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In the high-stakes world of business, mergers and acquisitions (M&A) represent a strategic move for companies to accelerate growth, diversify offerings, and enhance market presence. As reported by Bain & Company, the world of strategic M&A witnessed 27,000 deals announced, totaling approximately $2.4 trillion in the year 2023. M&A deals, whether they involve acquiring a competitor, entering a new market, or merging with a complementary business, reshape industries.

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.

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.

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.

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.

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.

Your organization is likely sitting atop vast quantities of diverse data. However, all that data must undergo certain processes before you can fully leverage it. Data discovery is among those processes. Let’s learn more about it.

Workflows determine how organizations conduct processes. These workflows can initially be very straightforward—just a simple series of steps that must be completed sequentially to achieve a particular outcome. However, the steps can become more complicated as business processes and requirements become more extensive. Your organization needs to keep these workflows running smoothly even as they become more complicated.

Smooth and effective data migration helps organizations move data across systems efficiently to maintain their competitive advantage. Still, Gartner reports that only 17% of initiatives involving data migration are completed within their budgets or set timelines. Understanding these data migration challenges is the first step toward overcoming them. In this blog, we’ll explore data migration and its different types, challenges, and strategies for dealing with them.