Disruptive technology has become the new normal in today’s market. Disruptions in innovation and technology are directly influencing factors such as technological needs, business growth, market requirements, new trends and so on. It is enabling businesses to keep evolving constantly and remain market leaders. For example, earlier human intervention was required for any file transfer between systems but post technological advancement, it has evolved into safe file transfer protocol (SFTP) interface which leads to transfer of files with a quicker turnaround time. Today’s market needs and trends have innovated it further to real-time mode of transfer through application programming interface (API).
Business needs constantly evolve which enforce technology and processes to change drastically. In today’s digital era, information plays a vital role in the planning, strategy, and decision-making capabilities of a business. To derive information in a shorter turnaround time, every organization would require processed and unprocessed data at its disposal. When such type of data is present with partners or third-party vendors in the cloud, there arises a major need for data mart warehouse where an organization captures or replicates data touchpoints at its end by replicating the partners’ data structure. This empowers organizations to process data independently for arriving at strategic and innovative business decisions.
A paradigm shift has taken place over the past few decades with organizations adopting software as a service (SaaS)-based cloud services and moving away from on-premise services. Products on the cloud work in the business model that entirely operates on the uniqueness of its code base, data structure and algorithm to derive the desired output of its service, which may be talent management, analytics, sales and delivery or AI-driven forecaster.
Following are the business reasons to have access to data points at the organization’s end:
Redefine HR analytics using self-existing infrastructure
Minimize dependency on partners or third-party vendors
Take decisions based on previous and forecasted data
Minimize manual administrator tasks
Drive disruptive innovation based on transaction data
Design unique business plans based on user data
Plan, design, and implement solutions with minimal turnaround time
Products on the cloud use innovative business models that help businesses decide whether to invest in a new analytics platform, or expose the organization’s unique data structure model to third-party vendors. The challenges and opportunities have enabled cloud-based service providers to innovate a unique data structure for client organizations or third-party vendors upon request. This will help create the unique schema data structure without violating IP rights, and also meet the business needs of the client by sharing data points at regular intervals.
For instance, in one of the implementations, we observed a few shortcomings when this unique schema was set up by a client. There was a notable impact on the business, as this model defies the rule of thumb of data mart which replicates the structure at the source and destination of two systems. Few of the observations were:
Concerns on the accuracy of data due to unique data structure
Reconciliation of data between source and destination systems
Scope of automation to eliminate human intervention at the provider and consumer ends
Quantitative and qualitative mechanism over data touchpoints between parent and child architectures
Automated health checks on source and destination systems
However, on an overall basis, the unique schema data structure does provide confidence to organizations which deal with a huge volume of transactions. The unique schema data structure in data mart has ensured business needs are met without any violation of copyrights. It has also empowered clients to create and configure business processes according to their needs in real time.