Purpose
In this article, Allbound System Admins will learn about Data Connectors and how a data connector can be used to get more powerful platform analytics.
Introduction
An Allbound Data Connector is either an Open Database Connectivity (ODBC) or Java Database Connectivity (JDBC) interface that allows you to connect your Allbound Data to your Business Intelligence (BI) tool.
While platform analytics are already available via Allbound Channel Insights, Allbound's Data Connectors allow you to:
- Use the BI tool of your choice: If you are already using PowerBI or Tableau for all your other business intelligence and data visualization you can connect your Allbound data to continue to use a single BI tool for all your data analysis and visualization.
- Get insights across multiple SaaS data sources: Your BI tool allows you to connect multiple data sources including your Allbound PRM, your CRM, your ERP, your marketing automation system, your custom success platform, and many other data sources. This allows you to join your data together to answer your more complex questions.
- Expand your analytics with increased flexibility in a BI Tool beyond Channel Insights: You may have a need for analytics that differ from what is provided in Channel Insights. Using a BI tool with your Allbound data allows you to create your own queries, graphs, and dashboards giving you the flexibility to control how you are analyzing and visualizing your data.
The diagram below illustrates how your BI tool can connect to all your business applications and tools to gain insights across your centralized company data.
The diagram below illustrates the different data you can import from your business applications into your BI tool for creating valuable centralized insights.
The Allbound Data Pipeline
Your Allbound data is stored in numerous databases within the platform. Allbound utilizes AWS Athena to allow customers to analyze data from a single Allbound data pipeline. AWS Athena is a cost-effective and scalable solution for processing and analyzing large datasets, without the need for complex data pipelines.
Key Features and Benefits of AWS Athena | Description |
Secure Network Connectivity | Connecting to Athena using the service endpoint over HTTPS ensures a secure and reliable networking experience. We manage the AWS infrastructure, guaranteeing that your data remains protected during transmission and that query results are delivered safely. |
Robust Security Measures |
Encryption in transit: We configure TLS encryption for regional service endpoints, such as Amazon Athena, and for query results that stream to JDBC or ODBC clients. Encryption at rest: We enable SSE-S3 at the S3 storage level, ensuring Amazon S3 encrypts your objects before saving them on disks in data centers and decrypts them when you download the objects. This process provides an additional layer of security for your data stored in Amazon S3. |
Managed Authentication and Authorization |
We configure customer-specific IAM credentials that grant read-only access to each customer's unique datasets. We also establish procedures to periodically rotate these credentials in accordance with our organization's security policies, ensuring secure and compliant access to your data. |
High Availability, Durability, and Resilience |
Athena and S3 are designed to provide high availability, durability, and resilience for your data storage and querying needs. These robust AWS services ensure that your data remains secure and accessible, empowering you to focus on creating visualizations and reports with confidence. |
Optimized Performance |
When using a BI Tool to access your data stored in S3 through AWS Athena, enjoy these performance-enhancing benefits: Efficient data retrieval: Tailor your queries and employ filters to minimize the volume of data transmitted over the internet. This approach ensures a smoother experience, particularly when working with larger datasets. Optimal internet connection: Ensure a high-quality internet connection with sufficient bandwidth and minimal latency or packet loss. Scheduling data source loading during off-peak hours can further enhance the experience by reducing potential network congestion. Choose the appropriate mode: Select between Import and DirectQuery modes based on your specific use case and performance requirements. Import mode is ideal for situations where data refresh frequency is low and quick data analysis is needed. DirectQuery mode is more suitable when real-time data access is required, but it may be affected by the performance of the source system and network conditions. |
By leveraging these key features and benefits, customers can enjoy a seamless and efficient experience using their BI Tool when accessing their data in AWS, while Allbound manages and maintains the cloud infrastructure.
How to Request a Data Connector
To request a data connector, please submit a Support ticket or email help@allbound.com with the following info:
- Subject = Request for Data Connector
- Information to include in the body:
- BI Tool you will be using
An engineer will reply to your request with the following key pieces of information necessary to complete the Data Connector Setup:
- S3 bucket
- Schema
- Workgroup
- User
- Password
Once received, see the following applicable article for setting up the data connector to your BI Tool: