What Are Data Connectors and Why Are They Essential for Businesses?

Each year, businesses become more reliant on digital tools, making increasingly data-driven decisions to further the success of their company, with those decisions being informed by insights derived from that data.

However, with the increased insight that is able to be obtained from data analyses, the wealth of sources containing important, informative data has similarly increased, making it more difficult for businesses to effectively compile and analyse the data.

As a solution to this problem, data connectors are proving themselves essential for business, allowing them to get the most value from their data.

What Is a Data Connector?

A data connector collects data from a variety of sources, including databases, files, CRMs, analytics platforms, cloud applications, and more, and delivers it to one predetermined destination.

This destination is usually a data warehouse or a data lake, since these services can store large amounts of data that can be easily queried and transformed. Once the information is gathered in one location, it can be analyzed more effectively to generate meaningful insight.

How Data Connectors Work

At a basic level, a data connector does more than just move data from one place to another. It establishes a secure link with the source system using authentication methods like API keys or OAuth. Once connected, the connector continuously transfers or synchronizes information, either in scheduled batches or in real time. Many connectors also standardize data into a consistent format, which makes it easier to merge, analyze, and use across different business systems.

This process means data flows smoothly between applications, databases, and cloud services, reducing the complexity of working with multiple formats and ensuring accuracy across the organization.

Snapshot vs. Incremental Data Retrieval

To remain useful, data must be regularly retrieved from each source so that analysis is always based on the most current, relevant information. Connectors typically handle this in one of two ways:

• Snapshot retrieval: All the data from the source is recaptured by the connector, including both old and new data.
• Incremental retrieval: Only the new data that has accumulated since the last run is retrieved.

In most cases, incremental retrieval is the better option since it requires less storage, energy, and cost compared to pulling the entire dataset every time.

Common Types of Data Connectors

There are many kinds of data connectors, each designed to integrate with specific systems or use cases:

• Database connectors: Direct connections into relational, NoSQL, OLTP, or OLAP databases.
• API connectors: Links into software applications, often SaaS tools like Salesforce or HubSpot, that expose data endpoints.
• Flat file connectors: For legacy systems that export data as CSV, JSON, or XML.
• Cloud storage connectors: Secure connections to services like Google Drive, OneDrive, or Amazon S3.
• Event stream and queue connectors: Capture real-time data from modern applications or microservices.
• IoT connectors: Pull in data from distributed devices and sensors.
• Custom connectors: Tailor-made solutions for unique or proprietary systems.

This range of connector types means businesses can bridge almost any data gap, whether they rely on legacy systems or the latest cloud-native platforms.

The Benefits of Data Connectors

1. A Complete 360° View of Performance

By compiling data from multiple systems — such as customer engagement tools, financial records, and operational systems — businesses can see performance from every angle.

2. Seamless Integration with BI Tools

Data connectors not only aggregate information into one central location, but also integrate with business intelligence tools. This makes it possible to build dashboards, create reports, and visualize data trends without relying on complex manual processes.

3. Improved Productivity

Without connectors, teams must manually gather and transfer information from different systems. This approach is time-consuming, prone to error, and often means data is updated less frequently. Connectors automate the process, freeing employees to focus on higher-value tasks.

4. Data Governance and Accuracy

Because connectors handle authentication and transfer automatically, they reduce human error and enforce consistency. This improves data reliability and supports compliance by ensuring that sensitive or regulated information is integrated securely.

5. Data-Backed Predictions

By compiling historical data efficiently, connectors allow businesses to analyze past patterns and predict future outcomes. This helps companies prepare for likely events, maximize success, and quickly fix issues that could cause performance declines.

Real-World Example of Data Connectors in Action

Imagine a retail company launching a nationwide marketing campaign. To measure success, they need to connect multiple data sources:

• A data warehouse tracking store sales,
• APIs from social media and marketing platforms showing engagement,
• A CRM system linking those engagements to customer records,
• Financial systems calculating campaign ROI.

Without connectors, teams would spend hours manually extracting and combining information. With connectors in place, all of this data is automatically pulled together in near real time, giving leaders a single view of performance and enabling them to quickly adjust strategy if needed.

Making It Actionable

In today’s digitally driven business environment, data connectors are no longer optional. They are a critical piece of modern data infrastructure, helping companies integrate systems, streamline processes, improve accuracy, and ultimately unlock the full value of their data.

If you’re ready to move faster, reduce manual work, and make smarter decisions, data connectors are a game-changer for your business. Try Domo for free and see how easy it is to simplify your data integration and take the next step.