Data Modernization – continued 

This article picks up the discussion on data modernization with an emphasis on the expanded opportunities to restructure the data. Legacy systems were inherently built as online transaction processing systems and online analytical processing systems and usually as a monolithic server. With the shift to microservices for application modernization, data can now be owned by individual microservices that can choose to use the technology stack and specifically the database that makes most sense for that microservice without undue influence or encumbrance from other services. The popularity of unstructured storage – both big data for batch processing and event storage for streaming applications are evident from the shift to data lakes. That said, this does not mean relational storage is not required. 

Data technologies in recent years have popularized both structured and unstructured storage. This is fueled by applications that are embracing cloud resources. The two trends are happening simultaneously and are reinforcing each other. 

Data modernization means moving data from legacy databases to modern databases. It comes at a time when many databases are doubling their digital footprint. Unstructured data is the biggest contributor to this growth and includes images, audio, video, social media comments, clinical notes, and such others. Organizations have shifted from a data architecture based on relational enterprise-based data warehouses to data lakes based on big data. If the survey from IT spends is to be believed, a great majority of organizations are already on their way towards data modernization with those in the Finance service firms leading the way. These organizations reported data security planning as part of their data modernization activities. They consider the tools and technology that are available in the marketplace as the third most important reason in their decision making. 

Drivers for one-time data modernization plans include security and governance, strategy and plan, tools and technology, and talent. Data modernization is a key component of, or reason for, migrating to the cloud. The rate of adoption of external services in the data planning and implementation is about 44% for these organizations.