Successful companies will always prioritize the customer. Across industries and within specific businesses, departments and strategies remain dedicated to the customer life cycle: acquisition, conversion, retention, and loyalty. During each step of the cycle, large and varied amounts of data are consumed, processed, and produced.

Within the last decade, data has developed a growing importance. It is now central to the success and efficiency of every business strategy, process, and application. Many factors have precipitated this shift, including direct factors (like the advent of new technology) and indirect factors (like the rise of e-commerce and shifting demographics).

Data modernization is now key to business success. Companies have embraced the need to modernize, and popular initiatives include migrating to data warehouses, migrating to the cloud, and building sophisticated AI/ML engines to predict outcomes.

Without the proper intervention and oversight, these initiatives can quickly become siloed and less efficient. By becoming aware of common roadblocks within data modernization initiatives, businesses can avoid inefficiencies.

Success is not limited to the avoidance of pitfalls. Organizations must also implement strategies that will generate success. They must incorporate the four-question framework, discussed in this paper, at the onset of their individual modernization program. The four-question framework can be applied to an organization’s goals, data strategy, data architecture, governance strategy, and more.

Virtusa works with businesses to provide a range of tools, accelerators, and frameworks. Virtusa assesses data maturity by using the accelerated roadmap method (ARM) and accelerated solution design (ASD) framework. The framework rests on evaluation criteria, including customer-provided criteria, to make decisions surrounding a company’s ability to scale, its time to market, its reuse of current investments, its costs, its risks, and its degree of future-proofing.

Virtusa's tools work together: The analyzer tool automates the analysis and inventory of legacy database objects, and the code converter tool suite accelerates a company’s migration from ETL code to modern systems. Ultimately, these tools reduce the need for manual labor, thus improving the speed and efficiency of the migration process.