• June 30, 2022

Insight to realize revenue: don’t wait for data to drive it

Rocket data virtualizationMainframe data virtualization brings instant insight into a comprehensive view of your customer, driving revenue through repeat purchases, higher customer satisfaction, and customer acquisition. Our recent webinar, entitled Unlocking Revenue Opportunities with Mainframe Data Virtualization, with Bryan Smith, VP of Research and Development, and CTO, and Forrester’s  Noel Yuhanna, Principal Analyst, serving Enterprise Architecture professionals  explored and detailed how customer facing organizations must leverage insight instantly to maximize revenue from customers.  Noel Yuhanna particularly noted that in the age of the customer empowered buyers demand new levels of customer obsession.

The age of the customer is fueling a high velocity of customer interactions that can lead to greater revenue opportunities. These customer interactions are growing exponentially in enterprises thanks to new online and offline channels, and the need for multiple customer facing organizations, i.e. marketing, service, and sales, to ensure the best customer experience.

However, there is a central problem in all enterprises. While the amount of customer data grows exponentially, the ability to act on that data, instantaneously, to meet a customer need is prevented by siloed data warehouses that do not provide a comprehensive, multi-dimensional view, nor change fast enough, to optimize the customer experience. This multi-dimensional view is not only transactional data, but behavioral, including social and all forms of service interactions with the customer. The complexity of gaining customer insight is further impacted by not transforming the data credibly into meaningful insight through today’s business intelligence tools. Ultimately, data needs to be fully integrated, secure, reliable, and always available, or what we refer to as instant insight.

In Unlocking Revenue Opportunities with Mainframe Data Virtualization, Bryan and Noel bring together new and traditional elements that drive and transform data into instant customer insight – mainframe transactional data, structured and unstructured data in the Cloud, mobile, and business intelligence. Mainframe data virtualization enables data structures that are designed independently, to be leveraged together, in real time, and without data movement. Now architects and business intelligence professionals can work together to create data architectures that scale and extend to meet changing customer and business demands.

The webinar provided a use case on wealth managers responding to questions from clients on portfolio performance. Reviewing the performance of a portfolio is complex, given multiple investments, the buying and selling of investments, and calculating returns based on investment changes and reinvested dividends. Without mainframe data virtualization, providing an accurate response to clients involved accessing mainframe transactional data from multiple data stores, and then loading that data through multiple steps into a data warehouse for processing to ultimately assess performance. Most importantly, in this case, the client or customer experience is improved by delivering instant insight into portfolio returns that enables the wealth manager to meet the demanding and ever changing needs of clients.

The solution of mainframe data virtualization eliminates the need to move data and instead enables the synthesizing of data at the point in which it is available, providing direct access to line of business managers to answer customer requests instantaneously. For IT organizations and business intelligence professionals, no programming is involved, changes are not required of business intelligence tools, nor is the movement of data required.

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Calvin Fudge 0 Posts

Calvin Fudge spends an inordinate amount of time focused on the challenges companies face with data integration. In the last decade he has worked extensively on data services and data virtualization, and is part of a team that helped launch Rocket's mainframe data virtualization solution. He currently serves as director of product marketing for Rocket's Data Lab, where he is helping customers increase business insight with real-time mainframe analytics.


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