFailedValue=''_DONE_NO_DATA_|_CANCELLED_''
   
   ,Join2_Alias=''s3''
   ,Join2_Src=''https://mws.amazonservices.com/Reports/2009-01-01'',Join2_RequestMethod=''POST''
   ,Join2_RequestData=''Action=GetReport&ReportId=[$s2.GeneratedReportId$]&MarketplaceId=ATVPDKIKX0DER&SellerId=Axxxxxxxxxxxxxx''	
   ,Join2_ColumnDelimiter=''{TAB}''
   ,Join2_ResponseCharset=''Windows-1252''	 
   ,Join2_EnableStatusCheck=''False'' 
   ,Join2_EnableRawOutputModeSingleRow=''False''
   ,Join2_WaitTimeMs=10000
   )') 
   go
   select * from tmpMWS_Report

    

Performance Tip

If you like to improve performance and dont want to use SELECT INTO approach to load into temp table as above then you can use EXEC (….) AT YourLinkedServerName  as below.

Advantage of this method is your Query speed will increase because system calls API only once when you call EXEC AT. In OPENROWSET it needs to call above query twice (Once to obtain metadata and once to get data).

INSERT INTO tmpMWS_Report
EXEC('select s3.* .................. ') AT [AMAZON-MWS-CSV]

Method 2 – Multiple query approach (For old driver)

Now lets see how to load Amazon MWS data in SQL Server using old driver (v1.1.2 or older) which didnt support single query approach like previous section. If you are using older driver or for some reason you like to split steps into multiple procedures then use below approach.

usp_MWS_Report  Stored Proc ( Generate ReportRequest, Wait until done, Read data )

USE MyDatabase
GO

/*
Examples: 
Get ReportType from here https://docs.developer.amazonservices.com/en_UK/reports/Reports_ReportType.html

exec usp_MWS_Report @MarketplaceId ='ATVPDKIKX0DER', @SellerId='AZxxxxxxxx', @ReportType = '_GET_MERCHANT_LISTINGS_DATA_'
exec usp_MWS_Report @MarketplaceId ='ATVPDKIKX0DER', @SellerId='AZxxxxxxxx', @ReportType = '_GET_FLAT_FILE_ORDER_REPORT_DATA_'

--Do not Throw Error if no data found (return empty resultset or run custom sql)
exec usp_MWS_Report @MarketplaceId ='ATVPDKIKX0DER', @SellerId='AZxxxxxxxx', @ReportType = '_GET_FLAT_FILE_ORDER_REPORT_DATA_',@ThrowErrIfNoData=0,@EmptyRowSql='select top 0 * from Orders'
--Supply date range
exec usp_MWS_Report @MarketplaceId ='ATVPDKIKX0DER', @SellerId='AZxxxxxxxx', @ReportType = '_GET_MERCHANT_LISTINGS_DATA_', @StartDate='2019-01-01T00:00:00Z', @EndDate='2019-01-31T00:00:00Z'

--loading into table 

--//////////////////////////////////
— Step-1 : Create Local Linked server to point to self
--//////////////////////////////////
USE [master]
GO
--change default catalog
--For MSSQL 2012, 2014, 2016, 2017, and 2019 use @provider=N'MSOLEDBSQL' below (SQL Server Native Client 11.0)---
EXEC master.dbo.sp_addlinkedserver @server = N'ME', @srvproduct=N'', @provider=N'SQLNCLI11', @datasrc=N'localhost', @catalog=N'Northwind'
--For MSSQL 2022 or higher use @provider=N'MSOLEDBSQL' below (Microsoft OLE DB Driver for SQL Server)---
--EXEC master.dbo.sp_addlinkedserver @server = N'ME', @srvproduct=N'', @provider=N'MSOLEDBSQL', @datasrc=N'localhost', @catalog=N'Northwind'

EXEC master.dbo.sp_addlinkedsrvlogin @rmtsrvname=N'ME',@useself=N'True',@locallogin=NULL,@rmtuser=NULL,@rmtpassword=NULL
GO
--//////////////////////////////////
— Step-2 : Enable RPC OUT and Disable MSDTC
--//////////////////////////////////
EXEC sp_serveroption 'ME', 'rpc out', true;  
GO
--Below needed to support EXEC + INSERT (dynamic query)
EXEC sp_serveroption 'ME', 'remote proc transaction promotion', false;
GO
--test simple query
select * from OPENQUERY(ME,'select 1')
GO

--//////////////////////////////////
— Step-3 : Load data into table from MWS Report
--//////////////////////////////////
SELECT * INTO #amazon_mws_report
FROM OPENQUERY(me,'
SET NOCOUNT ON;
EXEC usp_MWS_Report 
   @Columns=''[item-name], [item-description], [listing-id]'',
   @MarketplaceId =''ATVPDKIKX0DER'', 
   @SellerId=''Axxxxxxxxxxxxxxxxx'', 
   @ReportType = ''_GET_MERCHANT_LISTINGS_DATA_''
WITH RESULT SETS 
(
	(itmname varchar(1000),itmdesc varchar(1000),itmid varchar(1000))
)
')

select * from #amazon_mws_report


*/
CREATE proc [dbo].[usp_MWS_Report]
	@MarketplaceId varchar(100),
	@SellerId varchar(100),
	@ReportType varchar(100)='_GET_MERCHANT_LISTINGS_DATA_',
	@StartDate varchar(100)=null,
	@EndDate varchar(100)=null,
	@ReportId bigint=null,  ---i.e. 14783134522018025
	@ThrowErrIfNoData bit=1,
	@EmptyRowSql varchar(1000)=null, --SQL to run if no data found
	@Columns varchar(8000)='*'  --report columns which goes in final SELECT  e.g. [item-name], [item-description], [listing-id] ....
as


declare @retGeneratedReportId bigint
set @retGeneratedReportId=@ReportId
---////// STEP 1 /////////
if(@ReportId is null)
begin
	create table #step1(ReportRequestId bigint)
	insert into #step1
	exec usp_MWS_RequestReport @ReportType,@MarketplaceId,@SellerId,@StartDate,@EndDate

	--select * from #step1 --debug

	declare @retReportRequestId bigint
	select @retReportRequestId=ReportRequestId from #step1

	---////// STEP 2 /////////
	declare @status varchar(100)
	declare @cnt int
	create table #step2(ReportProcessingStatus varchar(100),GeneratedReportId bigint)
	
	--Keep looping until status is done or we waited too long
	while(isnull(@status,'') IN ('','_SUBMITTED_','_IN_PROGRESS_') )
	begin
		truncate table #step2
		insert into #step2
		exec usp_MWS_GetReportIdAndStatus @retReportRequestId,@MarketplaceId,@SellerId 
	
		select @status=ReportProcessingStatus, @retGeneratedReportId=GeneratedReportId from #step2
		if(isnull(@status,'') IN ('','_SUBMITTED_','_IN_PROGRESS_') )			
		begin
			--amazon says dont check often https://docs.developer.amazonservices.com/en_UK/reports/Reports_GetReportRequestList.html
			Print 'Status='+  isnull(@status,'') +'. Checking after 45 sec... #' + cast(@cnt as varchar(10))
			WAITFOR DELAY '00:00:45'			
		end
		else
			print @status

		set @cnt=@cnt+1

		--if(@cnt>50)
			--//throw err?
	end
	--select * from #step2 --debug
end

if(@retGeneratedReportId is null and @status='_DONE_NO_DATA_')
begin
	if(@ThrowErrIfNoData=1)
		RAISERROR('Cannot generate report - No data found for specified criteria',16,1); 
	else if (isnull(@EmptyRowSql,'')<>'')
		execute(@EmptyRowSql)
end
else if(@retGeneratedReportId is null)
	RAISERROR('Cannot generate report - Unknown error (either report got cancelled or other error occurred)',16,1); 

	
---////// STEP 3 /////////
--If xml format of report data then use XML driver else CSV (most are Tab delimited reports in CSV format)
--exec usp_MWS_GetReportDataXml @retGeneratedReportId,@MarketplaceId,@SellerId
exec usp_MWS_GetReportDataCsv @retGeneratedReportId,@MarketplaceId,@SellerId,@Columns

drop table #step1
drop table #step2

GO

usp_MWS_RequestReport  Stored Proc ( Step1 – Create Report Request )

USE [MyDatabase]
GO

CREATE proc [dbo].[usp_MWS_RequestReport]
	@ReportType varchar(100),
	@MarketplaceId varchar(100),
	@SellerId varchar(100),
	@StartDate varchar(100)=null,
	@EndDate varchar(100)=null
as

/*Learn more : https://docs.developer.amazonservices.com/en_UK/reports/Reports_RequestReport.html */

--//Confirm ISO Date format 2019-06-01T04%3A00%3A00Z  rather 2019-06-01T04:00:00Z
if(isnull(@StartDate,'')<>'')
begin
	set @StartDate='&StartDate=' + @StartDate
	set @StartDate=replace(@StartDate,':','%3A')
	if(@StartDate NOT LIKE @StartDate + 'T%')
		set @StartDate=@StartDate + 'T00%3A00%3A00Z'
	if(@StartDate NOT LIKE @StartDate + '%Z')
		set @StartDate=@StartDate + 'Z'
	--//T04%3A00%3A00Z
end
if(isnull(@EndDate,'')<>'')
begin
	set @EndDate='&EndDate=' + @EndDate
	set @EndDate=replace(@EndDate,':','%3A')
	if(@EndDate NOT LIKE @EndDate + 'T%')
		set @EndDate=@EndDate + 'T00%3A00%3A00Z'
	if(@EndDate NOT LIKE @EndDate + '%Z')
		set @EndDate=@EndDate + 'Z'
end

set @StartDate = isnull(@StartDate,'')
set @EndDate = isnull(@EndDate,'')

declare @sql varchar(max) 
set @sql = 'SELECT * FROM OPENQUERY([AMAZON-MWS-XML]
, ''
SELECT ReportRequestId FROM $
WITH(
	Src=''''https://mws.amazonservices.com/Reports/2009-01-01'''',RequestMethod=''''POST''''
	--,ElementsToTreatAsArray=''''Product''''
	,Filter=''''$.RequestReportResponse.RequestReportResult.ReportRequestInfo''''
	,RequestData=''''Action=RequestReport&ReportType=' + @ReportType  + '&MarketplaceId='+ @MarketplaceId +'&SellerId='+ @SellerId + @StartDate + @EndDate +'''''
	,CacheFileLocation=''''c:\temp\mws-cache-step-1.cache''''
	,CacheEntryTtl=300 --send every 5 mins else use from cache
	,WaitTimeMs=''''300''''
	,IncludeParentColumns=''''False''''
	,Meta=''''[{"Name": "ReportRequestId","Type": "Int64"}]''''
)'')'
--print @sql

EXECUTE( @sql)
--sleep 25 seconds after this - hope report is ready by that time else We have to loop
WAITFOR DELAY '00:00:25'  --lets wait 30 sec... incase we get luck and report is done?
GO

usp_MWS_GetReportIdAndStatus Stored Proc ( Step2 – Get Report Id and Report Status )

USE MyDatabase
GO


CREATE proc [dbo].[usp_MWS_GetReportIdAndStatus]
	@ReportRequestId bigint,
	@MarketplaceId varchar(100),
	@SellerId varchar(100)
as

declare @sql varchar(max) 
set @sql = 'SELECT * FROM OPENQUERY([AMAZON-MWS-XML]
, ''SELECT *  FROM $
WITH(
	 Src=''''https://mws.amazonservices.com/Reports/2009-01-01'''',RequestMethod=''''POST''''
	,ElementsToTreatAsArray=''''ReportRequestInfo''''
	,Filter=''''$.GetReportRequestListResponse.GetReportRequestListResult.ReportRequestInfo''''
	,RequestData=''''Action=GetReportRequestList&ReportRequestIdList.Id.1=' + cast(@ReportRequestId as varchar(20)) + '&MarketplaceId='+ @MarketplaceId +'&SellerId='+ @SellerId +'''''
	,WaitTimeMs=''''300''''
	,IncludeParentColumns=''''False''''
	--,CacheFileLocation=''''c:\temp\mws-cache-step-2.cache''''
	--,CacheEntryTtl=10  --do not use from cache too old.. but cache still prevents too many requests
	,Meta=''''[{"Name": "ReportProcessingStatus","Type": "String", Length: 100},{"Name": "GeneratedReportId","Type": "Int64"}]''''	
)'')'

--print @sql

EXECUTE( @sql)

GO

usp_MWS_GetReportDataCsv Stored Proc (Step3 – Get Report Data in CSV format )

Last step in report generation is download the report data in CSV format.

USE MyDatabase
GO

CREATE proc [dbo].[usp_MWS_GetReportDataCsv]
	@ReportId bigint,
	@MarketplaceId varchar(100),
	@SellerId varchar(100),
	@Columns varchar(8000)='*'

as

declare @sql varchar(max) 
set @sql = 'SELECT '+ @Columns +' FROM OPENQUERY([AMAZON-MWS-CSV], 
''SELECT * FROM $
WITH(
    Src=''''https://mws.amazonservices.com/Reports/2009-01-01'''',RequestMethod=''''POST''''
	,RequestData=''''Action=GetReport&ReportId=' + cast(@ReportId as varchar(20)) + '&MarketplaceId='+ @MarketplaceId +'&SellerId='+ @SellerId +'''''
	,WaitTimeMs=''''300''''
	,ColumnDelimiter=''''{TAB}''''
	,ResponseCharset=''''Windows-1252''''	
	,CacheFileLocation=''''c:\temp\mws-cache-step-3.cache''''
	,CacheEntryTtl=300 --once report is generated lets try to read from cache 
	)''
)'

print @sql

EXECUTE( @sql)
GO

Example – Import data from Amazon MWS into SQL Server Table

Finally when we have all stored procs created we can load into target table as below. In our previous article we saw how to use SELECT INTO along with OPENQUERY to load data into new temp table or insert into some existing table. However when you want to load Stored Proc output into table its not straight forward specially when we calling dynamic SQL.

Three tricks worth mentioning here which makes it possible to load data from stored proc into temp table dynamically.

1. Create a linked server to Self so we can use OPENQUERY against to call stored proc so its easy to use SELECT INTO.
2. Use WITH RESULT SETS to describe metadata of output. This is needed because we are using dynamic SQL inside proc and WITH RESULT SETS describes the metadata.
3. Use of SET NO COUNT ON to avoid error like below
   

   "SOMESERVERNAME" indicates that either the object has no columns 
   or the current user does not have permissions on that object

4. If you dont do above tricks then you may see errors like this (INSERT is not allowed when we use DYNAMIC SQL inside nested Stored Procs)

To load output into table you must know column names from the output.  If you dont know you can try to run stored proc without @Columns like below.

EXEC usp_MWS_Report @MarketplaceId =''ATVPDKIKX0DER'', @SellerId=''Axxxxxxxxxxxxx'', @ReportType = ''_GET_MERCHANT_LISTINGS_DATA_''

Once we know columns from report, you can run following script to insert into table.

Full Script – Load MWS Report Output into Table

--//////////////////////////////////
— Step-1 : Create Local Linked server to point to self
--//////////////////////////////////
USE [master]
GO
--change default catalog
--For MSSQL 2012, 2014, 2016, 2017, and 2019 use @provider=N'MSOLEDBSQL' below (SQL Server Native Client 11.0)---
EXEC master.dbo.sp_addlinkedserver @server = N'ME', @srvproduct=N'', @provider=N'SQLNCLI11', @datasrc=N'localhost', @catalog=N'Northwind'
--For MSSQL 2022 or higher use @provider=N'MSOLEDBSQL' below (Microsoft OLE DB Driver for SQL Server)---
--EXEC master.dbo.sp_addlinkedserver @server = N'ME', @srvproduct=N'', @provider=N'MSOLEDBSQL', @datasrc=N'localhost', @catalog=N'Northwind'

EXEC master.dbo.sp_addlinkedsrvlogin @rmtsrvname=N'ME',@useself=N'True',@locallogin=NULL,@rmtuser=NULL,@rmtpassword=NULL
GO
--//////////////////////////////////
— Step-2 : Enable RPC OUT and Disable MSDTC
--//////////////////////////////////
EXEC sp_serveroption 'ME', 'rpc out', true;  
GO
--Below needed to support EXEC + INSERT (dynamic query)
EXEC sp_serveroption 'ME', 'remote proc transaction promotion', false;
GO
--test simple query
select * from OPENQUERY(ME,'select 1')
GO

--//////////////////////////////////
— Step-3 : Load data into temp table from Amazon MWS Report
--//////////////////////////////////
SELECT * INTO #amazon_mws_report
FROM OPENQUERY(me,'
SET NOCOUNT ON;
EXEC usp_MWS_Report 
   @Columns=''[item-name], [item-description], [listing-id]'',
   @MarketplaceId =''ATVPDKIKX0DER'', 
   @SellerId=''Axxxxxxxxxxxxx'', 
   @ReportType = ''_GET_MERCHANT_LISTINGS_DATA_''
WITH RESULT SETS 
(
	(itmname varchar(1000),itmdesc varchar(1000),itmid varchar(1000))
)
')

select * from #amazon_mws_report

Import Amazon MWS Data into SQL Table (Load Report output into temp table)

Conclusion

In this article, we saw how to load Amazon MWS Data into SQL Server. We used simple SQL queries with ZappySys XML / CSV Driver to pull data from Amazon MWS API. ZappySys ODBC PowerPack makes it super easy to consume data from virtually any API (JSON / XML or CSV Web Services), no coding required. Download here to get started with ZappySys ODBC drivers.

The post How to import Amazon MWS data into SQL Server (T-SQL) appeared first on ZappySys Blog.

In our previous article we saw how to read Google Analytics data using SSIS. But what if you don’t use SSIS and you still like to Import Google Analytics data into SQL Server or Read inside other Reporting / ETL Apps (e.g. Excel, Power BI, MS Access … and many more). Not all BI tools comes with native driver / connectivity for Google Analytics. Sometimes they do offer Google Analytics connectivity but don’t offer feature you looking for (e.g. Sort, Segment Filter). In such case you have to look for solution outside.

Well not to worry we will show you how simple it is to connect to Google Analytics using ZappySys JSON Driver (For REST API / Files) in few mins. This driver is one of the best REST API drivers you can find in the market. It is so generic that it can virtually access any REST API you may find internally or on public sites (e.g. Facebook, Salesforce, Azure, AWS). Check these articles to see many more use cases of JSON Driver.

At the end of this article you will learn how to Query Google Analytics data in SSMS like below (Yes that’s correct .. Pretty Awesome!!! ).

Import Google Analytics Data into SQL Server Table (using T-SQL Code)

Testing Google Analytics API

If you are new to Google Analytics API then read little bit about Google Analytics REST API here. Google also offers a really good way to test Analytics API using Query Explorer Tool here. So please check that and understand how to craft correct REST API URL which will be used in the next section.

Using Google Analytics Query Explorer Tool – Create REST API Url (Dimension / Metrics Selection Browser)

Sample Google Analytics API Response

Behind the scene here is how API Request and Response Looks like for Google Analytics REST API. Notice that Authorization Header in below request is automatically added by ZappySys Driver or Query Testing tool above. Also notice nextLink attribute in response, its used to fetch more data. By default each response contains upto 10000 rows.

Request

GET https://www.googleapis.com/analytics/v3/data/ga?ids=ga:185737326&start-date=30daysAgo&end-date=yesterday&metrics=ga:avgSessionDuration&dimensions=ga:date
Authorization: Bearer ya29.GlwUxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

Response

{
    "kind": "analytics#gaData",
    "id": "https://www.googleapis.com/analytics/v3/data/ga?ids=ga:123456789&dimensions=ga:date&metrics=ga:avgSessionDuration&start-date=30daysAgo&end-date=yesterday",
    "query": {
        "start-date": "30daysAgo",
        "end-date": "yesterday",
        "ids": "ga:123456789",
        "dimensions": "ga:date",
        "metrics": ["ga:avgSessionDuration"],
        "start-index": 1,
        "max-results": 1000
    },
    "itemsPerPage": 1000,
    "totalResults": 30,
    "selfLink": "https://www.googleapis.com/analytics/v3/data/ga?ids=ga:123456789&dimensions=ga:date&metrics=ga:avgSessionDuration&start-date=30daysAgo&end-date=yesterday",
    "nextLink": "https://www.googleapis.com/analytics/v3/data/ga?ids=ga:123456789&dimensions=ga:date&metrics=ga:avgSessionDuration&start-date=30daysAgo&end-date=yesterday&start-index=10001&max-results=10000",
    "profileInfo": {
        "profileId": "123456789",
        "accountId": "33445566",
        "webPropertyId": "UA-33445566-3",
        "internalWebPropertyId": "454545454",
        "profileName": "All Web Site Data",
        "tableId": "ga:123456789"
    },
    "containsSampledData": false,
    "columnHeaders": [
        {
            "name": "ga:date",
            "columnType": "DIMENSION",
            "dataType": "STRING"
        },
        {
            "name": "ga:avgSessionDuration",
            "columnType": "METRIC",
            "dataType": "TIME"
        }
    ], "totalsForAllResults": {
        "ga:avgSessionDuration": "49.3779488037477"
    },
    "rows": [ 
		["20190425", "401.38912133891213"], 
		["20190426", "512.49723756906077"], 
		["20190427", "11.53488372093024"], 
		["20190428", "432.148648648648646"], 
		["20190429", "234.650735294117645"],
		.......
		.......
		.......
		.......
		["20190525", "74.123435294117645"]
	]
}

Creating Google API Project (Obtain Client ID / Secret)

Very first step to call any Google API including Google Analytics is to create Google API Project and register OAuth App to obtain Client ID and Client Secret. If you dont want to go through this hassle and start easy way then ZappySys offers Inbuilt Default App on OAuth Connection UI but we strongly recommend you create your own app rather than using Default App because in Default App API call limit is shared by many. Your data is never shared with ZappySys in any case even you use Default App.

Here is how to create API Project to call Google API. Once you create Google API Project make sure you enable Google Analytics API.

So once you have Client ID and Client Secret we can move forward to the next step.

Loading Google Analytics data into SQL Server

In our previous article we saw in depth general idea on how to import REST API data in SQL Server (T-SQL Script) without relying on any ETL tools.  Now lets look at step by step on how to load Google Analytics data into SQL Server.

In this example, our goal is to extract a Google Analytics report which shows average session duration and new users count by date (For last 30 days).

Setup ZappySys Data Gateway

Very first step to access any REST API Data inside SQL Server is to configure ZappySys Data Gateway. We covered this in previous article.  But here are high level steps for initial setup of Data Gateway.

1. Search for Gateway in Start menu and  Select ZappySys Data Gateway
   

   Open ZappySys Data Gateway

2. Create new User in Data gateway on Users tab. Enter username and password (we will use this when we create Linked Server) . Check Admin Option
   

   Add Data Gateway User

Setup Google Analytics API Data Source in Gateway / ODBC

Once gateway user is setup, now lets create a new Data Source for Google Analytics API. In this section we will talk how to create data source in gateway but most instructions can be used to create data source in ODBC too. At the end of this article we explained how to Launch ODBC Datasource UI. Step#1 and 2 are only different, all other steps same in ODBC DSN creation.

1. Click Add Data Source option (Select Native – JSON Driver )
   

   Add Gateway Data Source (Native JSON Driver)

2. Click Edit to configure data source
   

   Edit Gateway Data Source Settings

3. Now lets configure Driver settings.  Click on Load Connection String button.
   

   Load ZappySys Driver ConnectionString to configure UI

4. Enter the following ConnectionString to get started with predefined settings.
   Change ids (111223344 to your own Profile ID in DataPath URL). Other URL Parameters explained in next section.
   

   DRIVER={ZappySys JSON Driver};
   DataPath='https://www.googleapis.com/analytics/v3/data/ga?ids=ga:11223344&start-date=30daysAgo&end-date=yesterday&metrics=ga:avgSessionDuration,ga:newUsers&dimensions=ga:date';
   DataConnectionType=OAuth;
   ScopeSeparator='{space}';
   Scope='https://www.googleapis.com/auth/analytics https://www.googleapis.com/auth/analytics.readonly';
   ServiceProvider=Google;
   Filter='$.rows[*]';
   ArrayTransformType=TransformSimpleTwoDimensionalArray;
   ArrayTransColumnNameFilter='$.columnHeaders[*].name';
   RequestMethod='GET';
   NextUrlAttributeOrExpr='$.nextLink';
   ClientId='xxxxxxxxxxxx';
   ClientSecret='yyyyyyyyyyyyyy';
   UseCustomApp='True'

    
5. URL used in DataPath is most important (parameters explained below) . You can use   Query Explorer Tool here to build same URL.
   

   https://www.googleapis.com/analytics/v3/data/ga?ids=ga:11223344&start-date=30daysAgo&end-date=yesterday&metrics=ga:avgSessionDuration,ga:newUsers&dimensions=ga:date

   Parameters Explained 
   
   Here is some required parameters used in above REST API URL.
   ids=ga:11223344
   This is your Profile ID which you like to extract.  Read more
   start-date=30daysAgo
   This can be yyyy-MM-dd or some other some predefined date keywords (e.g today, yesterday 10daysAgo). Read more.
   end-date=yesterday
   Same as above
   metrics=ga:avgSessionDuration,ga:newUsers
   This can be comma separated list of metrics you like to extract (max 10). Read more.
   dimensions=ga:date
   This can be comma separated list of metrics you like to extract (max 7). Read more.
6. Now its time to configure OAuth settings. Click on Configure Connection. Enter Client ID and Client Secret Obtained in the previous section (see here) and then click Generate Token as below.
   

   Configure Google API Data Source / DSN (Google Analytics API Example)

7. Thats it now can click on Preview Tab and run sample query like below.
   

   select * from $

   –OR–
   (Select Table name from dropdown and generate default query and then you can add alias , remove unwanted columns)
   

   SELECT 
   "ga:date" date, 
   "ga:avgSessionDuration" avgSessionDuration,
   "ga:newUsers" newUsers
   FROM "rows"

   –OR–
   (Type custom query with your own URL generated from here, Change Profile ID – from 11223344 to your own id)
   

   SELECT * FROM $
   WITH(
   	 Src='https://www.googleapis.com/analytics/v3/data/ga?ids=ga:11223344&start-date=30daysAgo&end-date=yesterday&metrics=ga:avgSessionDuration,ga:newUsers&dimensions=ga:date'
   	,IncludeParentColumns='False'
   )

   

Create Linked Server in SQL Server using T-SQL Script

Once our Gateway Data Source is configured we can now move to SQL Server Part to define Linked Server.

Here is how you can define linked server to access Google Analytics Data inside SQL Server. There are two ways to create Linked Server (1)  via T-SQL script (2) via SSMS UI)

Here is how to create using Script.

USE [master]
GO

--drop existing linked server for same name if already found
EXEC master.dbo.sp_dropserver @server=N'GOOGLE_ANALYTICS_LS', @droplogins='droplogins'
GO

EXEC master.dbo.sp_addlinkedserver 
	@server = N'GOOGLE_ANALYTICS_LS', 
	@srvproduct=N'', 
	@provider=N'SQLNCLI', 
	@datasrc=N'localhost,5000', --this is host name and port number where  ZappySys Data Gateway is running
	@catalog=N'ZS-GA' --this must be same name as defined on Data Source tab Grid on ZappySys Data Gateway

EXEC master.dbo.sp_addlinkedsrvlogin 
	@rmtsrvname=N'GOOGLE_ANALYTICS_LS',
	@useself=N'False',
	@locallogin=NULL,
	@rmtuser=N'SOME-GATEWAY-USER', -- user name created on ZappySys Data Gateway
	@rmtpassword='SOME-GATEWAY-PASSWORD' -- password for ZappySys Data Gateway user
GO

Create Microsoft SQL Server Linked Server using SSMS UI

Import Google Analytics Data into SQL Server Table (T-SQL Code)

Now lets see how to run sample query to import Google Analytics Data into SQL Server. Notice that how we have escaped quotes in OPENQUERY.
NOTE: Change id 11223344 with your own Id (use this tool to create URL)

select * into GaApiLoad from OPENQUERY([GOOGLE_ANALYTICS_LS] ,
'SELECT * FROM "rows"
WITH 
 (
   SRC=''https://www.googleapis.com/analytics/v3/data/ga?ids=ga:11223344&start-date=30daysAgo&end-date=yesterday&metrics=ga:avgSessionDuration,ga:newUsers&dimensions=ga:date''
  ,IncludeParentColumns=''False''
 )
')
select * from GaApiLoad

Import Google Analytics Data into SQL Server Table (using T-SQL Code)

Expose Google Analytics Data as View

To make it simple you can expose above query as SQL Server views so you can access them from any Reporting / ETL Tools.

CREATE VIEW vw_Google_Analytics_BounceRate_PageViews_Last30Days
AS
--change ids to your own Profile ID
select * from OPENQUERY([GOOGLE_ANALYTICS_LS] ,
'SELECT * FROM "rows"
WITH 
 (
   SRC=''https://www.googleapis.com/analytics/v3/data/ga?ids=ga:11223344&start-date=2019-04-01&end-date=2019-04-30&metrics=ga:bounceRate,ga:uniquePageviews&dimensions=ga:date''
  ,IncludeParentColumns=''False''
 )
')
GO

Making things Dynamic using Stored Procedure with Parameters

Now let’s make few things dynamic. We will change above query so we can pass Id, Dimensions and Metrics as parameters.

Run below script to Create a stored proc and fetch google analytics data in SQL Server.

use MyDatabase
go
create proc usp_GoogleAnalyticsData
	@ids varchar(1000),
	@startDate varchar(50)='30daysAgo',
	@endDate varchar(50)='yesterday',
	@metrics varchar(200)='ga:avgSessionDuration,ga:newUsers',
	@dimensions varchar(200)='ga:date'	
as

declare @sql varchar(4000)

set @sql='select * from OPENQUERY([GOOGLE_ANALYTICS_LS] ,
''SELECT * FROM "rows"
WITH 
 (
   SRC=''''https://www.googleapis.com/analytics/v3/data/ga?ids=ga:' + @ids 
   +'&start-date='+ @startDate 
   +'&end-date='+ @endDate 
   +'&metrics='+ @metrics 
   +'&dimensions='+ @dimensions 
   +'''''
  ,IncludeParentColumns=''''False''''
 )
'')'

print @sql
execute(@sql)

go

--Example: query google analytics data
exec usp_GoogleAnalyticsData 
	@ids='11223344',  --Change this ID - Obtain from here https://ga-dev-tools.appspot.com/query-explorer/
	@startDate ='30daysAgo',  --or like this 2019-04-01
	@endDate   ='yesterday', --or like this 2019-04-30
	@dimensions='ga:date', 
	@metrics   ='ga:bounceRate,ga:uniquePageviews'

Insert Google Analytics Data into table (Save Stored Procedure Output)

Now what if you like to save Stored Proc output into a table? Well for that you must create table with same structure as stored proc output and then use INSERT INTO sql like below.

--import google analytics data in a table
if(object_id('GaDataLoad') is not null)
	drop table GaDataLoad
create table GaDataLoad([Date] date, BounceRate numeric(10,5), PageViews numeric(10,5))  

insert into GaDataLoad
exec usp_GoogleAnalyticsData 
	@ids='11223344',  --Change this ID - Obtain from here https://ga-dev-tools.appspot.com/query-explorer/
	@startDate ='30daysAgo',  --or like this 2019-04-01
	@endDate   ='yesterday', --or like this 2019-04-30
	@dimensions='ga:date', 
	@metrics='ga:bounceRate,ga:uniquePageviews'

select * from GaDataLoad

Performance Tips / Handling data errors due to missing rows

By default ZappySys API Drivers sends minimum 2 API requests. First one to fetch metadata and second, third… for Data. There will be a time when you wont have any data and it may throw error about no records found because it fails to parse metadata. You can avoid such issue by supplying metadata before hand so you can avoid expensive API calls. Check this article see how you can supply cached metadata in your SQL Query as below. This will avoid Metadata call and speedup significantly. It will also avoid errors due to no rows found for specified criteria.

select * from OPENQUERY([GOOGLE_ANALYTICS_LS] ,
'SELECT * FROM "rows"
WITH 
 (
   SRC=''https://www.googleapis.com/analytics/v3/data/ga?ids=ga:11223344&start-date=30daysAgo&end-date=yesterday&metrics=ga:bounceRate,ga:uniquePageviews&dimensions=ga:date''
  ,IncludeParentColumns=''False''
  ,Meta=''[ 
     {"Name": "ga:date","Type": "String", "Length": 16 },
     {"Name": "ga:bounceRate", "Type": "String", "Length": 36 },
     {"Name": "ga:uniquePageviews", "Type": "String", "Length": 10 }
    ]''
 )
')

ODBC Connection – Google Analytics Data in Other Apps (e.g. SSRS / Power BI / Excel / Tableau)

So far we have talked accessing data inside SQL Server using Data Gateway Approach but what if you like to access in other apps ? Well you have three options.

1. Use Microsoft SQL Server Driver to call Linked Server Queries (OPENQUERY approach we saw earlier)
2. Access Google Analytics Data using ODBC connectivity
3. Use Microsoft SQL Server Driver to send direct SQL queries to Gateway (Bypass Linked Server – Use inner SQL query without OPENQUERY in this case)

Method-1 : Linked Server Approach

First approach most likely works in all cases because most apps will support connecting to SQL Server using OLEDB / ADO.net / ODBC / JDBC Drivers. So calling SQL Queries which uses Linked Server (i.e. OPENQUERY statement)  is advisable.

Method-2 : ODBC Driver Approach

However in some cases this may not be possible (e.g. You don’t have SQL Server inhouse or you don’t want to rely on SQL Server to access API). In such case you can use ODBC connectivity in your app. Since ODBC is widely adopted standard most app out there (Except JAVA apps) should support ODBC Drivers. If you like to use this approach then create ODBC DSN rather than Data Gateway Data source and use it in your Reporting / ETL / Custom Apps.

Open ODBC Data Sources (Create DSN)

ODBC User DSN Tab: Add new Driver Screen

Method-3 : Direct connection to Data Gateway (By pass Linked Server)

Last option we suggest for cases like JAVA Apps / Linux / Mac machines where you cannot install ZappySys ODBC Drivers and you dont have option to use SQL Server Linked Server either. In such case you can try to send SQL Queries to Gateway directly using Microsoft SQL Server Compatible Drivers (i.e. ODBC /JDBC). See this example how we called API Queries inside JAVA Apps.

Google Analytics / REST API Integration in various apps

ZappySys ODBC Drivers built using ODBC standard which is widely adopted by industry for a long time. Which mean the majority of BI Tools / Database Engines / ETL Tools already there will support native / 3rd party ODBC Drivers. Below is the small list of most popular tools / programming languages our Drivers support. If your tool / programming language doesn't appear in the below list, which means we have not documented use case but as long as your tool supports ODBC Standard, our drivers should work fine.  

BI / Reporting Tools Integration	ETL Tools Integration	Programming Languages Integration
Microsoft Power BI Tableau SSRS (SQL Reporting Services) QlikView /Qlik Sense MicroStrategy Google Sheet Microsoft Excel Microsoft Access Oracle OBIEE Many more (not in this list).....	Informatica PowerCenter (Windows) Informatica Cloud SSIS (SQL Integration Services) SQL Server Talend Data Studio Pentaho Kettle Oracle OBIEE Many more (not in this list).....	Visual Studio C# C++ JAVA Python PHP PowerShell T-SQL (Using Linked Server)

 

Conclusion

In this article we explored many ideas of JSON / API integration in SQL Server.  We saw how to create OAuth App for Google API and import Google Analytics data into SQL Server Table without doing any ETL using pure T-SQL code (Query / Views /Stored Procs). You can Download  FREE Trial of ODBC PowerPack and try yourself see how easy it is to query any API inside SQL Server and avoid expensive ETL processes.

The post Import Google Analytics data into SQL Server / Reporting / ETL appeared first on ZappySys Blog.