Business and enterprise applications have relied on databases to store information and process it for results and inferences. But the architecture of databases used over the last decade has been used with certain limitations
Most databases have been built to use with specific applications and for specific purposes. In other words, applications and databases are configured to match each other to generate specific results for end users. Change the obligation and the database needs to be configured to match the purpose. In the present era of digital transformation and business agility, the biggest hurdles remain to manage the complex databases and the enormous growth in duplication of data.
However, till newly businesses had no option but to wade through large, extensive, complex and limited database structures, locked to legacy applications that generated predetermined reports and dashboards. Changing the requirements of the management dashboard has meant recreating the database, a long and demanding process.
While the basic core ERP engine still remains, the driver of enterprise transaction processing cannot be ignored. The associated ecosystem of tools and interfaces to engage and access this engine are in the process of being transformed. Creating and replicating databases to meet new requirements, the significant lead times associated with the process, the limited benefits and gains at the end of it, has led to the coming out of next generation ERP.
While duplication and complexity of databases structures are offshoots of traditional inward facing IT investments, the challenges of data deluge are coming from another source. Sensor-generated data, data from social media applications, consumer data generated from mobile and other connected devices, are generating exponential volumes of data that are in an unstructured format. For any business, the external unstructured data needs to be linked to internally structured databases to be brought into context and generate business friendly conclusions. Many of the open source data warehouses are limited in their ability to put together with internal, structured application databases.
The limitations of ERP applications to meet the increasing demands of business to compete in real time, the more and more long lead times to make modifications, the inability to manage new sources of data generation, have pushed business managers to independently test the waters of cloud-based applications available on the multitude of connected devices. And question the longer term viability of expensive and cumbersome ERP systems.
IT managers are now faced with answering two fundamental questions. How can they leverage previous investments in ERP systems while meeting the requirements of business managers faced with the onslaught of digital transformation? How can they rapidly integrate existing ERP systems with newer, more open, agile digital applications? The primary objective of such initiatives being to transform and rebuild the business into one adapted for change and to perform as a high-velocity enterprise.
The transformation process leading to building next generation ERP systems and architecture typically involves the following:
The most significant aspect of Modern ERP solutions is simplification at every level. This includes system architecture, program structure, data model, user interface, intuitiveness, data results, data dashboards, data interpretations, amongst others.
Other characteristics of Modern ERP applications include inbuilt-modularity of solutions, hybrid approach to deployment, extensive interoperability through open APIs, backward and forward platform compatibility, intrinsic open source approach, and flexible architecture for future product expansion.
Another question that arises for end users is how to migrate into next-generation ERP solutions. A ray of sunlight here vendors is offering all possible migration paths. End users can opt for on-premise or hybrid migration options. If it is on-premise they can opt for Greenfield, all-new environment migration. Or they can opt for upgrading selected hardware, and a phased-wise approach for improvement. For a hybrid IT migration, the optimal mix of private and public cloud deployments are selected.
It has been decades since the first databases were used by enterprises; the IT industry may now be on a fresh and revamped path of win-win relationships with their eco-system of end customers.