Systems | Development | Analytics | API | Testing

When Facebook acquired WhatsApp in 2014, they had to integrate an enormous amount of data—450 million monthly active users generating billions of messages, photos, and videos daily—into Facebook’s systems. This data migration required precise planning and execution to ensure a smooth transition and prevent data loss while maintaining the accuracy and integrity of the information.

Imagine that you’re a healthcare provider who’s just treated a patient. It’s time to get paid for your services, but you don’t want to deal with endless paperwork and unnecessary phone calls. There’s a better and more streamlined way to handle it — the electronic way. Electronic Data Interchange (EDI) is responsible for providing just that.

Every organizational activity or interaction today generates data. This quickly creates large amounts of data at organizational and departmental levels, but data generation is only the beginning. No matter how much raw data you have at your disposal, you can only leverage it fully if you know how to process it correctly for your requirements. You can process data flows using one of two approaches: batch processing or batch processing.

Across industries worldwide, businesses are turning to ERP to automate repetitive tasks, enjoy easy scalability, stay flexible, and derive insights using a single source of truth. According to Statista, Enterprise Resource Planning (ERP) software market revenue will reach USD 53.15 billion this year. If your organization implements an ERP system, you’ll find that data migration is one of the most critical components of this process.

Technological advancements are driving mergers and acquisitions (M&As) at an unprecedented rate. Companies aim to extend their market reach, acquire new technologies, and achieve cost synergies through these deals. For instance, in 2023, nearly 40,000 mergers and acquisition (M&A) deals were completed worldwide. For a successful merger, companies should make enterprise data management a core part of the due diligence phase.

In business, speed is key. When facing rapid change, adapting slowly eats into an organization’s revenue, opportunities, and market share. This has led organizations to deploy business process automation technologies to streamline processes, roll out products faster, and deliver services of a higher quality. However, organizations often stitch together disparate automation tools, leading to disjointed IT ecosystems and bloated licensing costs.

Developing, distributing, and monitoring a drug or medical device is an extensive process. It involves the coordination of people, systems, and substantial amounts of data. Production slowdowns negatively impact the product lifecycle, adding unnecessary costs and keeping valuable products from the patients who need them. The need for automation is evident.

Think about a time when insufficient information or inaccessible data slowed you down. Or maybe a time when your work required manual data entry that resulted in human error and rework, taking time away from higher value tasks. These moments of process frustration and inefficiency are exactly what workflow optimization helps address. Workflow optimization describes the strategies and measures taken to improve the flow of daily tasks and make processes more efficient.

Workflow automation involves automating repetitive tasks and processes in a sequence using technology, reducing the need for manual intervention. It involves designing, creating, deploying, and automating business processes like data entry and customer interactions. Workflow automation uses software to replace manual and paper-based processes. Its primary goal is to ensure that the right people work on the right tasks at the right time.