How to Approach Data Integration Project

Today, in the internet-focused world we live in, data is widely considered to be among the world’s most valuable resources because of how much potential revenue and the business value it can provide. Data has become a valuable commodity, similar to commodities like oil and gold. As you can see, the data is priceless, and companies are worried about putting their data at risk when attempting to connect systems that collect data. 

Data integration is the process of combining data from several different sources into one unified view, to make the data more actionable and valuable to an enterprise. It’s about efficiently managing data and making it available to those who need it.

The benefits of data integration are numerous.  Here are just a few:

  • Better data integrity and data quality
  • Seamless knowledge transfer between systems
  • Easy available, fast connections between data stores
  • Increased efficiency and ROI
  • Better customer and partner experience
  • Better decision-making
  • Complete view of business intelligence, insights, and analytics

That’s great; but before any data integration occurs careful planning and a range of assessments need to take place. The steps below illustrate the proven plan that we follow to deliver integrated data successfully to our clients.

Define the project

Clearly define your goals and your purpose of the integration. Some questions to answer include:

  • What are you trying to achieve?
  • What are your expectations of this integration?
  • What is the desired workflow?

After asking these questions, document comprehensive functional and non-functional requirements for clarity of scope and deliverables. See examples of the objectives for our data integration projects.

Know and understand the systems

Review all the systems involved with the data, from extraction to every system that uses the final, consolidated output, and have a definite understanding of the business processes involved. 

Connect the systems via data integration platform

Identify any network or firewall configuration necessary for data transfer. Do database or FTP ports that need to be opened? Are data connectors, Web services, APIs, and SDKs available to extract data programmatically?

Determine if there is a flat or structured file exchange and whether txt, csv and xml are an option. Consider whether there is any configuration, modification or programming of the system itself needed to enable data interchange. The objective here is to enable applications and services to communicate with each other.

Implement the project

Identify a project champion. This person will engage all the right stakeholders in the most effective and efficient manner to remove roadblocks and track progress.

 Identify the stakeholders. Which departments within the organization use the data or systems and should be involved in the project? Who within those departments will be involved in the design and implementation of the project? Which senior leaders will have input and oversight?

Test the systems thoroughly before implementation, using sample data. This ensures that data quality rules and data mappings have been implemented correctly.


When everything is completed, you can start relaxing and switch to support mode. If you are using the Etlworks data integration platform, it is easy. Our dedicated support team is here for you 24/7.

Etlworks is also a great choice for your data integration project because we can connect anything. We support the widest range of data formats and targets while maintaining low latency and accuracy.

Lastly, Etlworks can scale large and small. Etlworks supports any number of inputs, from low to high volume, so you can start small and scale up over time.

Contact us for a demo and 14-day trial to see if Etlworks works for your organization.

Author: Olena S.

Data Architect, University of Pittsburgh

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