Data Connectors Role in Business Intelligence

With the rapid increase in technology adoption, Software-As-A-Service (SaaS) space has rapidly evolved too. There are software solutions for almost everything. While this is a major positive for enterprises, the major downside is the data is with SaaS application owners. For decision-makers, it becomes difficult to make strategies if they do not have one place to see the entire data from various departments of the organization. 

Let’s say there is a sales team and a marketing team in a company. The sales team has CRM software that captures data of sales prospects and the marketing team has social media management tools and Email marketing software that has a dataset of intended target audiences or potential new prospects. The key problem here is the data is coming from three different sources – CRM, Social Media and Email marketing software. Aggregating this data is a challenge that needs to be solved. 

Having a single source of truth will help in quicker and smooth decision making for the business. This is where the role of Data Connectors comes into play. 

We will deep dive into understanding data connectors, how they exactly work and why should enterprises have them implemented in their organization. 

What are Data Connectors? 

Data connector can be defined as a process that has an automated scheduled data pulls from different source locations and pushed it into a defined destination location. 

There are many important variations in sources, destinations and schedules. We will be focusing on the ones that are highly common for the data analytics teams and used daily. 

Sources:

Data sources can be categorized as follows: 

• Databases 
• SaaS applications 
• File systems 
• Events 

According to a study, more than 40 SaaS applications are being used by enterprises that have less than 50 employees. And more than 200 SaaS applications are used for a staff strength of 1000+ employees. This indicates that the number of data sources for an enterprise is skyrocketing. There are PDFs and Excel files as data sources too that are not considered in the study. 

Data Extraction from a Data Source 

The Data Analytics team wants the data to be made available in such a way that a huge amount of data can be stored and processed through SQL. Cloud data warehouses like Snowflakes or Data Lake is use to process large chunks of data. Data warehouses and Data Lakes have gained popularity as they can be scaled at very affordable rates.  

The data needs to be extracted from the source and pushed to the destination after some interval  So that there will be no gap into the data visualization reports leaders are using for decision making  

For example, you pull the data of sales prospects from Hubspot (Sales CRM) and push it on a Data Warehouse (Cloud/on-premises) . Doing this activity once in a while may create data gaps in your reports and won’t be giving the real picture. That’s why scheduling is also important in connectors. 

Why Use Data Connectors? 

Here are some of the reasons why your enterprise should consider having data connectors:  

1. Single Source of Truth: Using Data Connectors you can pull the data from different SaaS Applications and Events to define destination for c a central repository of ness data. A single source of truth will help you create a holistic picture of your organization.
   
2. Better Decision Making: When the data is stored in a structured, consolidated and presented in form of interactive dashboards, it is easy to make decisions for the management. This leads to a direct positive impact on the growth of the business as data-driven decisions are made based on factual evidence.
3. Enhanced Productivity: Data connectors allows for consolidated data from various sources. This enhances productivity as there is no need to extract data manually from various sources. With the scheduling feature, data is automatically pulled again and again and updated frequently. This enables your personnel to focus on core activities rather than doing mundane tasks of data aggregation, every time.
4. Streamline Operations: Data connectors help to gather data not only from different sources but also from various departments of organizations. Data from sales, logistics, finance, IT and other departments of an organization is collected and managed in a cohesive manner. This way, real-time insights are provided from every department. 

The Intellify Advantage 

We at Intellify, building custom Data Connectors for our clients for last 9+ years. We have state of the art, highly generic connectors framework for different applications and SaaS platforms. 

Our team of experts can work with you to understand your data challenges and create a custom solution to overcome the same. Let’s schedule a free consultation with us today!