Spotify Web API exposes rich data for artists, albums, tracks, playlists, and categories. If you want to build dashboards from this data, you can connect Spotify to Power BI through an ODBC layer and query API responses using SQL.

In this tutorial, you will learn how to configure the ZappySys ODBC Driver for REST APIs for Spotify, test the connection, and load Spotify data into Power BI.

Steps

Create a Spotify Developer App

1. Open the Spotify Developer Dashboard and sign in with any free or premium Spotify account.
2. Click Create app, then enter an app name, description, and a redirect URL (for example: http://127.0.0.1:3000).
   

   Spotify – Create app

3. Open app Settings and copy your Client ID and Client Secret.
4. Store these credentials securely.

Create a New ODBC DSN Using ZappySys JSON Driver

1. Search for ODBC in the Windows Start menu and open ODBC Data Source Administrator.
   
2. In User DSN or System DSN, click Add.
3. Select ZappySys JSON Driver and click Continue.
   

Configure the Connection and API Settings

1. Enter a Spotify endpoint URL. Example:
   

   https://api.spotify.com/v1/search?q=genre:pop&type=artist&limit=50

2. In Connection Type, select OAuth and click Configure.
3. Set Credential Type to OAuth2 / Client Credentials Grant and fill in the following values:
   • Client ID: Your Spotify Client ID
   • Client Secret: Your Spotify Client Secret
   • Access Token URL: https://accounts.spotify.com/api/token
   • Scopes/Permissions: (leave empty)
4. Click OK to save HTTP authentication settings.
   

   Spotify ODBC OAuth connection

5. Set HTTP Request Method to GET.
6. Add the following HTTP Header:
   • Accept: application/json
7. Set JSON Path Filter to:
   

   $.artists.items[*]

8. Click Test Connection, then click OK to save the DSN.
   

   Spotify – ODBC JSON driver configuration

Preview Spotify Data in ODBC Driver

1. Open the Preview tab in the DSN configuration window.
2. Generate a query and click Preview Data.
3. Confirm rows are returned. If not, recheck credentials, endpoint URL, and JSON Path Filter.
   

   Spotify – ODBC preview data

Connect Power BI to Spotify via ODBC

1. Open Power BI Desktop.
2. Go to Home > Get Data > More….
3. Search for ODBC and click Connect.
   

   Power BI – Get data from ODBC connection

4. Select your Spotify DSN from the data source list.
5. Optionally enter a custom SQL query in Advanced options.
   

   Power BI – Enter query Spotify

6. Click OK, review the preview, and click Load.
   

   Power BI – Spotify Result

7. In the Navigator, select fields or tables you want to import into your model.

Query Spotify Data with SQL

Use custom SQL queries in the ODBC driver or Power BI to shape data before loading.

Example 1: List All Artists

SELECT
    id,
    name,
    type,
    popularity,
    followers_total,
    uri
FROM _root_

Example 2: Filter Highly Popular Artists

SELECT
    id,
    name,
    popularity,
    followers_total
FROM _root_
WHERE popularity >= 80
ORDER BY popularity DESC

Example 3: Artists with Large Followings

SELECT
    id,
    name,
    followers_total,
    popularity
FROM _root_
WHERE followers_total >= 1000000
ORDER BY followers_total DESC

Example 4: Search by Genre

SELECT
    id,
    name,
    genres,
    popularity
FROM _root_
WHERE genres LIKE '%pop%'
ORDER BY popularity DESC

Conclusion

Connecting Spotify to Power BI using the ZappySys ODBC Driver gives you a fast way to analyze music catalog trends and artist metrics with SQL and dashboards. Once your DSN is configured, you can reuse the same pattern for tracks, albums, playlists, categories, and market-specific reporting.

Explore more connectors and API integrations with the ZappySys ODBC Drivers.

The post How to get data from Spotify into Power BI appeared first on ZappySys Blog.

Introduction

Spotify provides rich music and podcast metadata through its Web API, including artists, albums, tracks, playlists, and categories. Many data teams need this data in SQL Server for analytics, trend reporting, and catalog enrichment.

In this tutorial, you will learn how to connect Spotify API data to SQL Server Integration Services (SSIS) by using ZappySys SSIS PowerPack. This approach helps you automate extraction and loading without building a custom API client.

Steps

Create a Spotify Developer App

1. Go to the Spotify Developer Dashboard and sign in with any free or premium Spotify account.
   

   Spotify – Create app

2. Click Create app, give it a name, description, and a Redirect URI (for example http://127.0.0.1:3000).
3. Go to the app Settings page and copy your Client ID and Client Secret.
4. Store both values securely and avoid hard-coding secrets directly in package components.

Create an OAuth2 Connection in SSIS

1. Create or open your SSIS project and package.
2. In Connection Managers, right-click and choose New Connection….
3. Select ZS-OAUTH from the SSIS connectors list.
   

   Create a new SSIS OAuth API Connection Manager

4. Set the following values:
   • OAuth Provider: Custom
   • OAuth Version: OAuth2
   • OAuth Grant Type: Client Credentials Grant
   • Client ID: Your Spotify Client ID
   • Client Secret: Your Spotify Client Secret
   • Access Token URL: https://accounts.spotify.com/api/token
   • Scopes/Permissions: (leave empty)
5. Click Test Connection to confirm a token is issued successfully, then click OK.
   

   Spotify – OAuth connection

Create and Configure JSON Source

1. Add a Data Flow Task in Control Flow and open it.
   

   Drag and drop Data flow

2. In Data Flow, drag and drop ZS JSON Source.
   

   SSIS JSON Source – Drag and Drop

3. Open the JSON Source editor and enable Use credentials.
4. Select the Spotify OAuth2 connection you created.
5. Set the API URL to a Spotify endpoint. Example to search artists by genre:
   

   https://api.spotify.com/v1/search?q=genre:pop&type=artist&limit=50

6. Set HTTP Request Method to GET.
7. Add the following HTTP Header:
   • Accept: application/json
8. Set JSON Path Filter based on the endpoint. For the search artists endpoint:
   

   $.artists.items[*]

9. Click Preview to confirm rows are returned, then click OK.
   

   Spotify – JSON source

Configure Destination and Load into SQL Server

1. Add an Upsert destination (or another destination of your choice, such as a Trash destination or JSON/CSV/XML destination).
2. Connect the output arrow from JSON Source to the destination component.
3. Configure your SQL Server connection and target table.
4. Check the options you want to use: Insert or/and Update.
5. Map the source columns to destination columns in the Mappings section.
   

   Spotify – Upsert destination

6. Click OK and execute the package.
7. Validate that Spotify rows have been loaded into your SQL Server table.
   

   Spotify – Upsert Destination example

Conclusion

You now have a practical SSIS pattern to extract Spotify Web API data and load it into SQL Server by using ZappySys SSIS PowerPack. With OAuth2 Client Credentials authentication, pagination handling, and proper column mapping, you can operationalize Spotify catalog data for BI and reporting use cases.

Explore the full capabilities of the ZappySys SSIS PowerPack to extend this pipeline with transformations, audits, error handling, and SQL Server Agent scheduling.

The post SSIS Tutorial: How to get data from Spotify appeared first on ZappySys Blog.

Introduction

Hivebrite is a community management platform used for memberships, events, directories, and engagement workflows. Many teams need Hivebrite data in SQL Server for reporting, segmentation, and operational analytics.

In this tutorial, you will learn how to connect Hivebrite API data to SQL Server Integration Services (SSIS) by using ZappySys SSIS PowerPack. You can then automate extraction and loading without writing a custom API client.

Steps

Prepare Hivebrite API access

1. Sign in to your Hivebrite admin area and go to Integrations → External Integrations.
2. Click Create a Service App and give it a name.
   • Copy the Client ID (UUID) and Client Secret shown at creation — the secret is displayed only once and cannot be retrieved afterward.
3. Identify your Authorization Host based on the zone that hosts your community:
   • US: auth.us.hivebrite.com
   • EU: auth.eu.hivebrite.com
   • APAC: auth.apac.hivebrite.com
   • CH: auth.ch.hivebrite.com

Create an OAuth2 connection in SSIS

1. Create or open your SSIS project and package.
2. In Connection Managers, right-click and select New Connection….
3. Select ZS-OAUTH from the SSIS connectors list.
   

   Create a new SSIS OAuth API Connection Manager.

4. Set the following values:
   • OAuth Provider: Custom
   • OAuth Version: OAuth2
   • OAuth Grant Type: Client Credentials Grant
   • Client ID: Your Hivebrite Client ID (UUID)
   • Client Secret: Your Hivebrite Client Secret
   • Access Token URL: https://auth.{zone}.hivebrite.com/oauth2/token
   • Scopes/Permissions: (leave empty)
     

     Hivebrite – OAuth connection configuration

5. Go to the OAuth2 Grant Options tab and add the following to the Extra attributes for the token request parameter:
   

   audience=partner

6. Then click OK to save the configuration.
   

   Hivebrite – OAuth connection advanced configuration

Create and configure JSON Source

1. Drag a Data Flow Task into Control Flow and open it.
   

   Drag and drop Data Flow

2. In Data Flow, drag and drop ZS JSON Source.
   

   SSIS JSON Source – Drag and Drop

3. Open the JSON Source editor and enable Use credentials.
4. Select the Hivebrite OAuth2 connection you created.
5. Set the API URL using your community’s API host. Example to extract members:
   

   https://{your-community}.hivebrite.com/admin/v4/members

6. Set HTTP Request Method to GET.
7. Add the following HTTP Header:
   • Accept: application/json
8. Set JSON Path Filter to $.data[*] — Hivebrite wraps all collection responses under an data array.
9. Click Preview to confirm rows are returned, then click OK.
   

   Hivebrite – JSON source example

Configure destination component

1. Add an Upsert destination (or another destination of your choice, such as a Trash destination or JSON/CSV/XML destination).
2. Connect the output arrow from JSON Source to the destination component.
3. Configure your SQL Server connection and target table.
4. Check the options you want to use: Insert or/and Update.
5. Map the source columns to destination columns in the Mappings section.
   

   Hivebrite – Upsert destination

6. Click OK and execute the package.
7. Validate that Hivebrite rows have been loaded into your SQL Server table.
   

   Hivebrite – Upsert Destination example

Conclusion

You now have a repeatable SSIS pattern to extract Hivebrite API data and load it into SQL Server by using ZappySys SSIS PowerPack. With OAuth2 Client Credentials authentication, proper pagination, and column mapping, you can operationalize Hivebrite data for BI and reporting workflows.

Explore the full capabilities of the ZappySys SSIS PowerPack to extend this setup with advanced transformations, retry logic, auditing, and scheduling through SQL Server Agent.

The post SSIS Tutorial: How to get data from Hivebrite appeared first on ZappySys Blog.

Cin7 is a connected inventory and order management platform used by growing businesses to synchronise products, stock, orders, and customer data across sales channels. Many organisations need Cin7 data in Power BI to monitor inventory health, order trends, and fulfilment performance.

Using the ZappySys ODBC Driver for REST APIs, you can query Cin7 REST API data with SQL and load it into Power BI without writing custom connector code.

This tutorial shows how to create a Cin7 ODBC DSN, configure API authentication, preview data, connect Power BI, and run practical SQL queries.

Steps

Get Cin7 API Credentials

1. Sign in to your Cin7 account.
2. Open Settings → Integrations & API → API v1 in your Cin7 admin portal.
   • Note your API Username shown on the page.
   • Click Add New API Connection, give it a name (e.g. ZappySys), and copy the generated API Key.
   

   Cin7 – Generate new API connection

3. Store both values securely — the API Username and API Key together act as your login credentials.
   

   Cin7 – API credentials

4. Note your API base URL: https://api.cin7.com/api.

Create a New ODBC DSN Using ZappySys JSON Driver

1. Search for ODBC in the Windows Start menu and open ODBC Data Source Administrator.
   
2. In User DSN or System DSN, click Add.
3. Select ZappySys JSON Driver, then click Continue.
   

Configure Cin7 API Connection

1. Enter a Cin7 endpoint URL in this format:
   https://api.cin7.com/api/v1/Products
2. In Connection Type, select HTTP and click Configure.
3. Set Credential Type to Basic Auth (Username/Password).
4. Set Username to your Cin7 API Username.
5. Set Password to your Cin7 API Key.
6. Click OK to save HTTP authentication settings.
   

   Cin7 – ODBC HTTP connection configuration

7. Set HTTP Request Method to GET.
8. Set JSON Path Filter to $.Products[*] for the Products endpoint.
9. Click Test Connection, then click OK to save the DSN.
   

   Cin7 – JSON Driver configuration

Preview Cin7 Data in ODBC Driver

1. Open the Preview tab in the DSN configuration window.
2. Generate a query and click Preview Data.
3. Confirm rows are returned. If not, recheck endpoint URL, credentials, and JSON Path Filter.
   

   Cin7 – JSON Driver result

Connect Power BI to Cin7 via ODBC

1. Open Power BI Desktop.
2. Go to Home > Get Data > More….
3. Search for ODBC and click Connect.
   

   Power BI – Get data from ODBC connection

4. Select your Cin7 DSN from the data source list.
5. Optionally enter a custom SQL query in Advanced options.
   

   Cin7 – Power BI select driver

6. Click OK, review the preview, and click Load.
   

   Cin7 – Power BI result

7. In the Navigator, select fields or tables you want to import into your model.

Query Cin7 Data with SQL

Use custom SQL queries in the ODBC driver or Power BI to shape data before loading.

Example 1: List Products

SELECT
    ID,
    StyleCode,
    Name,
    Category,
    Brand,
    IsActive,
    ModifiedDate
FROM Products

Example 2: Active Products Only

SELECT
    ID,
    StyleCode,
    Name,
    IsActive
FROM Products
WHERE IsActive=true

Example 3: Recently Modified Products (Last 30 Days)

SELECT
    ID,
    StyleCode,
    Name,
    ModifiedDate
FROM Products
WHERE ModifiedDate >= <<today-10d,FUN_TO_DATE>>

Conclusion

Connecting Cin7 to Power BI using the ZappySys ODBC Driver gives you a fast, SQL-friendly way to build inventory and sales analytics from Cin7 API data. You can centralise operational data, model it in Power BI, and publish dashboards without building custom connectors.

Explore the full capabilities of the ZappySys ODBC Drivers to integrate Cin7 and other APIs into your reporting workflow.

The post How to get data from Cin7 into Power BI appeared first on ZappySys Blog.

Cin7 is a connected inventory and order management platform used by growing businesses to synchronise products, stock, orders, and customer data across multiple sales channels. Many organisations need Cin7 data in SQL Server for reporting, demand planning, fulfilment tracking, and analytics.

In this tutorial, you will learn how to connect to Cin7 REST APIs using SQL Server Integration Services (SSIS) with the ZappySys SSIS PowerPack. This approach helps you build repeatable ETL pipelines without writing custom API integration code.

Steps

Get Cin7 API Credentials

1. Sign in to your Cin7 account.
2. Open Settings → Integrations & API → API v1 in your Cin7 admin portal.
   • Note your API Username shown on the page.
   • Click Add New API Connection, give it a name (e.g. ZappySys), and copy the generated API Key.
   

   Cin7 – Generate new API connection

3. Store both values securely — the API Username and API Key together act as your login credentials.
   

   Cin7 – API credentials

Get Cin7 Base URL and Endpoint Path

1. Identify the REST endpoint you want to query (for example, products, customers, or sales orders).
2. Keep your API base URL and endpoint path ready for SSIS configuration.
3. Example:
   https://api.cin7.com/api/v1/Products

Create an HTTP Connection in SSIS

1. Create or open your SSIS project and package.
2. In Connection Managers, right-click and select New Connection….
3. Select ZS-HTTP from the SSIS connectors list.
4. Set Credentials Type to Basic Auth.
5. Enter your API Username in the Username field and your API Key in the Password field
6. Click OK to save the connection.
   

   Cin7-HTTP connection

Create and Configure JSON Source

1. Drag a Data Flow Task into Control Flow and open it.
2. In Data Flow, drag and drop the ZS JSON Source.
3. Open the JSON Source editor and enable Use credentials.
4. Select the Cin7 HTTP connection you created earlier.
5. Set the API URL. Example to extract products:
   

   https://api.cin7.com/api/v1/products

6. Set HTTP Request Method to GET.
7. Add the following HTTP Header:
   1. Accept: application/json
8. Set JSON Path Filter based on the endpoint (for example, $.Products[*] for the Products endpoint).
9. Click Preview to confirm rows are returned, then click OK.
   

   Cin7 – JSON Source configuration

Configure Destination Component

1. Add an Upsert destination (or another destination of your choice, such as a Trash destination or JSON/CSV/XML destination).
2. Connect the output arrow from JSON Source to the destination component.
3. Configure your SQL Server connection and target table.
4. Check the options you want to use: Insert or/and Update.
5. Map the source columns to destination columns in the Mappings section.
   

   Cin7 – Upsert destination

6. Click OK and execute the package.
7. Validate that Cin7 rows have been loaded into your SQL Server table.
   

   Cin7 – Upsert Destination example

Conclusion

You now have a working SSIS integration to extract Cin7 data using ZappySys SSIS PowerPack and Cin7 REST APIs. With this pattern, you can automate extraction of inventory, product, and order data into SQL Server for reporting and analytics.

Explore the full capabilities of the ZappySys SSIS PowerPack to optimise your data integration tasks. By applying this pattern, you can extend your solution to include transformations, data validation, error handling, and scheduling through SQL Server Agent.

The post SSIS Tutorial: How to get data from Cin7 appeared first on ZappySys Blog.

While ZappySys SSIS PowerPack includes a dedicated Amazon S3 CSV File Destination, many users ask whether there is a dedicated JSON destination for Amazon S3.

The good news is that you can already achieve this using existing ZappySys components without writing any custom code. In this article, we’ll explore three different approaches to exporting JSON files to Amazon S3 using SSIS.

Prerequisites

Before you begin, ensure you have the following:

• ZappySys SSIS PowerPack installed
• An Amazon S3 connection is configured
• An SSIS package
• A data source such as SQL Server, API, CSV, Excel, XML, or JSON

Method 1: Export JSON Directly to Amazon S3 (Recommended)

If your goal is simply to generate a JSON file in Amazon S3, the easiest approach is to use the Export JSON File Task.

The task supports writing the generated JSON directly to an Amazon S3 bucket, eliminating the need to create a temporary local file.

Recommended for: Direct exports with minimal package complexity.

Step 1 – Add Export JSON File Task

Add the Export JSON File Task to your Control Flow.

Step 2 – Configure the Source

Select the data source you wish to export and configure the Source Connection (OLEDB, ADO.NET (SQL), or ODBC).

Step 3 – Configure Amazon S3 Destination

In the destination settings:

• Select Amazon S3 as the destination.
• Select or create an Amazon S3 connection.
• Specify the Bucket Name.
• Optionally specify a Folder.
• Enter the output JSON file name.

Step 4 – Execute the Package

Run the package.

The Export JSON File Task generates the JSON document and uploads it directly into your Amazon S3 bucket.

Benefits

• No intermediate local files
• Simple configuration
• Faster execution
• Easier package maintenance

Method 2: Generate JSON Locally, then Upload to Amazon S3

If your workflow requires validating, compressing, encrypting, archiving, or otherwise processing the JSON file before upload, first generate the JSON locally and then upload it using the Amazon S3 Task.

Recommended for: Advanced ETL workflows requiring intermediate file processing.

Step 1 – Generate the JSON File

Use the Export JSON File Task to save the JSON document locally.

C:\Exports\Customers.json

Step 2 – Upload using Amazon S3 Task

Add an Amazon S3 Task after the Export JSON File Task.

Configure the task to:

• Upload File
• Select the generated JSON file
• Select the Amazon S3 Bucket
• Specify the destination folder (optional)

Step 3 – Delete the Local File (Optional)

Enable Delete File After Successful Transfer if you no longer need the local copy.

Alternatively, use the Advanced File System Task to:

• Delete uploaded files
• Move processed files to an archive folder
• Rename processed files
• Create backup copies

Benefits

• Validate JSON before upload
• Archive processed files
• Compress or encrypt files
• Greater workflow flexibility

Method 3: Generate JSON in Data Flow and Save to Amazon S3

If your package already performs transformations in a Data Flow, you can generate JSON without using the Export JSON File Task.

Use the JSON Generator Transform together with the Amazon S3 CSV File Destination.

Although the destination component is named CSV File Destination, it can also write JSON when configured appropriately.

Recommended for: Existing Data Flow-based ETL packages.

Step 1 – Add JSON Generator Transform

Add a JSON Generator Transform to your Data Flow.

Step 2 – Configure Amazon S3 CSV File Destination

Connect the JSON Generator output to the Amazon S3 CSV File Destination.

Configure the destination as follows:

• Disable Header Row
• Disable Quote Around Values
• Output only the generated JSON column

The generated JSON is written directly to Amazon S3.

Benefits

• Entire workflow remains inside the Data Flow
• Works with existing transformations
• No temporary files
• High-performance pipeline

Which Method Should You Choose?

Conclusion

Although ZappySys SSIS PowerPack does not include a dedicated Amazon S3 JSON Destination component, exporting JSON files to Amazon S3 is fully supported using existing components.

Depending on your ETL requirements, you can:

• Export JSON directly to Amazon S3 using Export JSON File Task.
• Generate a local JSON file and upload it using Amazon S3 Task.
• Create JSON in a Data Flow using JSON Generator Transform and write it using the Amazon S3 CSV File Destination.

These approaches provide flexible, code-free solutions for automating JSON exports to Amazon S3 in SSIS.

Related Articles

• Export JSON from SQL Server using SSIS
• Load Data from SQL Server to Amazon S3
• Split Large Files while Loading Data using SSIS
• Amazon S3 Task Documentation

The post How to Export JSON Files to Amazon S3 using SSIS (3 Easy Methods) appeared first on ZappySys Blog.

Birdeye is a customer experience and reputation management platform that helps businesses manage reviews, listings, messages, and customer interactions across channels. Many organisations need Birdeye data in Power BI to track review trends, location performance, customer sentiment, and service responsiveness.

Using the ZappySys ODBC Driver for REST APIs, you can connect to Birdeye APIs, query data with SQL, and load it directly into Power BI dashboards without writing custom connector code.

This tutorial shows how to create an ODBC DSN for the Birdeye API, preview data, connect Power BI, and build analytics using custom SQL queries.

Prerequisites

1. A Birdeye account with API access enabled.
2. Power BI Desktop installed on your machine.
3. Basic understanding of SQL and Power BI data modelling.
4. Finally, install the ZappySys ODBC Driver.

Steps

Get Birdeye API Key

1. Sign in to your Birdeye account.
2. Open API settings in your Birdeye admin portal.
3. Generate or copy your API key.
   

   Birdeye – Generate token

4. Store the API key securely and do not expose it in logs or shared files.

Create a new ODBC DSN using ZappySys JSON Driver.

1. Search for ODBC in the Windows Start menu and open ODBC Data Source Administrator.
   
2. In the User DSN or System DSN tab, click Add.
3. Select ZappySys JSON Driver and click Continue.
   

Configure the Connection and API Settings

1. Enter the base URL:
   https://api.birdeye.com/v1/review/businessid/{business_id}
2. In Connection Type, select HTTP and click Configure.
3. Select Static token/API key for Credential type.
4. Use x-api-key in the Auth header name.
5. In Auth Scheme, select {none}
6. Click OK to save the configuration.
   

   Birdeye – ODBC HTTP connection

7. Set HTTP Request Method to GET.
8. Set the following values in the HTTP headers:
   1. Accept: application/json
   2. Content-Type: application/json
9. Set JSON Path Filter to match the review array in the response, for example:
   

   $.hoursOfOperations[*] or $.serviceAreas[*]

10. Click Test Connection to verify connectivity, then click OK to save the DSN.
    

    Birdeye – the JSON Driver configuration

Preview Birdeye data in ODBC Driver

1. Go to the Preview tab.
2. Generate a query, then click Preview Data to confirm rows are returned.
3. If no data is returned, verify your API key, business ID, and JSON Path Filter.
   

   Birdeye – the JSON source preview

Connect Power BI to Birdeye via ODBC

1. Open Power BI Desktop.
2. Click Get Data from the Home ribbon.
3. Click More…, search for ODBC, and click Connect.
   

   Power BI – Get data from ODBC connection

4. Select your Birdeye ODBC DSN from the dropdown list.
5. Optionally, enter a custom SQL query in Advanced options.
   

   Birdeye – Power BI select driver

6. Click OK, then click Load to import data.
   

   Birdeye – Power BI preview

7. In the Navigator window, select the columns you want to load.

Use Other Birdeye Endpoints

You can switch endpoints in DSN settings or custom queries to extract other modules:

• Businesses: https://api.birdeye.com/v1/businesses
• Locations: https://api.birdeye.com/v1/locations
• Messages: https://api.birdeye.com/v1/messages
• Listings: https://api.birdeye.com/v1/listings

Conclusion

Connecting Birdeye to Power BI using the ZappySys ODBC Driver makes it easy to build review and customer-experience analytics without custom connectors. With SQL-based access to Birdeye API responses, you can monitor rating trends, sentiment signals, and location performance in one place.

Explore the full capabilities of the ZappySys ODBC Drivers to integrate Birdeye and other APIs into your Power BI ecosystem.

Need Help?

If you encounter any issues, our support team is here to help:

1. Live Chat – Use the chat widget (bottom-right corner of this page)
2. Email – support@zappysys.com
3. Support center – Visit the ZappySys Support Portal

The post How to get data from Birdeye into Power BI appeared first on ZappySys Blog.

Introduction

Birdeye is a customer experience and reputation management platform that helps businesses manage reviews, listings, messages, and customer interactions across channels. Many organisations need Birdeye data in SQL Server for reporting, sentiment tracking, location performance analysis, and operational dashboards.

In this tutorial, you will learn how to connect Birdeye APIs to SQL Server Integration Services (SSIS) using ZappySys SSIS PowerPack. This approach helps you build repeatable ETL pipelines without writing custom API integration code.

Prerequisites

1. SQL Server Integration Services (SSIS) is installed.
2. Visual Studio with SSIS extension or SQL Server Data Tools (SSDT) is available.
3. A Birdeye account with API access enabled.
4. A valid Birdeye API key.
5. ZappySys SSIS PowerPack is installed on your machine.

Steps

Get Birdeye API Key

1. Sign in to your Birdeye account.
2. Open API settings in your Birdeye admin portal.
3. Generate or copy your API key.
   

   Birdeye – Generate token

4. Store the API key securely and do not expose it in logs or shared files.

Create an HTTP Connection in SSIS

1. Create or open your SSIS project and package.
2. In Connection Managers, right-click and select New Connection….
3. Select ZS-HTTP from the SSIS connectors list.
   

   Create a new HTTP connection

4. Set Credentials Type to Static token/API key.
5. Paste your token in the token value field.
6. Use x-api-key in the Auth header name.
7. In Auth Scheme, select {none}
8. Click OK to save the connection.
   

   Birdeye – HTTP connection

Create and Configure JSON Source

1. Drag a Data Flow Task into Control Flow and open it.
   

   Drag and drop Data flow

2. In Data Flow, drag and drop the ZS JSON Source.
   

   SSIS JSON Source – Drag and Drop

3. Open the JSON Source editor and enable Use credentials.
4. Select the Birdeye HTTP connection you created earlier.
5. Set the API URL. Example to extract reviews:
   

   https://api.birdeye.com/resources/v1/business/{{User::businnessID}}

6. Set HTTP Request Method to GET.
7. Set the following values in HTTP headers:
   1. Accept: application/json
   2. Content-Type: application/json
8. Set JSON Path Filter based on response shape (for example, $.hoursOfOperations[*] or $.serviceAreas[*]).
9. Click Preview to confirm rows are returned, then click OK.
   

   Birdeye – the JSON source configuration

Use Other Birdeye Endpoints (Optional)

You can reuse the same SSIS package pattern with other Birdeye endpoints:

• Businesses: https://api.birdeye.com/v1/businesses
• Locations: https://api.birdeye.com/v1/locations
• Reviews: https://api.birdeye.com/v1/review/businessid/{business_id}
• Messages: https://api.birdeye.com/v1/messages

Configure Destination Component

1. Add an Upsert destination (or another destination of your choice, such as a Trash destination or a JSON/CSV/XML destination).
2. Connect the output arrow from JSON Source to the destination component.
3. Configure your SQL Server connection and target table.
4. Check the options you want to use: Insert or/and Update
5. Map the source columns to destination columns in the Mappings section.
   

   Birdeye – Upsert destination

6. Click OK and execute the package.
7. Validate that Birdeye rows have been loaded into your SQL Server table.
   

   Birdeye – Upsert Destination example

Conclusion

You now have a working SSIS integration to extract Birdeye data using ZappySys SSIS PowerPack and Birdeye APIs. With this pattern, you can automate the extraction of reviews, location data, and customer interaction metrics into SQL Server for reporting and analytics.

Explore the full capabilities of the ZappySys SSIS PowerPack to optimise your data integration tasks. By applying this pattern, you can extend your solution to include transformations, data validation, error handling, and scheduling through SQL Server Agent.

Need Help?

If you encounter any issues, our support team is here to help:

1. Live Chat – Use the chat widget (bottom-right corner of this page)
2. Email – support@zappysys.com
3. Support center – Visit the ZappySys Support Portal

The post SSIS Tutorial: How to get data from Birdeye appeared first on ZappySys Blog.

Pipedrive is a CRM platform used by sales teams to manage leads, deals, contacts, activities, and pipelines. Many organisations need this data in Power BI to monitor sales performance, pipeline health, conversion rates, and team productivity.

Using ZappySys ODBC Driver for REST APIs, you can connect to Pipedrive APIs, query CRM data with SQL, and load it directly into Power BI dashboards without writing custom connector code.

This tutorial shows how to create an ODBC DSN for Pipedrive API, preview data, connect to Power BI, and build analytics using custom SQL queries.

Prerequisites

1. A Pipedrive account with API access enabled.
2. Power BI Desktop is installed on your machine.
3. Basic understanding of SQL and Power BI data modelling.
4. Finally, install the ZappySys ODBC Driver.

Steps

Get Pipedrive API token

1. Sign in to your Pipedrive account.
2. Go to Personal Preferences and open API.
3. Copy your API token and store it securely.
   

   Pipedrive – Personal token

Create a new ODBC DSN using ZappySys JSON Driver

1. Search for ODBC in the Windows Start menu and open ODBC Data Source Administrator.
   
2. In the User DSN or System DSN tab, click Add.
3. Select ZappySys JSON Driver and click Continue.
   

Configure the Connection and API Settings

1. Enter the base URL:
   https://api.pipedrive.com/v1/deals?api_token={your_api_token}
2. Set HTTP Request Method to GET.
3. Set JSON Path Filter to:
   

   $.data[*]

4. Click Test Connection to verify connectivity, then click OK to save the DSN.
   

   Pipedrive – JSON Driver configuration

Preview Pipedrive data in ODBC Driver

1. Go to the Preview tab.
2. Generate a query, then click Preview Data to confirm rows are returned.
3. If no data is returned, verify your API token, endpoint URL, and JSON Path Filter.
   

   Pipedrive – JSON Driver result

Connect Power BI to Pipedrive via ODBC

1. Open Power BI Desktop.
2. Click Get Data from the Home ribbon.
3. Click More…, search for ODBC, and click Connect.
   

   Power BI – Get data from ODBC connection

4. Select your Pipedrive ODBC DSN from the dropdown list.
5. Optionally, enter a custom SQL query in Advanced options.
   

   Pipedrive – Power BI select driver

6. Click OK, then click Load to import data.
   

   Pipedrive – Power BI preview

7. In the Navigator window, select the columns you want to load.

Query Pipedrive data with SQL

For advanced analytics, use custom SQL queries in Power BI or the ODBC tool.

Example 1: List All Deals

SELECT 
    id,
    title,
    value,
    currency,
    status,
    stage_id,
    add_time,
    update_time
FROM data

Example 2: Open Deals Only

SELECT 
    id,
    title,
    value,
    currency,
    stage_id,
    expected_close_date
FROM data
WHERE status = 'open'

Conclusion

Connecting Pipedrive to Power BI using the ZappySys ODBC Driver makes it easy to build CRM analytics dashboards without building custom connectors. With SQL-based access to Pipedrive API responses, you can monitor pipeline performance, deal progression, and sales activity in one place.

Explore the full capabilities of the Zappysys ODBC Drivers to integrate multiple data sources and build comprehensive Power BI dashboards. By combining Pipedrive data with other sources, you can create unified views of your operational data.

Need help?

If you encounter any issues, our support team is here to help:

1. Live Chat – Use the chat widget (bottom-right corner of this page)
2. Email – support@zappysys.com
3. Support Center – Visit the ZappySys Support Portal

The post How to get data from Pipedrive into Power BI appeared first on ZappySys Blog.

Introduction

Pipedrive is a popular CRM platform used by sales teams to manage deals, leads, contacts, activities, and pipelines. It offers REST APIs that let you access CRM data programmatically. Many organisations extract Pipedrive data into SQL Server for operational reporting, sales dashboards, and analytics.

In this tutorial, you will learn how to connect Pipedrive APIs to SQL Server Integration Services (SSIS) using ZappySys SSIS PowerPack. This approach helps you build repeatable ETL pipelines without writing custom API integration code.

Prerequisites

1. SQL Server Integration Services (SSIS) is installed.
2. Visual Studio with SSIS extension or SQL Server Data Tools (SSDT) is available.
3. A Pipedrive account with API access.
4. A valid Pipedrive API token.
5. ZappySys SSIS PowerPack is installed on your machine.

Steps

Generate Pipedrive API Token

1. Sign in to your Pipedrive account.
2. Go to Personal Preferences > API.
3. Copy your API token and store it securely.
   

   Pipedrive – Personal token

Create and Configure JSON Source

1. In your SSIS package, navigate to the Variables section and create the following variables: PersonalToken (String) — Enter the Personal Token from the previous step.
2. Drag a Data Flow Task into Control Flow and open it.
   

   Drag and drop Data flow

3. In Data Flow, drag and drop the ZS JSON Source.
   

   SSIS JSON Source – Drag and Drop

4. Open the JSON Source
5. Set the API URL with the variable. Example to extract deals:
   

   https://api.pipedrive.com/v1/deals?api_token={{User::PersonalToken}}

6. Set HTTP Request Method to GET.
7. Set JSON Path Filter to:
   

   $.data[*]

8. Click Preview to confirm rows are returned, then click OK.
   

   Pipedrive – JSON source configuration

Use Other Pipedrive Endpoints (Optional)

You can reuse the same SSIS package pattern with other Pipedrive endpoints:

• Persons: https://api.pipedrive.com/v1/persons?api_token={your_api_token}
• Organizations: https://api.pipedrive.com/v1/organizations?api_token={your_api_token}
• Activities: https://api.pipedrive.com/v1/activities?api_token={your_api_token}
• Leads: https://api.pipedrive.com/v1/leads?api_token={your_api_token}
• Pipelines: https://api.pipedrive.com/v1/pipelines?api_token={your_api_token}

Configure Destination Component

1. Add an Upsert destination (or another destination of your choice, such as a Trash destination or a JSON/CSV/XML destination).
2. Connect the output arrow from JSON Source to the destination component.
3. Configure your SQL Server connection and target table.
4. Check the options you want to use: Insert or/and Update
5. Map the source columns to destination columns in the Mappings section.
   

   Pipedrive  – Upsert destination

6. Click OK and execute the package.
7. Validate that Pipedrive  rows have been loaded into your SQL Server table.
   

   Pipedrive  – Upsert Destination example

Conclusion

You now have a working SSIS integration to extract Pipedrive data using ZappySys SSIS PowerPack and Pipedrive REST APIs. With this pattern, you can automate extraction of deals, contacts, and activity data into SQL Server for reporting and analytics.

Explore the full capabilities of the ZappySys SSIS PowerPack to optimize your data integration tasks. By applying this pattern, you can extend your solution to include transformations, data validation, error handling, and scheduling through SQL Server Agent.

Need Help?

If you encounter any issues, our support team is here to help:

1. Live Chat – Use the chat widget (bottom-right corner of this page)
2. Email – support@zappysys.com
3. Support Center – Visit the ZappySys Support Portal

The post SSIS tutorial: How export data from Pipedrive appeared first on ZappySys Blog.