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.

Organizations today are accumulating data more than ever. Traditional data management approaches, such as centralized data warehouses and siloed data marts, are struggling to keep pace with the ever-increasing volume, velocity, and variety of information. The complexity of modern data environments is outpacing the capabilities of these legacy systems and demands a more agile and distributed solution.

The modern data-driven approach comes with a host of benefits. A few major ones include better insights, more informed decision-making, and less reliance on guesswork. However, some undesirable scenarios can occur in the process of generating, accumulating, and analyzing data. One such scenario involves organizational data scattered across multiple storage locations. In such instances, each department’s data often ends up siloed and largely unusable by other teams.

With organizations prioritizing data-driven decision-making, the amount of collected and stored data is reaching historic highs. Meanwhile, organizations are democratizing access across all functions to convert this data into actionable insights. Since more users will work with sensitive data, ensuring secure access is more important than ever. Organizations must regulate and maintain the relationship between their data assets and users. Why?