Data Integration Practices: An Introduction

Data Integration Practices attempt to address the complexities and various components of data integration. These practices aim to make transitions smooth and flawless.

Data Integration is increasingly becoming popular as organizations utilize more applications and systems. Companies need the data stored in these systems to be stored together, in order to form a comprehensive view.

This collected data can then be used to provide actionable business intelligence.

Benefits of Data Integration Practices

Robust Data Integration practices can prevent duplicity of data

With robust Data Integration practices in place, organizations can get access to a single version of any data, preventing data duplicity and keeping the data synced across several applications.

Data Integration offers a comprehensive glimpse of an organization’s business

Data integration affords a comprehensive, informative glimpse of clients, customers or accounts operated and handled by an organization.

Data is easily accessible across the organization

Data Integration makes various types of data easily accessible to business leaders and employees across the organization. 

Challenges faced in the Data Integration process

There are several challenges in the Data Integration process.  Let’s highlight a few challenges that businesses and organizations face.

Technical complexities

The technical complexities inherent in the Data Integration process makes Data Integration a challenge. Businesses make significant investments in integration projects. Approximately 25% of IT budgets are allocated to Data Integration projects on an annual basis. As for returns on investment (ROI) McKinsey reports reveal that most IT projects deliver 56% less value that expected.

Applications developed in isolation

In many cases, businesses build applications and deploy them in isolation, while Data Integration is not prioritized. Businesses should ideally build and deploy applications while simultaneously attempting to address probable Data Integration challenges. They should be prepared to suitably handle organizational issues like how to optimize employee workflow, while also being equipped to address compliance and future technology upgrades.

Applications need to be developed which enable easy Data Integration

A business organization consists of several different departments working together to achieve organizational goals. Various departments’ needs and reasons for utilizing applications are bound to change over a period of time; and they would require the deployment of new applications. When new applications are deployed, it is very likely that these applications will need to integrate seamlessly with non-compliant systems. Data Integration practices must be developed in line with an organization’s various business activities.

While application developers and IT engineers are constantly working on developing enhanced products and solutions that can deliver better results, thereby positively impacting an organization’s performance, they seldom factor in the need for seamless data integration between different applications.

Need for a streamlined and seamless process

A major challenge faced by businesses is streamlining the Data Integration process in such a way that minimizes cost, optimizes utility of invested resources and yields positive returns on investment. Automation of the integration process is the solution. Automation shifts the Data Integration tasks workload from IT professionals to a dedicated software solution.

Ultimately, comprehensive and highly effective Data Integration processes provide business organizations with a unified view of important, actionable data. Organizations must address their Data Integration needs by forming strategic partnerships with data integration providers who have a comprehensive understanding of the challenges and can develop futuristic, compliant Data Integration solutions and systems. 

Explore Evolvus’ Data Integration solution that offers intelligent tool kits that address the complete data migration lifecycle and allow seamless consolidation of disparate systems.